Dissertations / Theses on the topic 'Efficient demand side management'

With the continuous growth in population and energy demands, more attention is being paid to energy consumption issues in residential environments. From the perspective of energy providers, high-accuracy short-term load forecasting plays a significant role in the energy generation plan, efficient energy distribution process and electricity price strategy optimisation. At the user-end, the home energy management system (HEMS) has been proposed as a cost-effective solution to reduce the electricity cost in households, while maintaining users' comfort and reducing the pressure on energy providers. To handle these challenges, in this work, we introduce a novel model based on the Transformer network to provide an accurate day-ahead load forecasting service. Our model combines a similar day selection approach involving the LightGBM and k-means algorithms. As compared to the traditional RNN-based approach, our proposed model can avoid to falling into local minimum and outperform in the global search. To evaluate the performance of our proposed model, we set up a series of simulation experiments based on the energy consumption data in Australia from 2006 to 2010. The results reveal that the average MAPE our proposed model can achieve is 1.09, the RNN is 2.37 and the LSTM is 1.69. Furthermore, it is a challenge to design cost-effective scheduling strategies for HEMS, which take many objectives into consideration while potentially benefiting both users and providers. In our work, we propose a new approach named adaptive multi-objective salp swarm algorithm (AMSSA), based on the traditional multi-objective salp swarm algorithm (MSSA), to realise a multi-objective optimisation approach for the power scheduling problem. AMSSA not only fulfils the trade-off among users' comfort, electricity cost and peak to average ratio (PAR), but also enhances the convergence speed for the overall optimisation process. Moreover, we also set up a testbed by using smart appliances and implemented our design on an edge-based energy management system. The experiment results demonstrated a reduction in both electricity cost (47.55%) and PAR (45.73%) as compared with the case without a scheduling scheme.

This thesis investigates the modelling of drying processes for the promotion of market-led Demand Side Management (DSM) as applied to the UK Public Electricity Suppliers. A review of DSM in the electricity supply industry is provided, together with a discussion of the relevant drivers supporting market-led DSM and energy services (ES). The potential opportunities for ES in a fully deregulated energy market are outlined. It is suggested that targeted industrial sector energy efficiency schemes offer significant opportunity for long term customer and supplier benefit. On a process level, industrial drying is highlighted as offering significant scope for the application of energy services. Drying is an energy-intensive process used widely throughout industry. The results of an energy survey suggest that 17.7 per cent of total UK industrial energy use derives from drying processes. Comparison with published work indicates that energy use for drying shows an increasing trend against a background of reducing overall industrial energy use. Airless drying is highlighted as offering potential energy saving and production benefits to industry. To this end, a comprehensive review of the novel airless drying technology and its background theory is made. Advantages and disadvantages of airless operation are defined and the limited market penetration of airless drying is identified, as are the key opportunities for energy saving. Limited literature has been found which details the modelling of energy use for airless drying. A review of drying theory and previous modelling work is made in an attempt to model energy consumption for drying processes. The history of drying models is presented as well as a discussion of the different approaches taken and their relative merits. The viability of deriving energy use from empirical drying data is examined. Adaptive neuro fuzzy inference systems (ANFIS) are successfully applied to the modelling of drying rates for 3 drying technologies, namely convective air, heat pump and airless drying. The ANFIS systems are then integrated into a novel energy services model for the prediction of relative drying times, energy cost and atmospheric carbon dioxide emission levels. The author believes that this work constitutes the first to use fuzzy systems for the modelling of drying performance as an energy services approach to DSM. To gain an insight into the 'real world' use of energy for drying, this thesis presents a unique first-order energy audit of every ceramic sanitaryware manufacturing site in the UK. Previously unknown patterns of energy use are highlighted. Supplementary comments on the timing and use of drying systems are also made. The limitations of such large scope energy surveys are discussed.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2005.
Includes bibliographical references (p. 278-289).
The main objective of this research is to identify robust technology and policy options which achieve substantial reductions in electricity demand in China's Shandong Province. This research utilizes a scenario-based approach to identify sensible and feasible energy efficiency and load reduction strategies. The research consists of technical analyses through the development of an hourly load simulation model to study the time and temperature sensitive impacts on electricity demand growth by different demand-side management (DSM) scenarios and a policy analysis to formulate policy priorities based on the socio-economic and environmental realities in China. This bottom-up comprehensive study helps inform decision-making given the technological, consumption and socio-economic conditions in large-scale electricity grid systems of Shandong and China, thus preferred DSM strategies are identified, and sensible policy recommendations are made with respect to Shandong province and China as a whole. This study developed a computer-based modeling tool for peak-load based electric demand analysis and long-term projections.
(cont.) The model simulates disaggregated hourly electric loads by end-user types with temperature-sensitive load simulation capability, which takes into account time use patterns, life-style and behavioral factors, distributed consumption behaviors of electricity users, appliances and equipment utilization patterns, environmental factors, and industrial structural and operational parameters. The simulation and scenario based research methodology provides a comparative basis, and dynamic insights to electricity demand in areas when limited generation and consumption information is available, which is especially appropriate for electricity sector studies in developing countries. The research showed that demand side management strategies could result in significant reduction in the peak loads as well as the total electricity consumption in Shandong.
(cont.) The results of the technical analysis concluded that (1) temperature sensitive load makes up the fastest growing demand within the entire consumption profile; (2) implementation of building energy efficiency strategies demonstrates the largest energy saving potential; (3) implementation of appliances standards, has limited effects on energy saving; (4) load management strategies to induce changes in consumption behaviors also shows great potential, however, they are difficult to estimate; and (5) urbanization policies also have a strong impact on electricity consumption. The recommended DSM policy priorities are based on the energy-saving potentials of the DSM strategies, which are listed in priority order: (1) improvement of building technology, (2) management of new installation first (3) management of temperature sensitive loads, (4) implementation of behavioral and load management strategies, (5) better management of urbanization policies (6) promotion of aggressive industrial motor substitution measures & industrial structural changes, and (6) improvement of appliance efficiency.
(cont.) This research also formulated integrated DSM policy recommendations to the Chinese government that are centered by the development of coordinated DSM policy framework, and that are based upon the current technological, managerial and institutional capacities of Chinese industry and governmental agencies. The details include moving away from the traditional utility centered IRP/DSM framework, developing a robust energy efficiency services industry, setting correct DSM priorities and implementing them, developing and upgrading the domestic energy efficiency product industry, and engaging end-user participation. The thesis recognized the barriers and difficulties in the policy implementation and stressed the importance of continuous adaptation and institutional learning in the implementation process.
by Chia-Chin Cheng.
Ph.D.

In 2011 South Africa's main electricity supplier, Eskom, experienced a peak electricity demand of 89% of their total installed generation capacity. The high utilisation rate makes it difficult to perform essential maintenance on the system. Eskom implements Demand-Side Management (DSM) projects in various industries, in order to reduce the demand and to ensure sustainable electricity supply. The mining sector consumes 14.5% of the total amount of electricity generated by Eskom. Mine compressed air systems can consume as much as 40% of a mine's total electricity requirements. This makes mine compressed air systems an ideal target for DSM. Electricity load seems to be reduced, but many DSM savings are not sustained throughout the project lifetime. An existing project feedback method of a specific Energy Services Company (ESCo) includes the manual collection of data from the mines and manual generation of reports. These reports show energy savings of the DSM projects to help the ESCo and their clients to improve and sustain the performance of the projects. A great amount of man-hours is used which results in large time delays in the feedback-loop. In order to address this, the need for a new automatic feedback reporting system was identified. This study mainly focusses on the development and implementation of a new method to monitor DSM savings on mine compressed air systems. It includes the reliable collection of data from mines, processing and storing of the data in a central database and generating savings reports. This is done automatically on a daily basis. In order to complete the feedback-loop, the reports are verified and emailed to clients and ESCo personnel on a daily basis. The new reporting system is implemented at a number of mines. Four of these project implementations are used as case studies to measure and interpret the effectiveness and value of this system. It saves a significant amount of man-hours and proves to be of great value in the sustainability of DSM project savings. Both Eskom and mining companies benefit from the efficient monitoring of mine compressed air savings.
Thesis (MIng (Computer and Electronic Engineering))--North-West University, Potchefstroom Campus, 2013.

The State of Kuwait has one of the largest per capita consumption in the world, reaching 13061kWh in 2006 (Kuwait MEW, 2007). The power sector in Kuwait is not commercially viable, due to the current under-pricing policy and heavily subsidized tariff. Kuwait needs to take action to meet the increased energy demand. A particular challenge is peak summer demand when extreme heat increases air conditioning loads. Peak demand reached 8900 MW in 2006, with a growth fast at an average rate 5.6% during the last decade. The generated energy reached 47605 GWh in 2006 and is growing fast at an average rate of 6.5%. Electricity demand is characterized by high seasonal variations and low load factor. The main objective of this research is to assess and evaluate the most effective and robust Demand Side Management (DSM) measures that could achieve substantial reductions in peak demand and electricity consumption in the residential sector. The residential sector in Kuwait consumes about 65% of total electricity consumption, and is characterized with inefficient use of energy due to several factors, including very cheap energy price and lack of awareness. To achieve the research objective, an integrated approach was used, including the following steps: • Performing a demand forecast and a building stock forecast across 10 years period (2010 -2019) for the residential sector. The main types of dwellings in Kuwait (villas, apartments and traditional houses) were considered in the forecast. • Conducting detailed energy audits and measurements on selected typical models of residential dwellings. The aim of this process is to examine energy patterns and identify the potential energy efficiency DSM measures. • Performing a simulation process, to evaluate energy performance of the audited dwellings and to estimate the potential DSM savings. Two basic scenarios were considered in simulation, the first represents the base-case with actual existing condition and the second for different DSM options. • Analysis of identified technological DSM options (five) and recommended policy DSM options (two) and ranking them in priority order using the Analytic Hierarchy Process (AHP). • Estimate the potential energy savings and peak demand reductions by the implementation of identified DSM options. A building block approach is used to estimate the aggregate impacts of DSM options and its reflection on the country Load Duration Curve (LDC). The research showed that a DSM portfolio consisting of the seven identified measures, and through a dedicated programme, could have substantial reductions in energy consumption and peak demand. The research showed that the total accumulated energy savings across the forecast period was estimated at approximately 37229 GWh, and the total peak demand reductions during at the end of forecast (2019) reaches 1530 MW representing 8.9% Of the overall peak load. With respect to the type of dwelling, the research also indicated that the total net revenues for the utility were estimated at: $292 million for villas, $79 million for apartments and $47 million for traditional houses. One of the important indicators showed as a result of implementing the identified DSM measures is the positive environmental impact that could be achieved by reducing CO2 total emissions by approximately 26.8 million tonne, which could achieve an annual income of about $38.9 million. Integrated DSM policy recommendations were formulated, including gradual tariff adjustment, and more involvement by the utility, or government, in the creation of sustainable DSM programmes.

Examining methods for controlling the electricity demand in Kuwait was the main objective and motivation of this researchp roject. The extensiveu se of air-conditioning for indoor cooling in office and large commercial buildings in Kuwait and the Gulf States represents a major part of the power and electricity consumption in such countries. The rising electricity generation cost and growing rates of consumption continuously demand the construction new power plants. Devising and enforcing Demand-SideM anagemen(t DSM) in the form of energye fficient operations trategies was the response of this research project to provide a means to rectify this situation using the demand-side management technique known as demand levelling or load shifting. State of the art demand-sidem anagementte chniquesh ave been examined through the developmenot f a model basedp redictive control optimisations trategyf or an integrateda ndm odulara pproachto the provisiono f ice thermals torage. To evaluate the potential of ice-storage assisted air-conditioning systems in flattening the demand curve at peak times during the summer months in Kuwait, a model of a Heating, Ventilation, and Air-conditioning (HVAC) plant was developed in Matlab. The model engaged the use of model based predictive control (MPQ as an optimisation tool for the plant as a whole. The model with MPC was developed to chose and decide on which control strategy to operate the integrated ice-storage HVAC plant. The model succeeded in optimising the operation of the plant and introduced encouraging improvement of the performance of the system as a whole. The concept of the modular ice-storage system was introduced through a control zoning strategy based on zonal orientation. It is believed that such strategy could lead to the modularisation of ice-storage systems. Additionally, the model was examined and tested in relation to load flattening and demonstrated promising enhancement in the shape of the load curve and demonstrated flattened demand curves through the employed strategy. When compared with measured data from existing buildings, the model showed potential for the techniques utilised to improve the load factor for office buildings.

Developing nations face insurmountable challenges to reliably and sustainably provide energy and water to the population. These resources are intricately entwined such that decisions on the use of one affects the other (energy-water nexus). Inadequate and ageing infrastructure, increased population and connectivity, urbanization, improved standards of living and spatially uneven rainfall are some of the reasons causing this insecurity. Expanding and developing new supply infrastructure is not sustainable due to sky high costs and negative environmental impact such as increased greenhouse gas emissions and over extraction of surface water. The exponentially increasing demand, way above the capacity of supply infrastructure in most developing countries, requires urgent mitigation strategies through demand side management (DSM). The DSM strategies seek to increase efficiency of use of available resources and reducing demand from utilities in the short, medium and long term. Renewable energy, rooftop rain water harvesting, pump-storage scheme and grey water recycling are some alternatives being used to curb the insecurity. However, renewable energy and rooftop water harvesting are spasmodic in nature hampering their adoption as the sole supply options for energy and water respectively. The built environment is one of the largest energy and water consuming sectors in the world presenting a huge potential towards conserving and increasing efficiency of these resources. For this reason, coupled with the 1970s energy challenges, the concept of green buildings seeking to, among other factors, reduce the consumption of energy and water sprung up. Conventionally, policy makers, industry players and researchers have made decisions on either resource independently, with little knowledge on the effect it would have on the other. It is therefore imperative that optimal integration of alternative sources and resource efficient technologies are implemented and analysed jointly in order to achieve maximum benefits. This is a step closer to achieving green buildings while also improving energy and water security. A multifaceted approach to save energy and water should integrate appropriate resource efficient technology, alternative source and an advanced and reliable control system to coordinate their operation. In a typical South African urban residential house, water heating is one of the most energy and water intensive end uses while lawn irrigation is the highest water intensive end use occasioned by low rainfall and high evaporation. Therefore, seamless integration of these alternative supply and most resource intensive end uses provides the highest potential towards resource conservation. This thesis introduces the first practical and economical attempt to integrate various alternative energy and water supply options with efficient devices. The multifaceted approach used in this research has proven that optimal control strategy can significantly reduce the cost of these resources, bring in revenue through renewable energy sales, reuse waste water and reduce the demand for grid energy, water and waste water services. This thesis is generally divided into cold and hot water categories; both of which energy-water nexus DSM is carried out. Open-loop optimal and closed-loop model predictive (MPC) control strategies that minimize the objective while meeting present technical and operational constraints are designed. In cold water systems, open-loop optimal and MPC strategies are designed to improve water reliability through a pump storage system. Energy efficiency (EE) of the pump is achieved through optimally shifting the load to off-peak period of the time-of-use (TOU) tariff in South Africa. Thereafter, an open-loop optimal control strategy is developed for rooftop rain water harvesting for lawn irrigation. The controller ensures water is conserved by using the stored rain water and ensuring only the required amount of water is used for irrigation. Further, EE is achieved through load shifting of the pump subject to the TOU tariff. The two control strategies are then developed to operate a grey water recycling system that is useful in meeting non-potable water demand such as toilet flushing and lawn irrigation and EE is achieved through shifting of pump's load. Finally, the two control strategies are designed for an integrated rain and grey water recycling for a residential house, whose life cycle cost (LCC) analysis is carried out. The hot water category is more energy intensive, and therefore, the open-loop optimal control strategy is developed to control a heat pump water heater (HPWH) and an instantaneous shower, both powered by grid-tied renewable energy systems. Solar and wind energy are used due to their abundance in South Africa. Thereafter, the MPC strategy is developed to power same devices with renewable energy systems. In both strategies, energy is saved through the use of renewable energy sources, that also bring in revenue through sale of excess power back to the grid. In addition, water is conserved through heating the cold water in the pipes using the instantaneous shower rather than running it down the drain while waiting for hot water to arrive. LCC analysis is also carried out for this strategy. Each of the two control strategies has its strengths. The open loop optimal control is easier and cheaper to implement but is only suitable in cases where uncertainties and disturbances affecting the system do not alter the demand pattern for water in a major way. Conversely, the closed-loop MPC strategy is more complicated and costly to implement due to additional components like sensors, but comes with great robustness against uncertainties and disturbances. Both strategies are beneficial in ensuring security and reliability of energy and water is achieved. Importantly, technology alone cannot have sustainable DSM impact. Public education and awareness on importance of energy and water savings, improved efficiency and effect on supply infrastructure and greenhouse gas emissions are essential. Awareness is also important in enabling the acceptance of these technological advancements by the society.
Thesis (PhD)--University of Pretoria, 2017.
National Hub for Energy Efficiency and Demand Side Management (EEDSM)
University of Pretoria
Electrical, Electronic and Computer Engineering
PhD
Unrestricted

Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2012.
Electric motors consume over 60% of the world's generated electricity. In South Africa approximately 65% of the energy generated is consumed by electric motors (Niekerk, 2009). About 95% of motors in use in South Africa are Standard-Efficient Motors (SE-motors) that operate at an average efficiency of 84% to 90%, depending on the size of the motor and the load driven by them. High-Efficient motors (HE-motor) run at an efficiency of 2% to 8% higher than that of SE-motors. In recent years, a drive to replace SE-motors with HE-motors has been promoted for the purpose of Demand Side Management (DSM). The rationale of using HE-motors as a tool of DSM is to harness a small difference in operating efficiency per motor, which can result in a huge reduction in electricity consumption, depending on the number of HE-motors that will replace SE-motors. Reducing the demand for electricity is the key driving factor for DSM in South Africa, so as to relieve the already stressed power generation capacity. Other consequential factors of DSM are to reduce the amount of pollutant gases emitted into the atmosphere. To the electricity users DSM will be a great incentive, as reduced consumption of electricity will decrease the amount of money spent on electricity. Much has been written on the ability of HE-motors to reduce electricity consumption, cost of electricity and global pollution. ESKOM has even demonstrated the faith they have in these motors by giving rebates to motor users who are willing to exchange their existing SE-motors with new HE-motors. The rebates are paid by ESKOM through a newly established DSM program. However, it must be mentioned that savings through HE-motors is not a perfect guarantee. HE-motors have inherent design limitations that may inhibit the saving of energy. To achieve higher efficiency, HE-motors are designed to operate on a smaller slip that consequently increases their speed compared to that of SE-motors (Cheek et al., 1995). Higher rotor speed impacts energy saving abilities of HE-motors when they are used to drive fans, pumps and compressors, normally referred to as centrifugal loads. An increase in speed results in a proportional increase in flow. Power consumed by a motor goes up as a cube of the speed, and the flow rate increases linearly with speed. Motor loads in the petrochemical industry are generally centrifugal, and that is why this thesis focuses on refineries.

Global climate change and the electricity supply constraints could possibly be one of the utmost strategic issues facing businesses and consumers of all sizes currently in South Africa. Energy Efficiency is the ability to produce the same output but with less energy. The implementation of Energy Efficiency strategies is pivotal in order to sustain the climatic conditions as well as mitigate the supply constraints the South African utility Eskom is experienced. The aim of this study was to reiterate the importance of energy efficiency strategies and to identify the barriers and challenges companies face towards implementing energy efficiency and energy management strategies. This dissertation identified incentives and rebate schemes available to promote energy efficiency strategies and discussed the policies and strategies the South African Government implemented towards realising the energy efficiency target of 12%.The literature review conclude with discussing best practices indentified by implementing corporate energy efficiency strategies. The level of preparedness and progress in implementing an energy management system and strategies between the different companies were assessed. The target population includes the high intensity user group (HIU), listed and SME companies in the different industry sectors in South Africa. The study concludes that there are still multiple challenges facing companies in implementing sustainable energy efficiency strategies. Although government and multiple stakeholders are initiating incentive and rebate models to promote the implementation of energy efficiency measures, industry still lacks the commitment to change their behaviour toward implementing energy management strategies.
Thesis (MBA)--North-West University, Potchefstroom Campus, 2013.

Demand Side Management (DSM) is one of the most viable and sustainable short term methods to address the shortfall in electricity generation in South Africa. This is because DSM projects can be implemented relatively quickly and inexpensively when compared with alternative generation options. This specifically applies to the mining industry. South African mines presently consume 15% of Eskom-generated electricity. Mine compressed air systems are some of the biggest users, consuming approximately 21% of mine electricity consumption. Electricity savings on compressed air systems are therefore important. With this study, various Energy Efficiency methods on compressed air systems were investigated. These methods include variable speed drives on compressor motors, temperature control of compressor discharge, minimising pressure drops in the air distribution systems, eliminating compressed air leaks, and optimising compressor selection and control. The most efficient strategies were identified, taking into account factors such as financial viability, sustainability, and ease of implementation. The best strategies were found to be the optimised control and selection of compressors, minimising compressed air leaks, and the optimal control of system pressure. These strategies were implemented and tested on large compressed air systems in gold and platinum mines. Savings of between 10% and 35% on the maximum demand of the systems were achieved. In present monetary terms this translates to as much as R108 million savings for the mines per year at the end of 2009 tariffs. If total mine compressed air electricity consumption can reduce by 30%, it will result in nearly a 1% reduction in total Eskom demand. This shows that mine compressed air savings can make a significant contribution to the drive for Energy Efficiency in South Africa.
Thesis (M.Ing. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2010.

[EN] The electric power industry is being shaken by a new idea that is taking shape: smart grids. Three aspects are considered keys to reach smart grids: a) The structure of the network must meet the smart grid concept, i.e. it must be resistant to failures, e.g. causing the automatic separation of any broken element without affecting the operation of the other components; it must be flexible to allow the connection or disconnection of loads and distributed generators, it must maintain efficient operation under various load conditions, and so on. b) The network should open the possibilities of participation of large and small generators as well as users, enabling new business opportunities and active participation, so that "intelligent" generation or consumption may benefit. c) All participants must have easy access to the information needed to choose the best operating strategy in each case. In regard to the first condition (a) there are significant challenges to solve: network automation, optimal design, development of new protection and control equipment, etc. It will be necessary to develop equipment adapted to new problems and new needs that will be generated in these networks. Those items of equipment should be standardised, it will be necessary to define tests to take into account issues that currently are not usually needed, such as the presence of disturbances in voltage, or others. In this sense, marginally though, the research team in which the author works has collaborated with a laboratory for electrical testing, the Flex Power Grid Lab Research Infrastructure DNV KEMA in the Netherlands, in the definition and implementation of some tests, as described in Chapter 3. Smart grids. In the second aspect (b), deep social changes are needed and, above all, regulation changes are crucial. In any case, the first step is to know how the consumption of loads is, how can demand be modified, how can small generation (mainly renewable) and energy storage influence generation, and so on. Having accurate models that provide this information is a key factor for network agents to establish their best strategies. This dissertation discusses many aspects of energy demand and the problem of controlling several resources and agents in the system operation is addressed and Chapter 3. Smart grids shows the management and control software (in which the author has collaborated during the design and development stages) of a small smart grid that exists in LabDER laboratory at UPV, where various resources are integrated according to the needs of demand, energy prices, and so on. In the third condition (c) there are also major challenges to be solved, such as mass information management and the increasing volume of data traffic that it can involve. This dissertation proposes several algorithms to facilitate treatment of the available data to optimise the management of the resources in a smart grid or to make decisions about the participation in demand response programs, as shown in Chapter 8. Energy Management Systems for Smart Customers.
[ES] La industria eléctrica de potencia está siendo sacudida por una idea que va tomando forma: las smart grids. Tres aspectos pueden considerarse claves para llegar a las smart grids: a) La estructura de la red debe responder al concepto de red inteligente, es decir, ser resistente a fallos, por ejemplo provocando la separación automática de cualquier elemento averiado sin afectar al funcionamiento del resto de la red; ser flexible para permitir la conexión o desconexión de cargas y generadores distribuidos, mantener un funcionamiento eficiente bajo diversos estados de carga, etc. b) La red debe abrir las posibilidades de participación de grandes y pequeños generadores así como de los usuarios, permitiendo nuevas posibilidades de negocio y de participación activa, de manera que la generación o el consumo "inteligentes" se vean beneficiados. c) Todos los participantes deben tener acceso fácil a la información necesaria para poder elegir la mejor estrategia de funcionamiento en cada caso. En lo que respecta a la primera condición (a) hay importantes retos por resolver: automatización de la red, diseño óptimo, desarrollo de nuevas protecciones y equipos de control, etc. Será necesario desarrollar equipos adaptados a los nuevos problemas y nuevas necesidades que se generarán en estas redes. Esos equipos deberán ser normalizados, para lo cual será necesario definir ensayos que tengan en cuenta aspectos que actualmente no suelen ser necesarios, como la presencia de perturbaciones en la tensión, u otros. En este sentido, aunque de forma marginal, se ha colaborado con un laboratorio para ensayos eléctricos, la Flex Power Grid Lab Research Infrastructure del DNV KEMA en los Países Bajos, en la definición y realización de algunos ensayos, como se indica en el Capítulo 3. Smart grids. En el aspecto segundo (b), son necesarios profundos cambios sociales y, sobre todo, legislativos. En cualquier caso, el primer paso consiste en saber cómo es el consumo de los receptores, de qué manera puede variarse la demanda, qué influencia puede tener la pequeña generación (renovable principalmente) y el almacenamiento de energía, etc. Disponer de modelos precisos que proporcionen esta información es clave para que los actores de la red puedan establecer sus mejores estrategias. En la tesis se analizan muchos aspectos relacionados con la demanda de energía y se aborda el problema del control de la participación de diversos recursos y diversos agentes en el funcionamiento del sistema y en el Capítulo 3. Smart grids se muestra el software de gestión y control (en cuyo diseño y desarrollo se ha colaborado) de una pequeña smart grid que existe en el laboratorio LabDER de la UPV, donde se integran diversos recursos en función de las necesidades de la demanda, los precios de la energía, etc. En la tercera condición (c) hay, también, grandes retos por resolver, como la gestión masiva de información y el incremento en el volumen de tránsito de datos que puede representar. En la tesis se proponen diferentes algoritmos para facilitar el tratamiento de los datos disponibles a la hora de optimizar la gestión de los recursos de una smart grid o tomar decisiones de cara a participar en programas de respuesta de la demanda, tal como puede verse en el Capítulo 8. Sistemas de Gestión Energética para Smart Customers.
[CAT] La indústria elèctrica de potència està sent sacsada per una idea que va prenent forma: les smart grids. Tres aspectes poden considerar-se claus per a arribar a les smart grids: a) L'estructura de la xarxa ha de respondre al concepte de xarxa intel·ligent, és a dir, ser resistent a fallades, per exemple amb la separació automàtica de qualsevol element avariat sense afectar el funcionament de la resta de la xarxa; ser flexible per a permetre la connexió o desconnexió de càrregues i generadors distribuïts; mantindre un funcionament eficient davall diversos estats de càrrega, etc. b) La xarxa ha d'obrir les possibilitats de participació de grans i xicotets generadors així com dels usuaris. Així, ha de permetre noves possibilitats de negoci i de participació activa, de manera que la generació o el consum "intel·ligents" es vegen beneficiats. c) Tots els participants han de tindre accés fàcil a la informació necessària per a poder triar la millor estratègia de funcionament en cada cas. Pel que fa a la primera condició (a) hi ha importants reptes per resoldre: automatització de la xarxa, disseny òptim, desenrotllament de noves proteccions i equips de control, etc. Serà necessari desenrotllar equips adaptats als nous problemes i noves necessitats que es generaran en aquestes xarxes. Aqueixos equips hauran de ser normalitzats, per a la qual cosa serà necessari definir assajos que tinguen en compte aspectes que actualment no solen ser necessaris, com la presència de pertorbacions en la tensió, o altres. En aquest sentit, encara que de forma marginal, s'ha col·laborat amb un laboratori per a assajos elèctrics, la Flex Power Grid Lab Research Infrastructure del DNV KEMA en els Països Baixos, en la definició i realització d'alguns assajos, com s'indica en el Capítol 3. Smart grids. En l'aspecte segon (b), són necessaris profunds canvis socials i, sobretot, legislatius. En qualsevol cas, el primer pas consisteix a saber com és el consum dels receptors, de quina manera pot variar-se la demanda, quina influència pot tindre la xicoteta generació (renovable principalment) i l'emmagatzemament d'energia, etc. Disposar de models precisos que proporcionen aquesta informació és clau perquè els actors de la xarxa puguen establir les seues millors estratègies. En la tesi s'analitzen molts aspectes relacionats amb la demanda d'energia i s'aborda el problema del control de la participació de diversos recursos i diversos agents en el funcionament del sistema i en el Capítol 3. Smart grids es mostra el programari de gestió i control (en el disseny i desenrotllament del qual s'ha col·laborat) d'una xicoteta smart grid que existeix en el laboratori LabDER de la UPV, on s'integren diversos recursos en funció de les necessitats de la demanda, els preus de l'energia, etc. En la tercera condició (c) hi ha, també, grans reptes per resoldre, com ara la gestió massiva d'informació i l'increment en el volum de trànsit de dades que pot representar. En la tesi es proposen diferents algoritmes per a facilitar el tractament de les dades disponibles a l'hora d'optimitzar la gestió dels recursos d'una smart grid o prendre decisions de cara a participar en programes de resposta de la demanda, tal com pot veure's en el Capítol 8. Sistemes de Gestió Energètica per a Smart Customers.
Roldán Blay, C. (2016). Avances en Verificación y Medida de la Respuesta de la Demanda y Aplicación a su integración en Smart Grids [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/61302
TESIS

Smart grid has been under continuous development since 2008. It requires the re-construction of traditional power systems. As an important component of a smart grid, load management has been diffusely known as a bright solution to enhance the demand side energy efficiency and optimize energy consumption. In this project, load management techniques on the demand side are studied at two levels in a smart grid: the smart home level and the load aggregator level. At the smart home level, this project studies the development of home energy management systems (HEMSs), which optimally schedule home energy resources to minimize home electricity costs. The potential of plug-in electric vehicles (EVs) is harnessed by the developed HEMS to supply power to the home and absorb surplus residential renewable power output. At the load aggregator level, this project studies the feasibility of aggregating thermostatically controlled loads (TCLs) in multiple buildings to bid in the wholesale power market. An optimal scheduling model for TCLs is proposed in this project to minimize imbalance costs of the load aggregators in the power market. To address the uncertainties in imbalance penalty prices, this project introduces the rolling horizon optimization (RHO) technique to continuously update TCL ON/OFF plans with the realization of imbalance prices. This research also includes techniques for solving load management optimization models. A new heuristic optimization method, Natural Aggregation Algorithm (NAA), is used to solve the aforementioned HEMSs and TCLs scheduling models. The encoding scheme and constraint handling strategies are studied, and the efficiency of NAA in solving the models is also investigated.

This work presents the results from the analysis of the behavior of demand and energy consumption in the Campus of the Universidade Federal de Santa Maria to contribute to the adoption of strategic plans for demand side management. Presented are the basic concepts of electrical quantities, the definition of demand, as well as its available control and management techniques. The advantages of the demand side management option are highlighted. Two sets of load curves were collected : the load shapes of the campus as a whole, obtained from two years of demand records by the local electricity provider's energy meter; and the individual load curves of various buildings throughout the campus, obtained from measurements made with a multi-quantities electrical meter. Presented are the methods of obtaining their curves and highlighted the influence of temperature, business hours, school calendar and days of the week on them. Finally, a comparison is made between the whole university curve, with the individual load shapes. The set of information obtained forms the basics for demand side management on the campus, in near future. The results indicated that public educations buildings have peculiarities that should be taken into account when adopting measures to reduce consumption and load management. Such measures must take into account the presence of loads of different nature (purely academic through industrial, commercial and residential) and with different hours of use in comparison to similar off-campus loads.
Neste trabalho são apresentados os resultados obtidos a partir do estudo do comportamento da demanda e do consumo de energia elétrica no Campus da Universidade Federal de Santa Maria de forma a contribuir para a adoção de planos estratégicos de gerenciamento pelo lado da demanda. São apresentados os conceitos básicos das grandezas elétricas, a definição de demanda, bem como seu controle e técnicas de gerenciamento possíveis. As vantagens da opção do gerenciamento pelo lado da demanda são evidenciadas. Dois conjuntos de curvas de carga foram levantados: as curvas de carga do campus como um todo, obtidas a partir de dois anos de registros junto ao medidor de energia da concessionária local; as curvas de carga individuais de diversos prédios espalhados pelo campus, obtidas a partir de medições realizadas com um multimedidor de grandezas elétricas. São apresentados os métodos de obtenção das respectivas curvas e evidenciadas a influência da temperatura, horário de expediente, calendário letivo e dia da semana sobre as mesmas. Por fim, é feita a comparação entre a curva de carga geral da universidade, com as curvas de carga individuais. O conjunto de informações obtidas forma a base para um futuro gerenciamento pelo lado da demanda no campus. Os resultados obtidos permitiram concluir que os prédios públicos de ensino apresentam peculiaridades que devem ser levadas em conta quando se adotam medidas de redução do consumo e gerenciamento de carga. Tais medidas devem levar em conta a presença de cargas de diferentes naturezas (puramente acadêmicas, passando por industriais, comerciais e residenciais) e com horários de uso diferenciados em comparação a cargas idênticas fora do campus.

Large cooling systems consume up to 25% of the total electricity used on deep level mines. These systems are integrated with the water reticulation system to provide chilled service water and cool ventilation air. Improving the energy efficiency of these large cooling systems is an important electrical demand-side management initiative. However, it is critical that the service delivery and system performance be maintained so as to not adversely affect productivity. A novel demand-side management strategy, based on variable water flow, was developed to improve the energy efficiency of large cooling systems like those found on deep mines. The strategy focuses on matching the cooling system supply to the demand through the use of modern energy efficient equipment, such as variable speed drives. The strategy involves the modulation of evaporator, condenser, bulk air cooler and pre-cooling water according to partial load conditions. A unique central energy management system was developed to integrate the proposed strategies on large cooling systems. The system features a generic platform and hierarchical network architecture. Real-time energy management is achieved through monitoring, optimally controlling and reporting on the developed strategy. The system is robust and versatile and can be applied to various large cooling systems. The feasibility of the strategy and energy management system was first investigated through the use of an adapted and verified simulation model and a techno-economic analysis. The strategy was then implemented on four large mine cooling systems and its in situ performance was assessed as experimental validation. The results of the Kusasalethu surface cooling system are discussed in detail as a primary case study while the results of the Kopanang, South Deep South Shaft and South Deep Twin Shaft cooling systems are summarised as secondary case studies. The potential to extend the variable water flow strategy to other industrial cooling systems is assessed through an investigation on the cooling system of the Saldanha Steel plant. Results indicate that, over a period of three months, average electrical load savings of 606-2 609 kW (29.3-35.4%) are realised on the four systems with payback periods of 5-17 months. The average electrical load saving between the sites is 33.3% at an average payback period of 10 months. The service delivery and performance of the cooling system and its critical subsystems are not adversely affected. The potential to extend the method to other large cooling systems is also shown. The developed variable water flow strategy is shown to improve the energy efficiency of large cooling systems, making a valuable contribution towards a more sustainable future. This thesis is presented as a detailed discussion of the entire research process. The key results have also been summarised in a series of five research articles attached as independent annexures. Three articles have been published in international scientific journals, one has been presented at and published in the proceedings of an international conference and one is still under review.
Thesis (PhD (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2013

The demand for electricity in South Africa has grown faster than the increase in generation capacity. However, it is expensive and time consuming to commission new power stations. Another approach is to reduce electricity demand through the implementation of energy efficiency projects. This alternative is usually less expensive. Compressed air on South African mines is a large electricity consumer with a reputation of wastage. This allows significant potential for electrical and financial savings. A typical mine compressed air system consists of multiple compressors at various locations, surface connection networks, underground distribution systems, thousands of users and leaks. The size, complexity and age of these systems provide a major challenge for electricity saving efforts. Simulating such an intricate system is difficult as it is nearly impossible to accurately gather all the required system parameters. Some initiatives focused on subsections of mine compressed air systems. This is not the best approach as changes to one subsection may adversely affect other systems. A new approach to simplify mine compressed air systems was developed to identify saving opportunities and to assess the true impact of saving efforts. This new approach enables easier system analysis than complex simulation models. Techniques to gather critical system information are also provided. A new implementation procedure was also developed to integrate different energy saving strategies for maximum savings. An electrical power saving of 109 MW was achieved through the implementation of the integrated approach on twenty-two mine compressed air systems. The savings is equivalent to a reduction of 0.96 TWh per annum that relates to a saving of 0.4% of South Africa’s total electricity consumption. Average compressor power consumption was reduced by 30%. The power consumption reduction relates to an estimated annual electricity cost saving of R315 million. A saving of 0.96 TWh per annum is equivalent to a carbon dioxide emission reduction of 0.98 million tonne. The implementation of the integrated approach could be applied to other industrial compressed air systems. A reduction in electricity consumption of 30% on all industrial compressed air systems has the potential to reduce global electricity demand by 267 TWh per annum. That is more than the total amount of electricity consumed in South Africa.
Thesis (PhD (Electrical Engineering))--North-West University, Potchefstroom Campus, 2013

Thesis advisor: Scott Fulford
Can smart metering program and time-of-use (TOU) prices help reduce energy consumption in New York City? Being able to track electricity consumption levels and to modify consumer usage patterns are important for policy makers to efficiently manage the energy markets. Unfortunately, no reliable and up-to-date data have been brought to bear on this question. I study the effects of time-of-use (TOU) prices and smart metering for the residents of Shanghai and I investigate further what can policy makers do in order to adapt and transfer this successful DSM experience from Shanghai to the residential sector in New York City. The primary objective of my study is to characterize the realistic short-term and long-term potential for the smart metering program in New York City given my empirical findings that the smart metering program has had brought great benefits to the residents of Shanghai. People respond to incentives; if electricity is charged at different prices throughout a day, consumers are likely to shift their usage to when it is cheaper. My findings suggest that policy makers should think harder about designing a pricing scheme that can optimize the social plus
Thesis (BA) — Boston College, 2011
Submitted to: Boston College. College of Arts and Sciences
Discipline: College Honors Program
Discipline: Economics Honors Program
Discipline: Economics

A rapid growth in the national electricity demand is placing an ever-increasing demand on the national electricity supply utility, Eskom. Projections show that the load demand in South Africa may exceed the installed capacity by as early as 2007. This is mainly due to the increase in demand in the residential sector as a result of the electrification of rural and previously disadvantaged communities. However, the industrial and commercial sectors also have a role in this increase. In an attempt to reduce the demand for electricity Eskom has adopted its Demand Side Management (DSM) initiative. This initiative is aimed at lowering the electricity demand in peak times through energy efficiency (EE) or load shift, out of peak demand times. Eskom is implementing the DSM strategy by financing Energy Service Companies (ESCOs) to reduce the demand load of major electricity end-users during peak times. Buildings consume a large percentage of the total energy supply in the world. Most of the energy consumed in buildings is used by the heating, ventilation and air-conditioning (HVAC) systems, as well as lighting. However, a large potential for energy savings exists in buildings. Studies have shown that up to 70% of the electricity consumption of a building can be saved through retrofit studies. However, to capitalise on these opportunities, the ESCOs require tools and procedures that would enable them to accomplish energy savings studies quickly and efficiently. It should be a holistic approach to the typical ESCO building audit. A study of current available software programs showed the lack of holistic tools aimed specifically at retrofit audits, and therefore also the need for such a program. The building simulation program most suited to the retrofit study was chosen and it was used in a retrofit audit. By emulating a retrofit audit with this software, its performance in the field, both positive and negative, could be established. With the experience gained from the retrofit study, as well as input from ESCOs in the industry, a need for such a retrofit tool was established. The simulation program that was tested in the retrofit study is the tool Quickcontrol, as well as the newer version of the program, entitled QEC. The case study showed that even though these packages are well suited to ESCO work, they have certain drawbacks in view of the holistic project approach. The ESCOs require a simple, fast, and integrated procedure for energy audits. This procedure should be embodied in a software program. This study proposes a new integrated procedure for energy audits and the analyses of buildings, in the form of a software tool. This new tool is geared towards the ESCO building audit, in both South A6ica and internationally. It is designed to enable a diplomate engineer to accomplish a building energy and retrofit analysis in two weeks, leading the user through all the main project steps, from data acquisition to writing of the final project report. This is a significant improvement, since it normally takes 50 man-days for an experienced and trained engineering team to complete a full building audit. This tool was used in a case study to test its validity and accuracy. It was found that certain situations would arise in which the criteria that were set for the program would not be adequate. The results from the case study were favourable and satisfied the criteria that were set for the procedure.
Thesis (Ph.D. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2004.

The high penetration of renewable energy sources (RES), in particular, the rooftop photovoltaic (PV) systems in power systems, causes rapid ramps in power generation to supply load during peak-load periods. Residential and commercial buildings have considerable potential for providing load exibility by exploiting energy-e_cient devices like ground source heat pump (GSHP). The proper integration of PV systems with the GSHP could reduce power demand from demand-side. This research provides a practical attempt to integrate PV systems and GSHPs e_ectively into buildings and the grid. The multi-directional approach in this work requires an optimal control strategy to reduce energy cost and provide an opportunity for power trade-o_ or feed-in in the electricity market. In this study, some optimal control models are developed to overcome both the operational and technical constraints of demand-side management (DSM) and for optimum integration of RES. This research focuses on the development of an optimal real-time thermal energy management system for smart homes to respond to DR for peak-load shifting. The intention is to manage the operation of a GSHP to produce the desired amount of thermal energy by controlling the volume and temperature of the stored water in the thermal energy storage (TES) while optimising the operation of the heat distributors to control indoor temperature. This thesis proposes a new framework for optimal sizing design and real-time operation of energy storage systems in a residential building equipped with a PV system, heat pump (HP), and thermal and electrical energy storage systems. The results of this research demonstrate to rooftop PV system owners that investment in combined TSS and battery can be more profitable as this system can minimise life cycle costs. This thesis also presents an analysis of the potential impact of residential HP systems into reserve capacity market. This research presents a business aggregate model for controlling residential HPs (RHPs) of a group of houses that energy aggregators can utilise to earn capacity credits. A control strategy is proposed based on a dynamic aggregate RHPs coupled with TES model and predicting trading intervals capacity requirements through forecasting demand and non-scheduled generation. RHPs coupled with TES are optimised to provide DSM reserve capacity. A rebound effect reduction method is proposed that reduces the peak rebound RHPs power.

O objetivo do trabalho é analisar os protocolos mais conhecidos de medição e verificação de programas de eficiência energética sob da ótica a aplicação do recurso privado em projetos de eficiência energética. A simples comparação de faturas de energia e a utilização não rigorosa de indicadores para determinação da energia economizada praticamente deixa de ser uma opção com a disponibilização de padrões compreensivos de M&V. Para tal são analisados estudos de caso de projetos de eficiência energética nos segmentos comercial e industrial e estes indicam um distanciamento entre as ferramentas modernas de M&V e a realidade, de modo que há dúvidas sobre garantia da sustentabilidade das ações ao longo do tempo. Dessa análise dos protocolos e estudos de caso foram identificadas demandas que são partes de uma metodologia proposta em 9 etapas focadas na sustentabilidade da energia economizada. A aplicação dessa metodologia é complementar à aplicação dos protocolos, tal que o engenheiro de eficiência energética possa pensar em todo processo de gestão e não apenas na implementação das MCEs. Esse trabalho conclui que a simples aderência aos protocolos de M&V é insuficiente para garantir a sustentabilidade das ações de conservação de energia a longo prazo.
The purpose of this work is to analyze the most well known Measurement and Verification protocols to energy efficiency programs under private capital owner perspective. The simple comparison between energy bills and the non-rigorous use of energy efficiency indicators in the energy savings calculation are not an option anymore with the introduction of comprehensive M&V protocols. With this aim, energy efficiency case studies are analyzed in the commercial and industrial sectors and indicated theres a gap between the modern M&V tools and the reality. Doubts around the sustainability of energy savings in the long term raised. Based on literature review, analysis of protocols and case studies, improvement opportunities were identified and are part of a 9 steps methodology focused on the sustainability of energy savings proposed in this work. This methodology works in cooperation with current M&V protocols. The EE engineer shall then be able to think in the overall management process and not only in the Energy Conservation Measure. This work concluded that the M&V tools adherence solely is insufficient to guarantee the sustainability of energy savings in the long term.

From a big picture perspective, investing in energy efficiency in the existing stock of residential buildings in the United States brings unquestioned economic, employment and environmental benefits. The aggregation of energy and dollar savings from millions of small improvements in efficiency adds up to enormous regional and national savings. By employing cost-effective investments in building efficiency, we could reduce the cumulative energy use of Americaâ s housing stock by twenty-eight percent, save Americans $41 billion annually, abate 360 megatons of CO-2 (Choi Granade, et.al., 2009), and meet fifty percent or more of the expected electric load growth by 2025 (EPA, 2008). In Virginia alone investing in the efficiency of our existing stock of buildings could save the commonwealthâ s residents $2.2 billion annually by 2025 (ACEEE, 2008). But from the perspective of the individual property owner the potential benefits of investing in energy efficiency, although just as real, are either less obvious or have impediments to their attainment. Understanding and overcoming these micro-impediments to energy investing is essential to realizing the macro-benefits of energy efficiency. Consequently, any successful local energy program must tailor its efforts to address the barriers to investing in efficiency at the level of the individual consumer. This thesis, through an analysis of existing and emerging residential energy programs, along with a review of the behavioral and economic literature on the subject, aims to point out the micro-impediments to achieving macro-reductions in energy use. Becoming familiar with these obstructions on the level of the individual consumer is the first necessary step in producing model guidelines for a successful whole house local energy efficiency program. Although the basic tenets of these guidelines could be used as the basis for any locally organized energy program in the U.S., they are specifically tailored in this thesis for the Commonwealth of Virginia.
Master of Urban and Regional Planning

L'architecture physique des réseaux électriques et les structures organisationnelles des industries électriques survenues à la suite des réformes ont principalement été conçues en fonction des caractéristiques relatives aux infrastructures de transport et aux parcs de production. Or, les nouveaux enjeux de transition énergétique, associés aux progrès réalisés dans les équipements de communication et d'automatisation, plaident pour une plus grande participation des activités décentralisées de production et des consommateurs finals. Nous constatons que les systèmes électriques sont à l'aube d'évolutions majeures qui partagent une double caractéristique. La première et que ces évolutions nécessiteront des apports en capitaux considérables pour adapter et moderniser les réseaux de distribution. La seconde est que l'activation de l'aval de la chaîne électrique libère des gains d'efficacité économique actuellement inexploités, mais est également porteuse de contraintes nouvelles.Partant de ce constat, l'objectif de cette thèse est double. Il s'agit dans un premier temps de proposer une analyse théorique des instruments de régulation qui encadrent et orientent les dépenses des opérateurs réseau. Nous cherchons en nous appuyant sur la littérature à caractériser les outils de régulation les mieux adaptés à l'investissement en smart technologies. Puisqu'il est nécessaire de confronter l'analyse théorique aux faits, nous entreprenons de recenser les gains clés d'efficacité économique escomptés de la généralisation des smart grids. Nous illustrons chacun de ces gains par une étude empirique qui nous permet de comparer les résultats issus de notre analyse théorique aux schémas de régulation existants et de formuler un certain nombre de recommandations.Le second objectif de la thèse se concentre sur les impacts de la diffusion de programmes de la gestion de la demande. Le raisonnement adopté s'articule autour de deux constats. D'importants bénéfices sont attendus des réductions substantielles des pointes de demande, réductions qui se traduisent par de moindres opportunités de profit pour les producteurs. Il s'agira de réaliser une estimation des gains et pertes que l'on peut attendre de la gestion de la demande. Pour cela, nous développons et utilisons un modèle d'optimisation dans lequel nous intégrons plusieurs pays interconnectés dotés de parcs de production différenciés.La thèse montre que les cadres de régulation dominants actuellement sont limités dans leur portée incitative pour favoriser un investissement efficace dans la technologie, ce qui est susceptible de retarder son introduction. La quantification des impacts de la gestion de la demande montre quant à elle que des efficacités significatives peuvent être activées via la généralisation de ces mesures. Toutefois, elles posent des problèmes nouveaux dans la rémunération de l'existant, l'adéquation future des capacités, et souligne l'antagonisme potentiel entre perte de revenus pour les unités de pointe les plus réactives et développement des énergies bas carbone.De toute évidence, les interrogations soulevées par le développement des smart grids nécessitent que soit mené un débat politique éclairé puisque l'industrie électrique est indispensable à nos sociétés. Parmi le nombre considérable d'éléments à aborder, arriveront en bonne place les questions relatives au financement des projets d'investissement et à l'inclusion des nouvelles sources de flexibilité induites par l'adoption de la technologie dans les marchés électriques libéralisés
The physical architecture of electricity grids and the organizational structure of power systems implemented after the reforms have traditionally be achieved according to the characteristics of the transmission infrastructures and power mixes. However, the new challenges related to energy transition favor a greater participation of decentralized generation and final consumers to system exploitation and competitive markets. This latter participation is made possible thanks to recent innovations in the fields of communication and remote control technologies.Significant evolutions are expected in power industries that share common characteristics. First, these evolutions suppose massive capital investments to modernize and adapt current power distribution grids. Second, it is expected the activation of distribution grids and final consumers will unleash substantial unexploited economic efficiency gains as well as impose new constraints.Taking these simple facts as a starting point, the objective of the thesis is twofold. In the first place, we provide a theoretical analysis of the regulatory instruments that monitor the system operators' expenses. Relying on the literature, we aim at characterizing what regulatory tools and incitation are suitable for investing in smart grids technologies. Since it is necessary to compare theoretical formulation to facts, we use an empirical approach that allows us to designate key benefits pursued by the development of smart grids and to compare our theoretical results with practical regulatory applications. Our findings eventually allow us to formulate recommendations.In the second place, the thesis focuses on the impacts of demand-side management during peak periods. We structure our approach around two general observations. Large benefits should be generated in lowering substantially peak demand. However, such situation also creates losses of profit for generators. We provide an estimation of efficiency gains and revenue losses induced by peak shedding. To this end, we develop and use a linear optimization model and expand our analysis to interconnected countries endowed with differentiated generation means.The thesis shows dominant regulatory frameworks are unsuited to provide the necessary sets of incentive to efficiently develop smart technologies. This can cause delays in their integration to power grids. The quantitative evaluation of the impacts generated by demand-side management shows significant efficiency gains are achievable through final consumers' flexibility. However, such measures create new discrepancies regarding installed capacities profitability, future capacity adequacy, and highlight potential antagonism between missing money for flexible peak capacities and the development of low carbon energies.It is clear the issues raised by the development of smart grids call for informed public debate as power industries are essential to our societies. Among the considerable amount of elements to discuss, issues relative to financing the investment projects and the inclusion of the new sources of flexibility induced by the technology in competitive markets will be of priority

This thesis offers a decision support framework to establish the economic feasibility associated with considering the installation of a greywater system. Because of the potential dangers and lack of widespread knowledge of greywater systems, the study begins by providing an explanation of current greywater technology to include the history of the technology, an explanation of greywater as opposed to reclaimed water, the potential risks of greywater use, and the necessary components of a greywater system. This decision support framework can be used with any scale of greywater system to be installed within any scale of facility. The example of an typical Atlanta, Georgia, USA multifamily rental development is used within the study to explain the framework by showing a working model. The need for water conservation in Georgia is shown and how greywater use dovetails with the need to lower overall usage. The legality of greywater use in Georgia along with the specific legal uses is also shown. The findings are then made State of Georgia and use specific to a multifamily development. The decision support framework provided is a viable tool. The sample framework in chapter 5 shows that the implementation of a greywater unit in the sampled facility would save 5,060,739.6 gallons of potable water per year with a 10.49 year payback cycle.

Thesis (MScEng)--Stellenbosch University, 2012.
ENGLISH ABSTRACT: In the last century the earth has experienced an increase in the global mean temperature, with the main contributing factor being the increase in greenhouse gasses. Evidence indicates that the burning of fossil fuels, critical in the supply of energy, contributed towards three quarters of the carbon dioxide (CO2) increase. In 2008 South Africa reached electricity capacity constraints. A subsequent economic downturn experienced in the country, brought about by the worldwide economic recession, has relieved some of the strain on the electricity supply system. However, consumption levels are returning to those experienced during 2008 and no new base load power stations have been added. Short-term capacity constraints can be managed by shifting the peak demand, but the electricity shortage can only be avoided by adding additional capacity or reducing the overall electricity consumption. Supply-side solutions are both overdue and too expensive. The only solutions that can provide lasting results are demand-side solutions. During the past few years the Energy Efficiency and Demand-side Management (EEDSM) programme implemented by South Africa’s electricity supply utility, Eskom, has gained prominence. This programme relies heavily on calculating the savings incurred through any demand-side intervention. Energy audits enable the calculation of various consumption scenarios and can provide valuable insight into load operation and user behaviour. Energy audits involve a two-part procedure consisting of load surveying and an analysis. This thesis describes the development of both these procedures, combined into a single application. The application has been tested and provides an accurate and effective tool for simulating consumption and quantifying savings for various load adjustments. The results gained from the auditing application surpassed the expectations and provides the user with a sufficient base-line consumption estimate. The results do not reflect day-to-day variations, but the simulations are sufficient to quantify savings and determine whether demand-side interventions are financially viable. The application also presents a benchmark for the type of applications required to successfully implement an EEDSM programme.
AFRIKAANSE OPSOMMING: In die afgelope eeu het die aarde se gemiddelde temperatuur toegeneem, met die toename in kweekhuisgasse as die grootste bydraende faktor. Dit wil ook voorkom asof die verbranding van fossielbrandstowwe, wat noodsaaklik is vir die verskaffing van energie, verantwoordelik is vir driekwart van die toename in koolstofdioksied (CO2). Gedurende 2008 het Suid-Afrika elektrisiteitsbeperkings bereik. Die daaropvolgende ekonomiese afswaai wat in die land ervaar is weensdie wêreldwye ekonomiese resessie, het van die druk op die elekriese netwerk verlig. Verbruikersvlakke is egter besig om terug te keer na waar dit in 2008 was, maar geen nuwe basislas-kragstasies is gebou nie. Op die kort termyn kan die kapasiteitsbeperkings bestuur word deur die aanvraag te verskuif, maar die elektrisiteitstekort kan op die lang duur slegs vermy word deur bykomende kapasiteit by te voeg of die totale aanvraag te verminder. Toevoerkant-oplossings is beide agterstallig en te duur. Die enigste oplossings wat blywende resultate kan lewer, is dus aan die verbruikerkant. In die afgelope paar jaar het die effektiewe bestuur van energieverbruik baie aansien geniet. Die nasionale energievoorsiener, Eskom, het ook 'n program geloods om te help met die implimentering van energiebesparingmaatreëls. Die implementering van energie-oudits om met die kwantifisering van besparings te help, is van integrale belang vir die sukses van die program. Energie-oudits stel die eindverbruiker in staat om verskeie verbruiksmoontlikhede te beproef en sodoende waardevolle inligitng te verkry rakende die verbruikspatrone van die fasiliteit. Energie-oudits behels 'n tweeledige proses, bestaande uit 'n lasopname en 'n verbruiksanalise. Hierdie proefskrif beskryf die ontwikkeling van 'n stelsel wat beide die prosesse kombineer in 'n enkele applikasie. Die applikasie is getoets en bied 'n akkurate en doeltreffende instrument om verbruik te simuleer en besparings te kwantifiseer vir verskeie verbruiksmoontlikhede. v Die resultate van die oudit het die aanvanklike verwagtinge oortref en voorsien verbruikers van 'n goeie skatting van die basisverbruik van 'n fasiliteit. Die resultate weerspieël nie dagtot- dag variasies nie, maar die simulasies is voldoende om besparings te kwantifiseer en help om die finansiële lewensvatbaarheid van verbruikerskant-intervensies te bepaal. Die program bied ook 'n verwysingspunt vir applikasies wat besparingstudies wil implementeer.

The main objective of the thesis is to seek insights into the theory, and provide empirical evidence of rebound effects. Rebound effects reduce the environmental benefits of environmental policies and household behaviour changes. In particular, win-win demand side measures, in the form of energy efficiency and household consumption pattern changes, are seen as ways for households and businesses to save money and the environment. However, these savings have environmental impacts when spent, which are known as rebound effects. This is an area that has been widely neglected by policy makers. This work extends the rebound effect literature in three important ways, (1) it incorporates the potential for variation of rebound effects with household income level, (2) it enables the isolation of direct and indirect effects for cases of energy efficient technology adoption, and examines the relationship between these two component effects, and (3) it expands the scope of rebound effect analysis to include government taxes and subsidies. MACROBUTTON HTMLDirect Using a case study approach it is found that the rebound effect from household consumption pattern changes targeted at electricity is between 5 and 10%. For consumption pattern changes with reduced vehicle fuel use, the rebound effect is in the order of 20 to 30%. Higher income households in general are found to have a lower total rebound effect; however the indirect effect becomes relatively more significant at higher household income levels. In the win-lose case of domestic photovoltaic electricity generation, it is demonstrated that negative rebound effects can occur, which can potentially amplify the environmental benefits of this action. The rebound effect from a carbon tax, which occurs due to the re-spending of raised revenues, was found to be in the range of 11-32%. Taxes and transfers between households of different income levels also have environmental implications. For example, a more progressive tax structure, with increased low income welfare payments is likely to increase greenhouse gas emissions. Subsidies aimed at encouraging environmentally friendly consumption habits are also subject to rebound effects, as they constitute a substitution of government expenditure for household expenditure. For policy makers, these findings point to the need to incorporate rebound effects in the environmental policy evaluation process.’

The main objective of the thesis is to seek insights into the theory, and provide empirical evidence of rebound effects. Rebound effects reduce the environmental benefits of environmental policies and household behaviour changes. In particular, win-win demand side measures, in the form of energy efficiency and household consumption pattern changes, are seen as ways for households and businesses to save money and the environment. However, these savings have environmental impacts when spent, which are known as rebound effects. This is an area that has been widely neglected by policy makers. This work extends the rebound effect literature in three important ways, (1) it incorporates the potential for variation of rebound effects with household income level, (2) it enables the isolation of direct and indirect effects for cases of energy efficient technology adoption, and examines the relationship between these two component effects, and (3) it expands the scope of rebound effect analysis to include government taxes and subsidies. MACROBUTTON HTMLDirect Using a case study approach it is found that the rebound effect from household consumption pattern changes targeted at electricity is between 5 and 10%. For consumption pattern changes with reduced vehicle fuel use, the rebound effect is in the order of 20 to 30%. Higher income households in general are found to have a lower total rebound effect; however the indirect effect becomes relatively more significant at higher household income levels. In the win-lose case of domestic photovoltaic electricity generation, it is demonstrated that negative rebound effects can occur, which can potentially amplify the environmental benefits of this action. The rebound effect from a carbon tax, which occurs due to the re-spending of raised revenues, was found to be in the range of 11-32%. Taxes and transfers between households of different income levels also have environmental implications. For example, a more progressive tax structure, with increased low income welfare payments is likely to increase greenhouse gas emissions. Subsidies aimed at encouraging environmentally friendly consumption habits are also subject to rebound effects, as they constitute a substitution of government expenditure for household expenditure. For policy makers, these findings point to the need to incorporate rebound effects in the environmental policy evaluation process.’

Thesis (MBA (Business Management))--University of Stellenbosch, 2008.
AFRIKAANSE OPSOMMING: Die Suid-Afrikaanse Heropbouings Program (HOP) asook die Groei Indiensnemings- en Herverdelingsprogram(GEAR) het ‘n geweldige hoë standaard gestel vir die verskaffing van basiese dienste soos behuising en elektrifisëring vir almal. Die meer effektiewe gebruik van elektriese energie het die sosiale en politieke potensiaal om by te dra tot die sukses van GEAR ten opsigte van die geteikende lae inkomste gemeenskappe waar daar nie tans voldoende elektriese energie beskikbaar is nie. Hierdie studie dek ook die inisiatiewe ten opsigte van effektiewe elektriese energie waaroor die Suid-Afrikaanse regering in vennootskap met Eskom tans navorsing doen om te bepaal of daar enige ekonomiese waarde is, en/of die lae inkomste gemeenskappe deur die sogenoemde inisiatiewe bevoordeel kan word. Die studie sluit ook navorsing in om die bewustheid van die lae inkomste gemeenskappe ten opsigte van effektiewe elektriese energie te bepaal. Die studie kyk verder na verskeie ander voltooide studies ten opsigte van effektiewe energie in lae inkomste gemeenskappe. Alhoewel verskeie ander effektiewe energie programme wel hoë ekonomiese en omgewings voordele uit 'n sosiale oogpunt inhou, is dieselfde programme glad nie aantreklik vir die verbruikers nie. Vir hierdie feit is die regering se bemiddeling wel belangrik. Die uitslag van die studie ondersoek ook die verskillende beleidsopsies (nie in diepte nie) om die struikelblokke van effektiewe energie te oorkom, asook moontlike oplossings vir die regering om die verskille tussen wat goed is vir die gemeenskap, en wat goed is vir die elektriese industrie te oorbrug. Die studie toets ook die bewustheid van effektiewe energie onder die lae inkomste gemeenskappe en hul huidige deelname aan effektiewe energie programme.
ENGLISH ABSTRACT: South Africa’s Reconstruction and Development Programme (RDP) as well as Growth Employment and Redistribution (GEAR) set ambitious goals for providing basic services to all, including housing and electrification. More efficient use of electrical energy has the potential to socially and politically support the goals of GEAR, particularly when it is targeted at low-income communities lacking adequate energy services. This study looks at electrical energy efficiency initiatives that the South African government has under taken on its own as well as in partnership with Eskom and to check if there is any economic value that the poor communities may benefit from these initiatives. The study will also check the awareness of poor communities of electrical energy efficiency. Various studies in the subject of energy efficiency in relation to the poor communities that have been done in the past will also be looked at in this study. While many energy efficiency programmes may have significant economic and environmental benefits from a social perspective, they may not be as attractive to utilities and consumers. That is why government intervention is important. As a result this study also examine (not in great depth) the policy options for overcoming the significant barriers to energy efficiency, and ways government can bridge the gap between what is good for society and what is good for the electricity industry. This study extends further on checking the awareness of energy efficiency by the poor communities and their current participation in the energy efficiency programmes.

In order to meet greenhouse gas emissions targets, the Great Britain (GB) future electricity supply will include a higher fraction of non-dispatchable generation, increasing opportunities for demand side management (DSM) to maintain a supply/demand balance. Domestic electricity demand is approximately a third of total GB demand and has the potential to provide a significant demand side resource. An optimization model of UK electricity generation has been developed with an objective function to minimize total system cost (£m/year). The models show that dispatchable output falls from 77% of total output in 2012 to 69% in 2020, 41% in 2030 and 28% in 2050, supporting the need for increased levels of future DSM. Domestic demand has been categorised to identify flexible loads (electric space and water heating, cold appliances and wet appliances), and projected to 2030. Annual flexible demand in 2030 amounts to 64.3TWh though the amount of practically available demand varies significantly on a diurnal, weekly and seasonal basis. Daily load profiles show practically available demand on two sample days at three sample time points (05:00, 08:00 and 17:30) varies between 838MW and 6,150MW. Access to flexible demand for DSM purposes is dependent on the active involvement of domestic consumers and/or their acceptance of appliance automation. Analysis of a major quantitative survey and qualitative workshop dataset shows that 49% of respondents don’t think very much or not at all about their electricity use. This has implications for the effectiveness of DSM measures which rely on consumers to actively modify behaviour in response to a signal. Whilst appliance automation can be a practical solution to realising demand side potential, many consumers are reluctant to allow remote access. Consumers are motivated by financial incentives though the low value of individual appliance consumption limits the effectiveness of solely financial incentives. A range of incentives would be required to encourage a wide cross-section of consumers to engage with their electricity consumption.

To achieve a high level of reliability and robustness in power systems, the grid is usually designed for the peak demand rather than the average demand. This usually results in an under-utilized system. Demand side management (DSM) programs can be adopted to shape the load pattern of the users to better utilize the available power generation capacity and to prevent installing new generation and transmission infrastructures. In this thesis, we propose different algorithms for DSM. First, we focus on the problem of maximizing the social welfare of the users. We consider a scenario where the users are equipped with automated control units and are able to make price-responsive decisions. We propose a Vickrey-Clarke-Groves (VCG) mechanism to maximize the social welfare of the users. Subsequently, we focus on developing a novel automated load scheduling algorithm to minimize the energy expenses of the user. The proposed algorithm takes into account the effects of the load uncertainties in future time slots. Moreover, the operational constraints of different types of appliances including must-run appliances, and interruptible and non-interruptible controllable appliances are studied. Next, we study how the utility company can set price values for different times of a day such that the peak-to-average ratio (PAR) of the load is minimized. We also consider the effects of the uncertainty regarding the price-responsiveness of the users. To simulate the likely behavior of the users in response to different price values for different times of the day, we propose the use of a system simulator unit. We propose two pricing algorithms based on stochastic approximation aiming to minimize the PAR of the aggregate load. Finally, we consider systems with high penetration of renewable energy resources. To tackle the reverse power flow problem associated with these systems, we propose a joint load scheduling and trading algorithm. This algorithm encourages the users to sell their excess generation to their neighboring users which mitigates the reverse power flow problem.
Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate

In the light of increasing volatility in electricity price and availability, demand side management (DSM), which refers to the active management of electricity consumption, has become crucial for the economic performance of power-intensive industries. Due to its time-sensitive nature, DSM is a challenge for industrial plants; however, it can also be an opportunity if sufficient process flexibility is available, which can be leveraged to take advantage of financial incentives provided by various electricity markets. The goal of this work is to develop systematic decision-making tools for industrial DSM at the enterprise level. We identify and address four major challenges: (1) accurate modeling of operational flexibility, (2) integration of production and energy management, (3) decision-making across multiple time scales, and (4) optimization under uncertainty. We develop a discrete-time mixed-integer linear programing (MILP) model that integrates detailed production scheduling and electricity procurement from various sources. The proposed model is proven to be computationally efficient, which can be attributed to the mode-based formulation and the incorporation of a special type of process surrogate model, referred to as Convex Region Surrogate (CRS). In a CRS model, the feasible region is given by the union of convex regions in the form of polytopes, and for each region, the corresponding cost function is approximated by a linear function. For the construction of CRS models, we propose a data-driven algorithm that can be applied to data obtained from the real process or from simulations. Using the proposed integrated scheduling model as a basis, we optimize decisions regarding load shifting, inventory management, electricity procurement, energy storage, provision of interruptible load, etc. The framework is further extended to the supply chain level by also integrating distribution decisions, resulting in a multiscale production routing problem (MPRP). In order to solve large instances of the MPRP, we propose an iterative MILP-based heuristic algorithm that obtains high-quality solutions in reasonable computation times. A strong focus of this work lies on the treatment of uncertainty, which occurs in many forms in industrial DSM problems. We consider uncertainty in product demand, electricity price, and grid contingency events. These uncertainties all have different characteristics and affect the process in different ways; hence, we consider them using different modeling strategies, namely stochastic programming and robust optimization. We emphasize the consideration of risk, which is incorporated into the stochastic programming model using the conditional value-at-risk. In the proposed robust optimization models, we reduce the level of conservatism by implementing appropriate budget uncertainty sets and incorporating recourse decisions in the form of linear decision rules. Computational challenges are addressed by applying reformulations and decomposition strategies. Finally, we examine for linear systems the relationship between flexibility analysis and robust optimization. The effectiveness of the proposed methodologies is demonstrated in several case studies, many of which consider industrial test cases with real-world data provided by Praxair.

The work presented in this thesis concerns itself with the application of Demand Side Management (DSM) by industrial subsector as applied to the UK electricity industry. A review of the origins of DSM in the US and the relevance of experience gained to the UK electricity industry is made. Reviews are also made of the current status of the UK electricity industry, the regulatory system, and the potential role of DSM within the prevalent industry environment. A financial appraisal of DSM in respect of the distribution business of a Regional Electricity Company (REC) is also made. This financial appraisal highlights the economic viability of DSM within the context of the current UK electricity industry. The background of the work presented above is then followed by the construction of a framework detailing the necessary requirements for expanding the commercial role of DSM to encompass benefits for the supply business of a REC. The derived framework is then applied, in part, to the UK ceramics manufacturing industry, and in full to the UK sanitaryware manufacturing industry. The application of the framework to the UK sanitaryware manufacturing industry has required the undertaking of a unique first-order energy audit of every such manufacturing site in the UK. As such the audit has revealed previously unknown data on the timings and magnitude of electricity demand and consumption attributable to end-use manufacturing technologies and processes. The audit also served to reveal the disparity in the attitudes toward energy services, and thus by implication towards DSM, of manufacturers within the same Standard Industrial Classification (SIC) code. In response to this, attempt is made to identify the underlying drivers which could cause this variation in attitude. A novel approach to the market segmentation of the companies within the UK ceramics manufacturing sector has been utilised to classify these companies in terms of their likelihood to participate in DSM programmes through the derived Energy Services approach. The market segmentation technique, although requiring further development to progress from a research based concept, highlights the necessity to look beyond the purely energy based needs of manufacturing industries when considering the utilisation of the Energy Services approach to facilitate DSM programs.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
O presente trabalho é o resultado de uma pesquisa aplicada ao desenvolvimento de um equipamento eletrônico microprocessado destinado ao controle de demanda máxima e de fator de potência em instalações elétricas. Motivado pelo aumento na demanda e pela limitação nos recursos do sistema elétrico interligado, o uso de equipamentos que permitam o gerenciamento de energia pelo lado da demanda tem se difundido com grande velocidade, pois é o método de racionalização do uso de energia elétrica que apresenta boa relação entre custo e benefícios, trazendo resultados favoráveis em curto prazo. O uso de controladores de demanda máxima e de fator de potência nas instalações atendidas por contratos de fornecimento horo-sazonal é uma forma de garantir que o sistema não ultrapasse os limites contratuais, que resultam em aplicação de multa, e também um modo de se operar o sistema dentro de parâmetros conhecidos evitando perdas excessivas, racionalizando a utilização de seus componentes. Embora não exista regulamentação relacionada a tarifas diferenciadas de energia elétrica para unidades atendidas em baixa tensão, a utilização de controladores de demanda máxima e fator de potência pode trazer à esta classe de consumidores os benefícios do gerenciamento de energia, reduzindo perdas e em muitos casos permitindo a diminuição no valor da fatura de energia. Pelo ponto de vista do fornecimento, a existência de controle de demanda nas unidades consumidoras permite um melhor planejamento e maior aproveitamento do sistema de distribuição, minimizando investimentos no setor. Para aplicação em unidades consumidoras de porte reduzido, os equipamentos de gerenciamento de energia disponíveis no mercado apresentam dois inconvenientes principais: o excesso de recursos que na maioria dos casos não é explorado em sua...
The present work is the result of an applied research to the development of an electronic microcontrolled device used in the control of maximum demand and power factor in small and medium range electric facilities. Stimulated by the increase of demand and limitation of electrical resources of the interconnected system, the use of demand-side energy management devices was increased, since this method is the better mode to provide the energy rationalization, good cost-benefits relationship and presents best results in a short time interval after its implementation. The use of maximum demand and power factor controllers in facilities with differential billing fares is a method of guarantee that the agreement limits will not be exceeded, resulting in penalties, and also a safe mode of system operation, reducing losses and rationalizing the use their components. Although don't exist regulation related to the differential billing applied to low-voltage supplied consumers, the use of maximum demand and power factor controllers can bring to this consumers category the benefits of energy management, reducing losses and in most cases decreasing the energy billing. In the supply point of view, the demand control in consumers units allow the better planning and the best utilization of distribution system, minimizing the investment in this sector. For application in small-size consumer units, the commercially available energy management devices have two inconvenient: excess of resources, in the most cases sub-utilized which increase the price, and the need of a special external energy meter or energy transducer, uncommon in this class of facility. The device developed in this research have an electronic energy measurement system and associated signals independent of the supplier's meter, and also... (Complete abstract click electronic access below)

Demand Side Management (DSM) is the planning and implementation of strategies intended to encourage electricity consumers to reduce energy demand, improve energy efficiency, shift time of usage and promote the use of renewable energy based distributed generation system. It is a close socio- economic link between the utility and consumer for mutually benefiting to both. The research undertaken rivets on the potential use of DSM strategies to regulate electrical energy demand and mitigate carbon emissions in Oman. The main objective of this research is to examine the DSM based activities and policy options which could achieve significant reduction in electricity demand at the distribution network connected to the residential sector. It is revealed that temperature is the major environmental factor while use of air- conditioner units and practice of subsidised tariffs are epic centres of lavish electricity consumption at residential sector in Oman. This study applies a scenario based approach to identify viable energy efficiency and load reduction methods. The technical analysis comprises of bottom-up approach considering operational, behavioural and environmental factors to simulate the hourly load profile. Household load patterns are developed to identify and implement a range of DSM technological activities. An analytical model is set up to control the household load with minimal compromise of end-user satisfaction. Obtained results show that application of DSM strategies could contribute the substantial reduction in peak load and total energy demand. Studies carried out on renewable energy based hybrid power system manifest the viability and cost effectiveness of distributed generation to mitigate carbon emissions and peak load demand. The results of technical analysis are used to explicate the essential policy priorities underpinning the sustainable development of energy sector and mitigate the environmental issues. This comprehensive study provides the base to recommend the incentive based DSM programmes, smart metering, legal frame work for energy efficiency standards and labelling, investment subsidies to encourage renewable energy and legislation for distributed generation. The research has explored the benefits of DSM programmes along with barriers and challenges to implement the appropriate policies.

Durch den Ausbau an Wind- und PV-Anlagen in Deutschland wird der Flexibilitätsbedarf im Stromsystem steigen. Der Flexibilitätsbedarf kann zum einen durch verschiedene Technologien, z.B. Speicher oder Netze, und zum anderen durch die Stromnachfrage bereitgestellt werden. Eine gezielte Steuerung der Stromnachfrage wird als Demand Side Management (DSM) bezeichnet. Der zunehmend wetterabhängigen und fluktuierenden Stromerzeugung in Deutschland steht jedoch eine bis heute weitgehend unelastische Nachfrage gegenüber. In der Literatur sind verschiedene Arbeiten zu finden, die das Potential zur Lastabschaltung und verschiebung in Deutschland untersuchen. Hierbei liegt der Fokus auf absoluten Werten. Saisonale oder tageszeitliche Unterschiede bleiben dabei häufig unberücksichtigt. Die vorliegende Dissertation greift an dieser Stelle an und untersucht das Potential ausgewählter DSM-Anwendungen in stündlicher Auflösung. Die Ergebnisse zeigen, dass das verfügbare Potential starken saisonalen und tageszeitlichen Schwankungen unterliegt. Dementsprechend wird das DSM-Potential überschätzt, wenn nur absolute Werte betrachtet werden. Darüber hinaus zeigt die Autorin, welche Entwicklungen in den nächsten Jahren hinsichtlich der Verfügbarkeit des DSM-Potentials zu erwarten sind. Basierend auf der Potentialermittlung wird in der Dissertation die Rolle von DSM in einem EE-geprägten Stromsystem modellbasiert untersucht. Hierfür wird das lineare Optimierungsmodell ELTRAMOD, das den deutschen und europäischen Strommarkt abbildet, weiterentwickelt. Anhand verschiedener Szenarien wird zum einen der Beitrag von DSM zur Systemintegration von erneuerbaren Energien in Deutschland und zum anderen die Wechselwirkungen mit anderen Flexibilitätsoptionen (z.B. Speicher) untersucht. Die Ergebnisse zeigen, dass die DSM-Kategorien Lastabschaltung und verschiebung nur kurzzeitig auftretende Schwankungen der Einspeisung aus erneuerbaren Energien ausgleichen können. Zum Ausgleich großer Überschussmengen aus erneuerbaren Energien sind hingegen Power-to-X-Technologien, z.B. Power-to-Heat, besser geeignet.

Restrictive social distancing measures imposed by governments across the world to prevent the spread of COVID-19 have led to immediate changes in general behaviour and habits, which has had major effects on electricity systems. The pandemic has highlighted the great importance of reliable electricity supply in society as many people were forced to start working from home and thus became entirely reliant on digital modes of communication and information sharing. However, the resilience of energy systems could become weakened in the future as the share of intermittent renewable energy sources keeps increasing. If working from home were to become the norm in the future, knowing how households’ electricity load curves are affected by such a change could be valuable and help increase capabilities of demand side flexibility in the household sector. In this project, appliance-level electricity demand data gathered from Swedish households is used to create a simple bottom-up model. The purpose of the model is to be able to evaluate how the total electricity demand in a residential area changes after implementing behavioral changes at a household level. Specifically, the model was used to evaluate the effect of certain households in a region switching to working from home. Results were obtained from the model in the form of estimated changes in the electricity demand for different proportions of teleworking households. These changes were then combined with electricity demand data from a residential area in Stockholm to create new load curves that show what electricity demand could look like for the residential area at different shares of households working from home. The final results are presented in the form of estimated changes in electricity demand, peak power and electricity consumption for 30, 60 and 90 percent of households working from home.The results showed that weekdays' average load profile may have changed considerably in 2020 for residential areas similar to the one studied in Stockholm. For all scenarios, the change in electricity demand was most noticeable in the middle of the day, when the peak power increased significantly. During the evening, however, neither the electricity demand nor the power peak changed significantly. The peak power during normal working hours increased by 11,6% to 17,1% depending on the season, while total electricity consumption on an average weekday increased by 4,9% to 7,4% compared to pre-pandemic values. Still, the overall weekday power peak typically occurring around dinner time remained nearly unchanged. However, examining the results for different shares of households working from home shows that if almost all were to work from home, the overall peak power could shift from occurring in the evening to the middle of the day. If a new measurement campaign of Swedish households were to be conducted in the future, the ability to predict and prepare for the electricity demand of tomorrow’s homes would improve greatly.
I ett försök att förhindra spridningen av viruset COVID-19 har länder världen över infört sociala restriktioner som i många fall medfört drastiska förändringar av invånarnas vanor och beteenden samt en omfattande påverkan på landets elsystem. Pandemin har framhävt vikten av tillförlitlig elförsörjning i samhället i och med att många har tvingats börja arbeta hemifrån och således blivit helt beroende av digital kommunikation och informationsdelning. Energisystemens motståndskraft kan dock komma att försvagas i framtiden i takt med att andelen intermittenta förnybara energikällor fortsätter att öka. Om distansarbete skulle bli det nya normala i framtiden kan det vara värdefullt att känna till hur det påverkar hushållens belastningskurvor. Kunskapen kan även bidra till ökade möjligheter för flexibilitet på efterfrågesidan i hushållssektorn. I det här projektet används elbehovsdata på apparatnivå från ett stort antal svenska hushåll för att skapa en enkel bottom-up-modell över hushålls elförbrukning. Modellens syfte är att genom implementering av beteendeförändringar på en hushållsnivå kunna utvärdera hur det totala elbehovet i ett bostadsområde förändras. Specifikt användes modellen för att utvärdera effekten av att vissa hushåll i en region går över till distansarbete. Resultat erhölls från modellen i form av uppskattade förändringar av elbehovet vid olika andelar distansarbetande hushåll. Dessaförändringar kombinerades sedan med elbehovsdata från ett bostadsområde i Stockholm för attskapa nya belastningskurvor som visar hur elbehovet kan se ut för bostadsområdet vid olikaandelar distansarbetande hushåll. De slutgiltiga resultaten presenteras i form av uppskattade förändringar av elbehov, effekttoppar och elförbrukning vid 30, 60 och 90 procents andel distansarbetande hushåll. Resultaten visade att vardagars genomsnittliga belastningsprofil kan ha förändrats markant under 2020 för bostadsområden likt den studerade i Stockholm. För samtliga scenarier var förändringen i elbehovet mest märkbar mitt på dagen då effekttoppen ökade avsevärt. Under kvällstid förändrades dock varken elbehovet eller effekttoppen avsevärt. Effekttoppen under normala arbetstider ökade mellan 11,6% och 17,1% beroende på årstid, medan elförbrukningenen genomsnittlig vardag ökade med mellan 4,9% och 7,4% jämfört med innan pandemin.  Kvällens effekttopp, som vanligtvis inträffar runt middagstid, var i princip oförändrad. Däremot visar resultaten att i ett scenario där en mycket hög andel av befolkningen arbetar hemifrån kan den högsta effekttoppen inträffa mitt på dagen istället för på kvällen. För framtiden skulle en ny mätkampanj som kartlägger de svenska hushållens elförbrukning kunna medföra ökade möjligheter för samhället att förbereda sig inför och förutse morgondagens elbehov.

This research develops a systematical tool to recommend the best short-term operation and long-term investment planning to manage energy bills for neighbourhoods and precincts. Building energy efficiency measures, rooftop solar systems and batteries are evaluated with detailed operational simulation to estimate yearly bill savings across the economic lifetime of investment options. The outcome of this work is that integrated operation and investment options can provide the best return on energy investment for community cases.

Demand side management (DSM) is a means to improve the energy efficiency, reduce the greenhouse gas emission, the consumers’ cost and the power grid investments. Due to the energy shortage and environmental problems, DSM has received more attention in recent decades. In this thesis, a micro grid consisted of 100 fridges is constructed to simulate the approach of DSM. The thermodynamic model of refrigeration system is simulated. Three schedulers are designed, implemented and programmed to execute the load switching based on the power curves. Simulations are carried out on Matlab. Results are analyzed and discussed based on the overall power consumption, average power and temperature.

Power networks are under increasing pressure to maintain operation within permissible voltage and current limits with higher penetrations of renewable energy. This thesis aims to develop and evaluate a practical and economical way to control key domestic appliances to alleviate stress caused by high level of renewable energy penetration. The first objective in this thesis is to develop a network stress identification technique that does not rely on communication infrastructure. Traditionally, there is an emphasis on using centralized control strategies for demand side management (DSM) involving a central brain which collects information from each individual device and sends out commands to them which schedules their operation. This approach relies heavily on communication infrastructure and introduces security challenges, which are not problems for distributed or decentralised control. Whilst the latter two approaches have the virtue of scalability and flexibility, they require a good network model or good estimation of network condition without real time communication for effective control. A tap change detection approach via local voltage measurement has been developed and validated to enable the domestic smart appliance to perceive the network stress in three different levels across the power network without any real-time communication. The second objective is to explore the economic benefits associated with the usage of electric hot water tanks (EHWTs) as an alternative to home batteries or electric vehicles for demand response. To do this, an optimization approach for sizing of the EHWT is proposed. Real-world hot water usage data is analysed and applied, revealing four typical hot water usage patterns and 100-litre as the most common optimal tank size for UK consumer. Finally, since increasing PV generation has risen voltage concerns in various locations across the UK, such as in Cornwall, this thesis investigated to what extend intelligent EHWTs can be used to alleviate the LV network stress caused by the high level of PV penetration. A Monte-Carlo simulation is carried out on real UK LV networks, showing that the presence of intelligent EHWTs could improve both the voltage and current performance of the LV network and allow 50% more PV installations beyond the network's original capacity.

En raison de l'augmentation des coûts d'énergie et des préoccupations environnementales telles que les empreintes de carbone élevées, les systèmes de la production d'électricité centralisée se restructurent pour profiter des avantages de la production distribuée afin de répondre aux exigences énergétiques toujours croissantes. Les microgrids sont considérés comme une solution possible pour déployer une génération distribuée qui inclut des ressources énergétiques distribuées DERs (Distributed Energy Resources)(e.g, solaire, éolienne, batterie, etc). Dans cette thèse, nous traitons les défis de la gestion d'énergie dans un microgrid industriel où les charges énergétique sont constituées de processus industriels. Notre plan consiste à diviser la gestion de l'énergie du microgrid en deux parties: la production et la demande d’énergie.Du côté de la production d'énergie, les défis incluent la modélisation des générations de puissance et le lissage des fluctuations des DER. Pour modéliser les générations de puissance, nous proposons un modèle basé sur les concepts de service courbé de Network Calculus. En utilisant cet outil mathématique, nous déterminons une quantité minimale de puissance que les DERs peuvent générer; leur agrégation nous donnera une production d'énergie totale dans le microgrid. Après cela, s'il existe un déséquilibre entre la production et la demande d'énergie, nous proposons des stratégies différentes pour minimiser les coûts d'approvisionnement énergétique. Sur la base des données réelles de la consommation d'énergie d'un site industriel situé en France, des économies significatives peuvent être réalisées en adoptant ces stratégies. Dans cette thèse, nous étudions également comment atténuer les effets des fluctuations de puissance des DERs en conjonction avec des systèmes de stockage d'énergie. Pour cela, nous proposons un algorithme de lissage gaussien et nous le comparons avec des algorithmes de lissage trouvés dans l'état de l'art. Nous avons trouvé que l'algorithme proposé utilise de batterie de moins de taille à des fins de lissage par rapport à d'autres algorithmes. À cette fin, nous sommes également intéressés à étudier les effets de la gamme admissible des fluctuations sur les tailles de la batterie.Du côté de la demande, l'objectif est de réduire les coûts de l'énergie grâce aux approches de gestion de la demande DSM (Demand Side Management) telles que Demand Response (DR) et Energy Efficiency. Comme les processus industriels consomment énormément, une petite réduction de la consommation d'énergie en utilisant les approches DSM pourrait se traduire par des économies cruciales. Cette thèse se concentre sur l'approche DR qui peut profiter des prix variables de l'électricité dans le temps pour déplacer les demandes énergétiques des heures de pointe aux heures creuses. Pour atteindre cet objectif, nous comptons sur un modèle basé sur la théorie de file d'attente pour caractériser les comportements temporels (arrivée et départ des tâches) d'un système de fabrication. Après avoir défini les processus d'arrivée et de départ de tâches, une fonction d'utilisation efficace est utilisée pour prédire le comportement de la machine dans un domaine temporel et qui peut afficher son statut (allumé/éteint) à tout moment. En prenant le statut de chaque machine dans une ligne de production comme une entrée, nous proposons également un algorithme de planification DR qui adapte la consommation d'énergie d'une ligne de production aux deux contraintes de puissance disponibles et de taux de production. L'algorithme est codé à l'aide d’une machine d’état fini déterministe (Deterministic Finite State Machine) dans laquelle les transitions d'état se produisent en insérant une tâche à l'entrée du tapis roulant (on peut aussi avoir des transitions sans insertion de taches). Nous définissons des conditions pour l'existence d’un planificateur réalisable et aussi des conditions pour accepter positivement des demandes DRs
Due to increased energy costs and environmental concerns such as elevated carbon footprints, centralized power generation systems are restructuring themselves to reap benefits of distributed generation in order to meet the ever growing energy demands. Microgrids are considered as a possible solution to deploy distributed generation which includes Distributed Energy Resources (DERs) (e.g., solar, wind, battery, etc). In this thesis, we are interested in addressing energy management challenges in an industrial microgrid where energy loads consist of industrial processes. Our plan of attack is to divide the microgrid energy management into supply and demand sides.In supply side, the challenges include modeling of power generations and smoothing out fluctuations of the DERs. To model power generations, we propose amodel based on service curve concepts of Network Calculus (NC). Using this mathematical tool, we determine a minimum amount of power the DERs can generate and aggregating them will give us total power production in the microgrid. After that, if there is an imbalance between energy supply and demand, we put forward different strategies to minimize energy procurement costs. Based on real power consumption data of an industrial site located in France, significant cost savings can be made by adopting the strategies. In this thesis, we also study how to mitigate the effects of power fluctuations of DERs in conjunction with Energy Storage Systems (ESSs). For this purpose, we propose a Gaussian-based smoothing algorithm and compare it with state-of-the-art smoothing algorithms. We found out that the proposed algorithm uses less battery size for smoothing purposes when compared to other algorithms. To this end, we are also interested in investigating effects of allowable range of fluctuations on battery sizes.In demand side, the aim is to reduce energy costs through Demand Side Management (DSM) approaches such as Demand Response (DR) and Energy Efficiency (EE). As industrial processes are power-hungry consumers, a small power consumption reduction using the DSM approaches could translate into crucial savings. This thesis focuses on DR approach that can leverage time varying electricity prices to move energy demands from peak to off-peak hours. To attain this goal, we rely on a queuing theory-based model to characterize temporal behaviors (arrival and departure of jobs) of a manufacturing system. After defining job arrival and departure processes, an effective utilization function is used to predict workstation’s (or machine’s) behavior in temporal domain that can show its status (working or idle) at any time. Taking the status of every machine in a production line as an input, we also propose a DR scheduling algorithm that adapts power consumption of a production line to available power and production rate constraints. The algorithm is coded using Deterministic Finite State Machine (DFSM) in which state transitions happen by inserting a job (or not inserting) at conveyor input. We provide conditions for existence of feasible schedules and conditions to accept DR requests positively.To verify analytical computations on the queuing part, we have enhanced Objective Modular Network Testbed in C++ (OMNET++) discrete event simulator for fitting it to our needs. We modified various libraries in OMNET++ to add machine and conveyor modules. In this thesis, we also setup a testbed to experiment with a smart DR protocol called Open Automated Demand Response (OpenADR) that enables energy providers (e.g., utility grid) to ask consumers to reduce their power consumption for a given time. The objective is to explore how to implement our DR scheduling algorithm on top of OpenADR

The continuous development of Electricity Storage Systems (ESS) technologies has made them interesting choices in the utility scale electricity market. Renewable sources intermittency, load management and power quality are the major purposes of ESS investment in grids. Their primary goal is to technically find the best solution for those problems, while the economic profits pass through that. However, in the increasingly competitive market environments, ESS would possibly be able to be operated simply to maximise profits for the investor, without aiming in a specific technical problem solution. In that sense, ESS follow the simple guideline oftrading wholesale electricity; purchasing cheap and selling expensive electricity. Another characteristic of today's electricity markets is that the load pattern becomes more erratic, having higher peaks and the load factor ofthe generation and grid falls. Utilities use Demand-Side Management (DSM) to control the demand. One of the features of this control is the peak shaving and shifting of load to off-peak hours. This research optimises the operation ofESS; it identifies the best combination ofcharging and discharging operations (duration and timing within a management period) aiming in maximisation of profits, in two options of management periods; one-day and three-day. Three very important elements of the analysis is the extent in which the profitability ofESS is affected by the existence ofDSM programmes in the market, whether the ESS can be granted with emissions allowances and up to which installed capacity of ESS in the electricity network the profits are positive. For this purpose, a dynamic optimisation model has been built, which incorporates a deterministic model as a real case of application with specific values of parameters. The dynamic modelling assesses the point where the investments in power capacity of ESS show their maximum achieved profits per installed MW, in combinations of four main options: DSM, NoDSM, 24h and 72h management period. The deterministic model aims at the optimisation ofthe allocation ofthe charge and discharge operations, simulating a real situation with specific data and parameters. The results show that DSM programmes can have substantial impacts on net revenues and profits achieved by ESS, but not such, on variable costs and revenues. Profitability falls and amongst the storage technologies tested, only those with high electrical round trip efficiency and low replacement costs can be viable investment options. So, the extent of DSM application in the market can influence storage profitability in a variable way. High capital costs and low efficiencies are the first factors to work prohibitively, alongside with DSM, to the profitability ofESS. Investigation of extending the management period from one to three days, has given higher net revenues with relatively smaller increase of discharged electricity. The indirect emissions d'le to the charging operation of the ESS depend on the primary source of energy used to generate the electricity which was stored and therefore, the ESS cannot be granted of emissions allowances in the way they are considered in this research. However, if there are bilateral trading agreements between renewable energy generators and the operators of the ESS, then the avoided emissions of ESS would be positive and the profitability would grow from the participation in the ETS. In the case that the regulations could recognise some economic benefits for ESS (like they do for renewable sources) they could stand more easily and quickly in the competitive electricity market. Funding opportunities for covering the capital cost and special rates for selling electricity to the network and for providing ancillary services can be some of them.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2018
Cataloged from PDF version of thesis.
This thesis develops a strategic positioning for a consulting company operating in the demand-side of the business, that will utilize a strategic framework "create-capture- deliver" and help its customers to generate value using massive smallscale experimentations. The thesis addresses questions like best target industries, using human capital as a strategic resource of the company, and managing strategic partnerships. Efficient price optimization has become a competitive edge for many industries. Constant review of prices by pricing consultants may be an essential tool for some industries and companies but totally unacceptable for others. This study helps to clarify who would appreciate the service of price optimization. The study further provides insights on the types of firms that would need pricing services and how they can both integrate such services into their daily operations and turn such services into strategic advantage.
by Olga Egorov.
M.B.A.
M.B.A. Massachusetts Institute of Technology, Sloan School of Management

Electricity networks are undergoing a period of rapid change and transformation, with increased penetration levels of renewable-based distributed generation, and new influences on electricity end-use patterns from demand-manageable loads and micro-generation. This creates a number of new challenges for the delivery of a reliable supply of electrical energy. The main aim of this PhD research is to provide a methodology for a more detailed and accurate assessment of the effects of wind-based distributed generation (DG) and demand side management (DSM) on transmission network operation. In addition, the work investigates the potential for co-ordinated implementation and control of DG and DSM to improve overall system performance. A significant amount of previous literature on network integration of DG and DSM resources has focused on the effects at the distribution level, where their impact is direct and often easily observed. However, as penetration levels increase, DG and DSM will have a growing influence on the operation and management of the bulk transmission system. Modelling and analysis of the impact of embedded and highly-dispersed DG and DSM resources at transmission voltage levels will present a significant challenge for transmission network operators in the future. Accordingly, this thesis presents a number of new approaches and methodologies allowing for a more accurate modelling and aggregation of DG and DSM resources in power system studies. The correct representation of input wind energy resources is essential for accurate estimation of power and energy outputs of wind-based DG. A novel modelling approach for a simple and accurate representation of the statistical and temporal characteristics of the wind energy resources is presented in the thesis. An "all-scale" approach to modelling and aggregation of wind-based generation is proposed, which is specifically intended for assessing the impact of embedded wind generation on the steady state performance of transmission systems. The methodology allows to include in the analysis wind-based generation at all scales and all levels of implementation, from micro and small LV-connected units, through medium-size wind plants connected at MV, up to large HV-connected wind farms. The thesis also presents an assessment of the potential for DSM in the UK residential and commercial sectors, based on the analysis and decomposition of measured demands at system bulk supply points into the corresponding load types. Using a section of the Scottish transmission network as a case study, a number of DG and DSM scenarios are investigated in detail. These results demonstrate the importance of accurately modelling the interactions between the supply system and various DG and DSM schemes, and show that the aggregated effects of highly-distributed DG and DSM resources can have significant impacts on the operation of the bulk transmission system.

Carbon emission reduction is an urgent global task. Renewable energy sources integration can promote the transformation of cleaner and greener power system. But the time-varying nature of these sources causes indeterminacy problems. Smart grid is a powerful tool that can deal with these problems in electricity aspect. One of the key smart grid technologies is demand side management. How to use demand side management to regulate and decarbonise the power system is the main point of this thesis. In order to integrate renewable energy sources, a day-ahead electricity market scheme is proposed, involving the utility, the demand response aggregator and customers. This model leads to a multiobjective optimization problem, which is solved by an artificial immune algorithm. The simulation results confirm the feasibility and robustness of the proposed model. All participants can benefit from it, and the system power peak to average ratio can be reduced. In order to realize the carbon emission reduction, a system model for annual fuel sources scheduling and operational policy making of electricity generation is established, considering the economic, environmental and social aspects. A minimum Manhattan distance approach is proposed to select the final solution. The impacts of carbon tax and renewable obligation on carbon emission, generation cost and electricity bill are examined. These can reveal the proper strategy for deciding renewable energy source and carbon emission related policies. After that, a carbon emission flow model is introduced to facilitate the analysis and assessment of demand side management's impacts on carbon emission reduction. The time sensitivity of carbon emission in both generation side and customer side are obtained. The daily case and seasonal case are presented. The simulation results show that the load curtailment and load shift approaches can effectively reduce the carbon emission.