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1
Setlhaolo, Ditiro. "Optimal management of household load under demand response." Thesis, University of Pretoria, 2015. http://hdl.handle.net/2263/56107.
Full textAbstract:
Residential demand response (RDR) is one of the demand side management (DSM) programs
for smart grid applications that are designed to enable utility companies to manage the userside
electrical loads and also for consumers to voluntarily lower their demand. Instead of
adding more generators to the electrical power system, RDR programs pay residential energy
users to reduce consumption. Due to the complex interactions between residential customers
and the power utility companies; in this thesis, RDR is studied using an optimization
approach for the reason that optimization of energy consumption, with consequent cost reduction,
is among the primary problems of the present and future smart grid. In this thesis
optimal control models are formulated to study household energy management under timeof-
use (TOU) electricity pricing strategy.
The initial optimal control mathematical model is developed where consumers attempt to
find the best way to schedule their household electrical resources depending on the tariff
provided by the utility and the incentive offered during peak times. Under such a setting,
whenever customers have enough transferable appliances, significant energy cost savings can
be achieved with proper modelling of appliance usage in a household. Consumer behaviour
plays a crucial role in ensuring that RDR is achieved. It has been discovered in this thesis
that; inconvenience, incentive, budget and coordination of appliances affect consumer s energy
consumption behaviour. Other areas that need attention in order to further enhance the
solutions of the research question are investigated. It has been shown that by incorporating
the storage and photovoltaic (PV) generator the consumer can increase cost savings and
reduce their electricity peak consumption further as well as the total energy drawn from
the grid. Insights on the complexity of the optimization problem are provided, to allow
customers to better determine the trade-off between complexity, cost, and the need to schedule
their energy resources. The derived models provide a blueprint for integrating demand-side
management and scheduling of resources.
The other part of the study proposes an optimal energy management system that combines
DSM strategies for aggregated households; DR with a dedicated PV and battery which shows
that the aggregated consumption can reduce the power demanded from a distribution system
by a significant amount and thus relieve the power system network and afford some residential
members significant collective savings. Further more, it is shown in this thesis that
knowledge on carbon emissions can incentivize investment in renewable energy at household
level. It is also demonstrated that the consumer s preferences on the cost sub-functions of
energy, inconvenience and carbon emissions affect the consumption pattern. These results are
important for both the consumer and the electricity suppliers, as they illustrate the optimal
decisions considered in the presence of multiple sub-objectives.
In this work, field measurements are carried out to obtain the baseline appliance commitment
and these are compared with the optimal solutions obtained through the inconvenience
model.<br>Huishoudelike vraagrespons (HVR) is een van die vraagkantbestuur- (VKB) programme
vir slimnetwerktoepassings wat ontwerp is om elektrisiteitsmaatskappye toe te laat om
verbruikerskant- elektriese las te bestuur, asook om verbruikers toe te laat om hul elektriese
aanvraag vrywillig te verlaag. In plaas daarvan om meer elektrisiteit te genereer, betaal
HRV-programme huishoudelike verbruikers om hul verbruik te verlaag. Daar is komplekse
interaksies tussen huishoudelike verbruikers en die elektrisiteitsmaatskappye. Daarom is die
tesis dat HVR, benader vanuit n optimeringsperspektief, met gevolglike kostebesparing, een
van die hoofuitdagings van die toekomstige slimnetwerk is. In hierdie tesis word optimale beheermodelle
geformuleer om huishoudelike energiebestuur onder die tyd-van-verbruik- (TVV)
prysstrategie te bestuur.
Die aanvanklike optimale beheer wiskundige model word ontwikkel sodat die verbruiker sy
elektrisiteitsverbruik skeduleer om gebruik te maak van die aansporing wat tydens spitstye
gebied word. Sodoende kan noemenswaardige energiekostebesparings word, as verbruikers
oor genoeg verskuifbare elektriese toestel-laste beskik. Verbruikersgedrag speel n
deurslaggewende rol om HVR te verseker. Daar is in hierdie tesis bepaal dat ongerief, aansporing,
begroting, en koördinasie van toestelle verbruikers se energieverbruikgedrag beïnvloed.
Ander areas wat aandag nodig het ten einde oplossings te verbeter, word ook ondersoek.
Daar word getoon dat deur energiestoring en fotovoltaïese (FV) generators te gebruik, die
verbruiker sy kostebesparings kan vergroot en sy spitstydelektrisiteitsverbruik verder kan verlaag.
Insigte in die ingewikkeldheid van die optimeringsprobleem word verskaf, ten einde verbruikers
te help om kompleksiteit, koste en die skedulering van energiehulpbronne te bestuur.
Die modelle verskaf n bloudruk vir geïntegreerde VBK- en toestelvlakskedulering.
Die volgende gedeelte van die studie stel n optimale energiebestuursisteem vir VBK-strategieë
met gesommeerde huishoudings voor. VR met n toegewyde FV-sel en battery word gebruik,
en daar is bevind dat die gesommeerde verbruik noemenswaardig verminder kan word. Dit
bring noemenswaardige gesommeerde besparings vir sekere huishoudings teweeg, en verminder
ook die las op die elektrisiteitsnetwerk. Die volgende gedeelte van die studie wys dat
kennis van koolstofvrystellings beleggings in hernubare energie kan aanspoor op huishoudelike
vlak. Daar word ook bewys dat verbruikersvoorkeure met betrekking tot energie, gerief,
en koolstofvrystellings verbruikpatrone affekteer. Die resultate is belangrik vir beide elektrisiteitsverskaffers
en vebruikers, en illustreer optimale besluite gegewe die kompromieë tussen
teenstrydige doeleindes.
In hierdie werk word veldmetings gebruik om basislyntoesteltoewydings te bepaal en te
vergelyk met optimale oplossings wat deur simulasie verkry is.<br>Thesis (PhD)--University of Pretoria, 2015.<br>tm2016<br>Electrical, Electronic and Computer Engineering<br>PhD<br>Unrestricted
2
Zhao, Zezheng. "Residential Side Load Forecasting and Optimisation." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/27396.
Full textAbstract:
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.
3
Rahman, Md Moshiur. "Design and Implementation of a Web-based Home Energy Management System for Demand Response Applications." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23689.
Full textAbstract:
The objective of this work is to design and implement an architectural framework for a web-based demand management system that allows an electric utility to reduce system peak load by automatically managing end-use appliances based on homeowners\' preferences. The proposed framework comprises the following components: human user interface, home energy management (HEM) algorithms, web services for demand response communications, selected ZigBee and smart energy profile features for appliance interface, and security aspects for a web-based HEM system. <br />The proposed web-based HEM system allows homeowners to be more aware about their electricity consumption by allowing visualization of their real-time and historical electricity consumption data. The HEM system enables customers to monitor and control their household appliances from anywhere with an Internet connection. It offers a user-friendly and attractive display panel for a homeowner to easily set his/her preferences and comfort settings. <br />An algorithm to autonomously control appliance operation is incorporated in the proposed web-based HEM system, which makes it possible for residential customers to participate in demand response programs. In this work, the algorithm is demonstrated to manage power-intensive appliances in a single home, keeping the total household load within a certain limit while satisfying preset comfort settings and user preferences. Furthermore, an extended version of the algorithm is demonstrated to manage power-intensive appliances for multiple homes within a neighborhood.<br />As one of the demand response (DR)-enabling technologies, the web services-based DR communication has been developed to enable households without smart meters or advanced metering infrastructure (AMI) to participate in a DR event via the HEM system. This implies that an electric utility can send a DR signal via a web services-enabled HEM system, and appropriate appliances can be controlled within each home based on homeowner preferences. The interoperability with other systems, such as utility systems, third-party Home Area Network (HAN) systems, etc., is also taken into account in the design of the proposed web services-based HEM system. That is, it is designed to allow interaction with authorized third-party systems by means of web services, which are collectively an interface for machine-to-machine interaction. <br />This work also designs and implements device organization and interface for end-use appliances utilizing ZigBee Device Profile and Smart Energy Profile. Development of the Home Area Network (HAN) of appliances and the HAN Coordinator has been performed using a ZigBee network. Analyses of security risks for a web-based HEM system and their mitigation strategies have been discussed as well.<br /><br>Master of Science
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Majani, Charles Chore. "Development of an active load shifting technique for demand side management applications." Thesis, Cape Peninsula University of Technology, 2011. http://hdl.handle.net/20.500.11838/2200.
Full textAbstract:
Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2011.<br>Initiatives that are directed towards improving power management by a utility provider have
to consider technical feasibility, socio-economic and the environment. Patterns of power
consumption world over indicate that demand for electricity has over the years been on the
rise due to increase in activities that demand usage of electricity. Such activities include
construction and property development, development of industries and infrastructure. These
activities have strained the power production, whose development does not match the
increase in demand. ESKOM, a government authority mandated to generate, transmit and
distribute power in South Africa has seen demand surpassing its generation capacity, hence
resorting to load shedding actions. Load shedding imposes inconveniences to the consumers
who are completely disconnected from the grid, translating to unpredictable periods of
darkness. Utility providers have an option of constructing new peaker plants which lie idle
most of the day, to take care of high demand during the peak periods, hence, avoid effecting
load shedding actions.
Various ways of managing load have been presented in this research. In particular, the
research investigated possible ways utilities use in managing their capacity with an aim of
developing an alternative method and tool for Demand Side Management applications that
can be used by energy utility to improve reliability, manage and control consumption of
electrical energy through selective shedding of the load connected to the consumer when the
demand surpasses the utility's safe capacity.
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Tsivras, Sotirios-Ilias. "Load Demand Forecasting : A case study for Greece." Thesis, Högskolan i Gävle, Energisystem och byggnadsteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-29841.
Full textAbstract:
It is more than a fact that electrical energy is a main production factor of every economic activity. Since electrical power is not easy to store, it needs to be consumed as it is generated in order to keep a constant balance between supply and demand. As a result, for developing an efficient energy market it is significant to create a method for accurately forecasting the electricity consumption. This thesis describes a method for analyzing data provided by the ENTSO-E transparency platform. The ENTSO-E (European Network of Transmission System Operators) is a network of electricity operators from 36 countries across Europe. Its main objective is to provide transparency concerning data of electricity generation and consumption in Europe in order to promote the development of efficient and competitive electricity markets. By using the method described in this thesis, one may use historical data provided by ENTSO-E to forecast the electricity consumption of an EU country for the years to come. As an example, data of electricity consumption in Greece during the years 2015-2018 have been used in order to calculate the average load demand of a weekday during the year 2030. On the other hand, in order to correctly predict the electricity demand of a specific region over the next decade, one should take into account some crucial parameters that may influence not only the evolution of the load demand, but also the fuel mix that will be used in order to cover our future electricity needs. Advances in power generation technologies, evolution of fuel prices, expansion of electricity grid and economic growth are a subset of parameters that should be taken into account for an accurate forecast of the electricity consumption in the long run. Particularly for Greece, a set of parameters that may affect the electricity consumption are being computationally analyzed in order to evaluate their contribution to the load demand curve by the year 2030. These include the interconnection of Greek islands to the mainland, the development of Hellinikon Project and the increase of the share of electric vehicles. The author of this thesis has developed code in Python programming language that can be found in the Appendix. These scripts and functions that implement most of the calculations described in the following chapters can also be used for forecasting the load demand of other EU countries that are included in the ENTSO-E catalogue. The datasets used as input to these algorithms may also be used from the readers to identify more patterns for predicting the load demand for a specific region and time. A sustainable energy system is based on consumers with environmental awareness. As a result, citizens living inside the European Union should become a member of a community that promotes energy saving measures, investments in renewable energy sources and smart metering applications.
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Tsagkarakis, George. "Domestic demand and network management in a user-inclusive electrical load modelling framework." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/16207.
Full textAbstract:
Interest has been growing in the interaction of various power demand transformations, such as demand side management (DSM) and voltage control, with the power demand. Initial studies have highlighted the need for a better understanding of the power demand of low voltage (LV) residential networks. Furthermore, it is expected that future alteration of the residential appliance mixture, because of the advances in technology, will have an impact on both the demand curve as well as the electrical characteristics. This thesis presents a study of the impact of current and future household load on the power demand curve and the network operation. In order to achieve this, a bottom-up load modelling tool was developed to create LV detailed demand profiles that include not only the active and reactive power demand, but their electrical characteristics as well. The methodology uses a Markov chain Monte Carlo approach to generate residential LV demand profiles taking into account the user activity and behaviour to represent UK population. An appliance database has also been created which corresponds to the UK residential appliance mixture in order to calculate more accurately the power demand. The main advantages of the approach presented here are the flexibility in altering the type and number of the appliances that populate a household and how easily it can be adapted to a different population, location and climate. The tool is used to investigate the impact of scenarios that simulate future load replacement and the network behaviour under certain methods of demand control, implementation of DSM and control of voltage on the secondary of the LV transformer. The algorithm that was developed to apply the DSM actions on the power demand focused on the management of individual loads. The drivers used in this approach were the financial and environmental benefit of customers and the increase in the quality of the network operation. The control of the voltage as a method for power reduction takes into account the voltage dependence of the demand. The primary target is to quantify the benefits of this strategy either in combination with DSM for higher power reduction during the peak hours or on the current network as a quicker, easier and less expensive alternative to DSM. The study shows that there is a significant power reduction in both cases which is dependent on the time of day and not constant as expected from the literature. The results show that there are significant differences between current and future load demand characteristics that would be very difficult to acquire without the modelling technique presented. The alternative solution would require extensive local load and network modifications and a long period of expensive tests and measurements in the field.
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ALWAN, HAYDER O. "Load Scheduling with Maximum Demand and Time of Use pricing for Microgrids." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5954.
Full textAbstract:
Several demand side management (DSM) techniques and algorithms have been used in the literature. These algorithms show that by adopting DSM and Time-of-Use (TOU) price tariffs; electricity cost significantly decreases, and optimal load scheduling is achieved. However, the purpose of the DSM is to not only lower the electricity cost, but also to avoid the peak load even if the electricity prices low. To address this concern, this dissertation starts with a brief literature review on the existing DSM algorithms and schemes. These algorithms can be suitable for Direct Load Control (DLC) schemes, Demand Response (DR), and load scheduling strategies. \end{abstract} Secondly, the dissertations compares two of DSM algorithms to show the performance based on cost minimization, voltage fluctuation, and system power loss [see in Chapter 5]. The results show the importance of balance between objectives such as electricity cost minimization, peak load occurrence, and voltage fluctuation evolution while simultaneously optimizing the cost.
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Paisios, Andreas. "Profiling and disaggregation of electricity demands measured in MV distribution networks." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28777.
Full textAbstract:
Despite the extensive deployment of smart-meters (SMs) at the low-voltage (LV) level, which are either fully operational or will be in the near future, distribution network operators (DNOs) are still relying on a limited number of permanently installed monitoring devices at primary and secondary medium-voltage (MV) substations, for purposes of network operation and control, as well as to inform and facilitate trading interactions between generators, distributors and suppliers. Accordingly, improved and sufficiently developed models for the analysis of aggregate demands at the MV-level are required for the correct assessment of load variability, composition and time-dependent evolution, necessary for: addressing issues of robustness, security and reliability; accomplishing higher penetration levels from renewable/distributed generation; implementing demand-side-management (DSM) schemes and incorporating new technologies; decreasing environmental and economic costs and aiding towards the realisation of automated and proactive ''smart-grid'' networks. The analysis of MV-demand measurements provides an independent source of information that can capture network characteristics that do not manifest in the data collected at the LV-level, or when such data is restricted or altogether unavailable. This information describes the supply/demand interactions at the mid-level between high-voltage (HV) transmission and LV end-user consumption and opens possibilities for validation of existing bottom-up aggregation approaches, while addressing issues of reliance on survey-based data for technical and economic power system studies. This thesis presents improved and novel methodologies for the analysis of aggregate demands, measured at MV-substations, aimed at more accurate and detailed load profiling, temporal decomposition and identification of the drivers of demand variability, classification of grid-supply- points (GSPs) according to consumption patterns, disaggregation with respect to customer-classes and load-types and load forecasting. The developed models are based on a number of traditional and modern analytical and statistical techniques, including: data mining, correlational and regression analysis, Fourier analysis, clustering and pattern recognition, etc. The approaches are demonstrated on demand datasets from UK and European based DNOs, thus providing specific information for the demand characteristics, the dependencies to external parameters and to socio-behavioural factors and the most likely load composition at the corresponding geographical locations, while the approaches are also intendent to be easily adaptable for studies at equivalent voltage and demand aggregation levels.
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Sivabavanandan, Sivalingam. "Thermal energy storage application for load shifting and electrical demand management in Saudi Arabia." Thesis, Kingston University, 2005. http://eprints.kingston.ac.uk/35780/.
Full textAbstract:
Energy plays a major role in the economic prosperity of the Middle Eastern countries. Since the region is the largest oil producer of the world, it is less anticipated that these countries would ever be face with an energy crisis similar to the one experienced by the rest of the world during 1970s. The region was going through a chronic electricity demand supply crises with the demand for electrical energy in the rapidly expanding towns, cities and industries, far exceeding the power being made available. The relatively low electrical tariff also contributed to the increasing power demand due to wastage and uneconomical usage of electrical energy. The power generating companies and the Government authorities in the Middle East encouraged scientists and engineers to engage in ambitious Demand Side Management (DSM) programmes to develop novel ideas and new technologies to improve system efficiencies and to reduce energy consumption specifically in the field of refrigeration and air conditioning. The researcher began analysing the potential and possible applications of cool storage as a tool for Demand Side Management (DSM) in central air conditioning systems in the Middle East in 1991. The coupling of a refrigerated water storage tank or an ice storage tank to an air-cooled chiller plant, operated at night for load shifting, electrical peak demand reduction and energy conservation has been the major interest of investigation. The model project commissioned in 1996 used as a typical example to investigate electrical demand management for an office building in Riyadh, Saudi Arabia. The aim of this research was to develop new modified comfort cooling system coupled with a cool storage or commonly known as Thermal Energy Storage (TES) network. The research was expected to establish certain favouring conditions in relation to technical, economical and environmental criteria to make the TES application a viable option in comfort cooling systems in commercial buildings in the Middle East for electrical demand reduction, load shifting and energy conservation.
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Sherwood, P. M. "The application of short-term forecasting techniques applied to the control of electrical load in an energy management scheme." Thesis, University of Strathclyde, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382459.
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Zhang, Fan. "Thermal Comfort and Cognitive Performance Under Peak Demand Air-conditioning Management Strategies." Thesis, The University of Sydney, 2016. http://hdl.handle.net/2123/15651.
Full textAbstract:
This research focuses on university students’ thermal comfort and cognitive performance during direct load control (DLC) events in summer heat-waves. The specific indoor thermal environments resulting from three off cycle fractions, two cycling periods, two cooling setpoint temperatures, two different building envelope thermal performance conditions, and two ventilation rates were simulated within an EnergyPlus model of a university lecture theatre located in Sydney. Eight representative cases were selected from 48 simulations for examination using human subjects in a climate chamber. Fifty-six subjects in two separate experiments were exposed to three DLC conditions and one control condition. During the experimental periods, thermal comfort surveys and online cognitive performance tests were completed by the subjects. All the eight conditions yielded an average thermal acceptability of higher than the normative 80% limit. Subjects’ thermal comfort zone during DLC events was wider than predicted by ASHRAE’s PMV/PPD model. ASHRAE 55-2013 is overly conservative in defining the limits for temperature cycles, ramps and drifts. Analysis of cognitive performance tests confirmed that simpler cognitive tasks are less susceptible to temperature effects than more complex ones. In contrast with the prevailing belief about a single optimum temperature or thermal sensation for maximum performance, the present results indicated that the effects of thermal variations followed an extended-U relationship, with cognitive performance being stable across a relatively broad range of indoor temperatures. Results from this study reveal that as long as the DLC algorithms are judiciously designed and tailored to the specific building physics and occupancy conditions, DLC events can be readily accepted by university students without incurring thermal discomfort or performance decrements.
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Brodén, Daniel. "Analysis of Demand Response Solutions for Congestion Management in Distribution Networks." Thesis, KTH, Industriella informations- och styrsystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-138575.
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According to the 20-20-20 targets set by the European Union, 50 percent of the Swedish electricity share is to be provided by renewable energy sources by 2020. The Smart Grid Gotland (SGG) project has emerged as a response to this target. The project aims at demonstrating a proof of concept on how smart grid solutions can be used to integrate large quantities of renewable energy sources in an existing network. The outcomes of the project are intended to pave the way for future renewable energy integration projects in Sweden. The Thesis focuses on one of the technical objectives of the SGG project, i.e. to increase the hosting capacity of wind power on Gotland from 195 MW to 200 MW by using Demand-Response (DR) from households and industries. DR consist of shifting peak-loads to peakproduction hours. The integration of additional wind power causes a risk of exceeding the transmission capacity of the power export cable between Gotland and the Swedish mainland. The approach considered for this Thesis is to use an Ancillary Service (AS) toolbox scheme based on multi-agent systems. The AS toolbox consist of flexibility tools such as DR on long-term, short-term, a battery energy storage system and a wind curtailment scheme. The DR activity includes space heating and domestic hot water consumption from detached houses on Gotland. The simulation results indicate that 1900 household participants are sufficient to balance the additional 5 MW for worst case scenarios. Furthermore, it is shown that the DR participation from industries contributes in some cases to a reduction of 700 household participants. The findings helped conclude that using an AS toolbox solution on Gotland is fully possible from a technical perspective. However, barriers that stand against its realisation are of economical nature and need to be investigated in future studies.
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Alcázar, Ortega Manuel. "Evaluation and Assessment of New Demand Response Products based on the use of Flexibility in Industrial Processes: Application to the Food Industry." Doctoral thesis, Universitat Politècnica de València, 2011. http://hdl.handle.net/10251/10078.
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En el marco de un mercado de la electricidad con precios cada vez más altos y donde la participación de fuentes renovables de generación está jugando un papel cada vez más importante, esta tesis supone un enfoque innovador hacia la participación de recursos de demanda en mercados de operación, prestando una atención especial a segmentos industriales como el sector alimentario con un consumo energético intensivo.
En primer lugar, esta tesis describe detalladamente la situación actual de los programas de respuesta de la demanda que existen en diferentes partes del mundo. Este estudio permite concluir que los consumidores no han sido tenidos en cuenta suficientemente en la fase de diseño de los programas existentes, lo que ha provocado la infrautilización de recursos de demanda que, actualmente, permanecen sin explorar. Por otro lado, los consumidores no son conscientes del valor que su flexibilidad podría tener para el sistema eléctrico en su conjunto, ignorando que puedan existir otros agentes dispuestos a pagarles a cambio de reducir sus cargas en períodos determinados. Como resultado, esta tesis desarrolla una nueva metodología para explorar y valorar nuevos mecanismos de respuesta de la demanda donde el punto de vista de consumidores, operadores de red y cualquier otro agente interesado pueda ser tenido en cuenta. Esta metodología, basada en la evaluación y análisis detallado de los procesos, proporciona a los consumidores las herramientas adecuadas para evaluar su capacidad para reaccionar al precio de la electricidad, lo que permitiría al regulador poner en valor el beneficio social de dicha flexibilidad si pudiera ser utilizada en mercados de operación, ayudándole a definir los programas necesarios para utilizar de forma adecuada el potencial identificado por los consumidores.
La metodología desarrollada en esta tesis ha sido aplicada satisfactoriamente al sub-segmento de la industria cárnica, por lo que varias fábricas pertenecientes a este segmento han sido estudiadas en detalle. En concreto, la factibilidad de las acciones
propuestas ha sido probada y validada satisfactoriamente en una fábrica dedicada a la
producción de jamón curado en España, en la que se han evaluado diferentes
estrategias de flexibilidad.
Finalmente, se ha realizado una evaluación económica de la rentabilidad de la
aplicación de las acciones de flexibilidad propuestas tanto para el consumidor como
para el sistema eléctrico en su conjunto, donde se han considerado los precios reales
de los mercados de operación en España, aun cuando los consumidores no puedan
participar realmente en dichos mercados en la actualidad.<br>Alcázar Ortega, M. (2011). Evaluation and Assessment of New Demand Response Products based on the use of Flexibility in Industrial Processes: Application to the Food Industry [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10078<br>Palancia
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Ihbal, Abdel-Baset M. I. "Investigation of Energy Demand Modeling and Management for Local Communities. Investigation of the electricity demand modeling and management including consumption behaviour, dynamic tariffs, and use of renewable energy." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/5678.
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Various forecasting tools, based on historical data, exist for planners of national networks that are very effective in planning national interventions to ensure energy security, and meet carbon obligations over the long term. However, at a local community level, where energy demand patterns may significantly differ from the national picture, planners would be unable to justify local and more appropriate intervention due to the lack of appropriate planning tools.
In this research, a new methodology is presented that initially creates a virtual community of households in a small community based on a survey of a similar community, and then predicts the energy behaviour of each household, and hence of the community. It is based on a combination of the statistical data, and a questionnaire survey. The methodology therefore enables realistic predictions and can help local planners decide on measures such as embedding renewable energy and demand management.
Using the methodology developed, a study has been carried out in order to understand the patterns of electricity consumption within UK households. The methodology developed in this study has been used to investigate the incentives currently available to consumers to see if it would be possible to shift some of the load from peak hours. Furthermore, the possibility of using renewable energy (RE) at community level is also studied and the results presented. Real time pricing information was identified as a barrier to understanding the effectiveness of various incentives and interventions. A new pricing criteria has therefore been developed to help developers and planners of local communities to understand the cost of intervention. Conclusions have been drawn from the work. Finally, suggestions for future work have been presented.<br>Libyan government
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Rios, Silva Fredy Hernan [Verfasser], and H. [Akademischer Betreuer] Schmeck. "Stigmergy-based Load Scheduling in a Demand Side Management Context / Fredy Hernan Rios Silva. Betreuer: H. Schmeck." Karlsruhe : KIT-Bibliothek, 2016. http://d-nb.info/1104840847/34.
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Joo, Jhi-Young. "Adaptive Load Management: Multi-Layered And Multi-Temporal Optimization Of The Demand Side In Electric Energy Systems." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/307.
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Well-designed demand response is expected to play a vital role in operatingpower systems by reducing economic and environmental costs. However,the current system is operated without much information on the benefits ofend-users, especially the small ones, who use electricity. This thesis proposes aframework of operating power systems with demand models including the diversityof end-users’ benefits, namely adaptive load management (ALM). Sincethere are a large number of end-users having different preferences and conditionsin energy consumption, the information on the end-users’ benefits needsto be aggregated at the system level. This leads us to model the system ina multi-layered way, including end-users, load serving entities, and a systemoperator. On the other hand, the information of the end-users’ benefits can beuncertain even to the end-users themselves ahead of time. This information isdiscovered incrementally as the actual consumption approaches and occurs. Forthis reason ALM requires a multi-temporal model of a system operation andend-users’ benefits within. Due to the different levels of uncertainty along thedecision-making time horizons, the risks from the uncertainty of informationon both the system and the end-users need to be managed. The methodologyof ALM is based on Lagrange dual decomposition that utilizes interactive communicationbetween the system, load serving entities, and end-users. We showthat under certain conditions, a power system with a large number of end-userscan balance at its optimum efficiently over the horizon of a day ahead of operationto near real time. Numerical examples include designing ALM for theright types of loads over different time horizons, and balancing a system with a large number of different loads on a congested network. We conclude thatwith the right information exchange by each entity in the system over differenttime horizons, a power system can reach its optimum including a variety ofend-users’ preferences and their values of consuming electricity.
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Rios, S. Fredy H. [Verfasser], and Hartmut [Akademischer Betreuer] Schmeck. "Stigmergy-based Load Scheduling in a Demand Side Management Context / Fredy Hernan Rios Silva. Betreuer: H. Schmeck." Karlsruhe : KIT-Bibliothek, 2016. http://nbn-resolving.de/urn:nbn:de:swb:90-558013.
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Rios, S. Fredy H. [Verfasser], and H. [Akademischer Betreuer] Schmeck. "Stigmergy-based Load Scheduling in a Demand Side Management Context / Fredy Hernan Rios Silva. Betreuer: H. Schmeck." Karlsruhe : KIT-Bibliothek, 2016. http://d-nb.info/1104840847/34.
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Ihbal, Abdel-Baset Mostafa Imbarek. "Investigation of energy demand modeling and management for local communities : investigation of the electricity demand modeling and management including consumption behaviour, dynamic tariffs, and use of renewable energy." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/5678.
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Various forecasting tools, based on historical data, exist for planners of national networks that are very effective in planning national interventions to ensure energy security, and meet carbon obligations over the long term. However, at a local community level, where energy demand patterns may significantly differ from the national picture, planners would be unable to justify local and more appropriate intervention due to the lack of appropriate planning tools. In this research, a new methodology is presented that initially creates a virtual community of households in a small community based on a survey of a similar community, and then predicts the energy behaviour of each household, and hence of the community. It is based on a combination of the statistical data, and a questionnaire survey. The methodology therefore enables realistic predictions and can help local planners decide on measures such as embedding renewable energy and demand management. Using the methodology developed, a study has been carried out in order to understand the patterns of electricity consumption within UK households. The methodology developed in this study has been used to investigate the incentives currently available to consumers to see if it would be possible to shift some of the load from peak hours. Furthermore, the possibility of using renewable energy (RE) at community level is also studied and the results presented. Real time pricing information was identified as a barrier to understanding the effectiveness of various incentives and interventions. A new pricing criteria has therefore been developed to help developers and planners of local communities to understand the cost of intervention. Conclusions have been drawn from the work. Finally, suggestions for future work have been presented.
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Li, Chenxi. "Advanced Load Management Techniques with the Inclusion of Distributed Energy Resources in a Smart Grid." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/17855.
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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.
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Dalgleish, Abraham Zacharias. "The development, implementation and performance evaluation of an innovative residential load management system / Abraham Zacharias Dalgleish." Thesis, North-West University, 2009. http://hdl.handle.net/10394/4003.
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The power utility of South Africa, Eskom, expected a supply shortfall of approximately 400MW between February and August 2006 in the Western Cape. The peak of the crisis was in mid-winter (June to August). This shortfall was firstly caused when Eskom experienced a breakdown on the one of the two nuclear supply units. Secondly the remaining of the Koeberg units was due for refuelling which necessitated the shut-down of the reactor. No electricity was therefore generated by both units. It was clear that if electricity demand was not effectively curbed, extensive power outages would be experienced; which was the case.
Various demand side management (DSM) programmes were rolled-out to address lighting, switching from electricity to gas for cooking, compensating customers that could generate own electricity, energy efficiency and load curtailment in the education, commercial, and industrial sectors, as well as an extensive energy efficiency campaign. It is shown in this study that the most constrained periods were expected during the evening peak and was a consequence of electricity consumption in the residential sector. The residential evening peak is very prominent and primarily caused by water heating, cooking, space heating, lighting, and appliances. None of the mentioned programmes focused on the residential evening peak. Traditional residential DSM technologies were almost impossible to implement in the short timeframe because there are more than 625,000 residences in the Western Cape. A solution was looked for that could be implemented in a relatively short period to address the residential evening peak.
This study focuses on the development, implementation, and performance evaluation of Power Alert – An innovative residential load management system. The need for such a system was identified and the expected impact was determined through a feasibility study. Power Alert was designed to be a link between Eskom and the public through the national television broadcaster. It was operational during the whole Western Cape winter. A methodology to determine the impact of Power Alert was also developed to demonstrate the actual load reductions. The methodology was applied and Power Alert demonstrated that it was a valuable residential load management tool that could be designed and implemented in a much shorter time than conventional residential DSM measures.<br>Thesis (Ph.D. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2010.
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Ryckebusch, Gaëlle. "Analysis of Demand-Response Participation Strategies for Congestion Management in an Island Distribution Network." Thesis, KTH, Industriella informations- och styrsystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-169220.
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The Master Thesis is part of the Smart Grid Gotlandproject. This project aims at implementing smart grid solutionson the island of Gotland in order to be able to efficientlyintegrate large quantities of renewable energy production.In situations of high wind power production and lowconsumption, energy export problems may occur betweenGotland and the mainland. A novel approach to manageanticipated congestions, compared to traditional gridreinforcements, consists of using flexibility from demandresponse(DR) resources. However, such an approach presentschallenges as it requires both technical and economic considerations.This Master Thesis proposes and analyses twomarket-based strategies applied to detached houses for dayaheadcongestion management. The strategies are implementedin an Ancillary Service toolbox developed in theMATLAB programming environment.The first strategy involves using a dynamic network tariffwhile the second uses spot price optimization. Simulationsare performed for seasonal worst-case congestion scenarioswhile satisfying comfort and economic constraints ofthe DR participants. A sensitivity analysis is carried out toassess the impact of different spot price profiles and windpower production prognosis errors on the results.Results show that congestions are managed with a feasiblenumber of participants, but that their savings are negligiblefor both strategies (between 2 and 40 SEK/participant).Moreover, using a dynamic network tariff strategy impliesa DSO cost in the range of 1700-89000 SEK. These resultsapply for a 3-days congestion period, which is estimated tooccur 5-6 times a year if the maximum hosting capacity isincreased by 5 MW.To conclude, an AS toolbox with economic constraintsis feasible for Gotland conditions with a reasonable numberof DR participants. However, the simple cost-benefitanalysis that was carried out showed that the AS toolboxapproach was still much more costly than traditional gridreinforcement.
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Rana, Rohit Singh. "Multi-Dimensional Energy Consumption Scheduling for Event Based Demand Response." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39854.
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The global energy demand in residential sector is increasing steadily every year due to advancement in technologies. The present electricity grid is designed to support peak demand rather than Peak to Average (PAR) demand. Utilities are investigating the residential Demand Response (DR) to lower the (PAR) ratio and eliminate the need of building new power infrastructure. This requires Home Energy Management System (HEMS) at grid edge to manage and control the energy demand. In this thesis, we presented an MDPSO based DR enabled HEMS model for optimal allocation of energy resources in a smart dwelling. The algorithm is designed to lower peak energy demand as well as encourage the active participation of customers by offering a reward to comply with DR request. We categorized appliances as elastic non-deferrable loads and inelastic deferrable loads based on their DR potential and operating characteristics. The scheduling of elastic and inelastic class of appliances is performed separately using canonical and binary version of PSO given how we expressed out load categories. We performed use case simulation to validate the performance of MDPSO for combination of different tariffs: Time of Use (TOU), TOU and Critical peak rebate signal (CPR), TOU and upper demand limit. Simulation results show that algorithm can reduce the electricity cost in range of 28% to 7% under increasing comfort conditions in response to TOU prices and Peak demand reduction of about 24% under TOU pricing and medium comfort conditions for single household. Under CPR DR requests, with respect to TOU pricing, there is effectively no change in the peak under the minimum comfort scenario. Furthermore, algorithm is able to suppress the peak upto 25% under combination of TOU and hard constraint on maximum power withdrawn from grid with no change in the electricity cost. Scheduling of multiple houses under TOU pricing results in peak reduction of 7 % as compared to baseline state. Under combination of TOU and CPR the aggregate peak energy demand of multiple households during DR activation time intervals is reduced by 32 %. The algorithm can suppress the peak demand by 27% under TOU and hard constraint on maximum power withdrawn from grid by multiple houses.
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Skog, Nestorovic Benjamin, and Douglas Lindén. "Techno-economic analysis of Battery Energy Storage Systems and Demand Side Management for peak load shaving in Swedish industries." Thesis, KTH, Kraft- och värmeteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-277824.
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The Swedish electrical grid has historically been robust and reliable, but with increased electrification in numerous sectors, out-phasing of nuclear power and a high market diffusion of wind power, the system is now facing challenges. The rotational energy in the system is expected to decrease as a result of higher shares of intermittent energy sources, which can affect the stability of the grid frequency negatively. To manage increased frequency drops, the new Fast Frequency Reserve (FFR) market will be implemented by June 2020 in the Nordic power system. Simultaneously, it is expected that the demand of electricity will increase significantly in the transport and industry sectors in the coming years. Several DSOs already today indicate challenges with capacity and power security and have or will implement power tariffs as an economic incentive to prevent these problems. For energy intensive customers, such as industries, it will become important to reduce power peaks to avoid high grid fees. Several peak load shaving strategies can be utilized by industries to reduce their power peaks and thus the power tariff. The aim of this study is to economically analyze peak load shaving for Swedish industries. This is done using Li-Ion BESS and DSM, and to maximize the utilization of the BESS by including energy arbitrage and FFR market participation into the analysis. Firstly, a literature review is conducted within the topics of peak load shaving strategies, energy arbitrage and ancillary services. Secondly, data is gathered in collaboration with WSP Systems – Energy, the initiators of the project, to conduct case studies on two different industries. These cases are simulated in the modeling software SAM, for technical analysis, and then economically evaluated with NPV. Also, nine scenarios are created for the emerging FFR market concerning the number of activations per year and the compensation price per activation. The results from the case studies indicate that peak load shaving of 1 – 3 % with BESS provides a positive NPV for both case industries. However, higher percentages result in negative NPVs when no additional revenue streams are included. When considering energy arbitrage, it is concluded that the additional revenues are neglectable for both industries. Participating in the FFR market provides similar trends in the results as before. The exception is valid for scenarios with high numbers of FFR activations and compensation prices, where positive NPVs for all levels of peak load shaving can be concluded. The peak load shaving strategy DSM is implemented for one of the industries, where efficiency measures are concluded to have the most impact on the economic evaluation. If all efficiency measures would be implemented, the electricity consumption would be reduced by 17 %. Additionally, the power peaks would be reduced with 18 % and result in a significantly more positive NPV than peak load shaving using BESS. A sensitivity analysis concerning BESS capital cost and power tariff price concludes that the BESS price has a strong relation to the NPV, where a BESS price reduction of 60 % results in an NPV increase of at least 100 %. BESS prices have decreased the past years and are expected to keep decreasing in the future. Hence, investments in BESS can become more profitable and attractive in the coming years. Finally, for future research, it is recommended to combine the methodology from this study together with a load forecasting method. This combined methodology could then be practically applied to case specific industries with high peak loads.<br>Det svenska elnätet har historiskt sett varit robust och pålitligt, men i takt med ökad elektrifiering i flera sektorer, utfasning av kärnkraft samt ökad mängd installerad vindkraft ställs nu systemet inför nya utmaningar. Bland annat förväntas rotationsenergin i systemet minska som ett resultat av högre andelar intermittenta energikällor i systemet. För att hantera detta kommer den nya Fast Frequency Reserve (FFR) marknaden finnas tillgänglig från och med juni 2020. Samtidigt förväntas även efterfrågan på el inom transport- och industrisektorn öka markant de kommande åren. Redan idag är effektbrist ett problem i vissa regioner, vilket kan komma att förvärras. Många nätägare ska eller har redan infört effekttariffer för utnyttjande av deras elnät, vilket är ett ekonomiskt incitament för att hantera effektproblematiken där kunder med en mer flexibel elkonsumtion kommer gynnas. För större elförbrukare, som exempelvis industrier, kan det bli ekonomiskt betydelsefullt att sänka sina effekttoppar och därmed undvika höga nätavgifter. För att minska effekttoppar finns ett flertal så kallade peak load shaving-strategier, som kan utnyttjas av industrier för att minska kostnaderna för effekttariffen. Syftet med denna studie är att analysera peak load shaving för svenska industrier, med hjälp av ett Li-Ion batterilagringssystem och efterfrågeflexibilitet, samt maximera utnyttjandet av batteriet genom att inkludera energiarbitrage och deltagande i FFR-marknaden i analysen. Ett första steg i arbetet är att utföra en litteraturstudie för de berörda områdena. I ett andra steg insamlas data tillsammans med WSP, initiativtagaren av projektet, för att kunna göra en fallstudie på två industrier. För dessa fallstudier undersöks de tekniska förutsättningarna för att implementera peak load shaving-strategier genom modellering i simuleringsprogrammet SAM. Sedan utreds de ekonomiska förutsättningarna för fallstudierna, där NPV används som ekonomiskt nyckeltal. Dessutom skapas nio scenarion för den kommande FFR-marknaden för att uppskatta kostnader och inkomster. Resultatet av fallstudien visar att 1 – 3 % kapade effekttoppar med batterilagring ger ett positivt NPV för båda industrierna. Över 3 % blir resultatet negativt utan ytterligare inkomstströmmar inkluderade. Energiarbitrage konstateras att bidra med marginella positiva fördelar. Vid inkludering av FFR-marknaden i analysen erhålls liknande trender i resultaten, bortsett från scenarion med relativt högt antal avrop och pris. I dessa fall blir även 4 – 10 % kapade effekttoppar ekonomiskt attraktiva. För en av industrierna utvärderas efterfrågeflexibilitet, där effektivisering av elkrävande processer har störst inflytande på resultatet. Vid implementering av samtliga effektiviseringsåtgärder skulle elkonsumtionen minska med 17 %. Dessutom minskar effekttopparna med 18 %, vilket resulterar i ett signifikant mer positivt NPV, jämfört med användningen av batterilager. En känslighetsanalys gällande batteripris och effekttariffer, konstaterade att batteripriset har en stark påverkan på NPV. Vid en batteriprisminskning på 60 % ökar NPV med minst 100 %. Därmed kan batteriinvesteringar bli mer gynnsamma och attraktiva om batteripriser fortsätter att falla, vilket flera prognoser indikerar. Slutligen rekommenderas framtida studier att kombinera metodiken från detta arbete med en prognostiseringsmetod för elanvändning i industrier. Denna kombinerade metod kan sedan praktiskt tillämpas på fallspecifika industrier med höga effekttoppar.
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Hare, Jeremy (Jeremy B. ). "Disaggregation of residential home energy via non-intrusive load monitoring for energy savings and targeted demand response." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117983.
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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2018.<br>Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018.<br>"June 2018." Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 59-61).<br>Residential energy disaggregation is a process by which the power usage of a home is broken down into the consumption of individual appliances. There are a number of different methods to perform energy disaggregation, from simulation models to installing "smart-plugs" at every outlet where an appliance is connected to the wall. Non-Intrusive Load Monitoring (NILM) is one such disaggregation option. NILM is widely recognized as one of the most cost-effective methods for gathering disaggregated energy data while maintaining a high level of accuracy. Although the technology has existed for many years, the adoption rate of NILM, and other devices that disaggregate energy, has been minimal. This thesis provides details on the potential benefits, both for the customer and utility provider, associated with furthering the adoption of NILM devices and obtaining the disaggregated appliance level energy-use. A broad overview of potential benefits is presented; however, the primary goal of this thesis will be to investigate two benefits of NILM in detail: overall household energy reduction and targeted demand response. First, installation of a NILM device can provide electricity customers information that allows them to become more aware of their energy consumption, and thereby, more energy efficient. A study was conducted that looked at the electricity consumption of 174 homes that were using a passive NILM device in their home. This NILM device provided immediate feedback on the power consumption for a portion of the home's appliances via smart-phone application. The homes reduced their monthly energy consumption by an average of 2.6 - 3.1% after the NILM installation. This was validated by a number of analysis methods returning similar results. Aligned with this benefit comes a recommendation for an incentive structure that can reduce the price paid by the consumer and develop a higher adoption rate of NILM devices. Second, the wide-spread adoption of NILM devices can provide electric utilities information to reduce carbon intensity via targeted demand response. There is a significant opportunity for utilities to engage their customers based on the time of use of detailed appliances. Multiple metrics are presented in this thesis to quantify the deferrable load opportunity of specific appliances and individual households. Utility operational cost savings and greater customer incentives can be linked to the use of these metrics.<br>by Jeremy Hare.<br>M.B.A.<br>S.M.
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Chatterjee, Arnab. "Optimization of mine ventilation fan speeds according to ventilation on demand and time of use tariff." Diss., University of Pretoria, 2014. http://hdl.handle.net/2263/45900.
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With the growing concerns about energy shortage and demand supply imbalance, demand side
management (DSM) activities has found its way into the mining industry. This study analyzes
the potential to save energy and energy-costs in underground mine ventilation networks, by
application of DSM techniques. Energy saving is achieved by optimally adjusting the speed
of the main fan to match the time-varying flow demand in the network, which is known as
ventilation on demand (VOD). Further cost saving is achieved by shifting load to off-peak
or standard times according to a time of use (TOU) tariff, i.e. finding the optimal mining
schedule.
The network is modelled using graph theory and Kirchhoff’s laws; which is used to form a
non-linear, constrained, optimization problem. The objective of this problem is formulated
to minimize the energy cost; and hence it is directly given as a function of the fan speed,
which is the control variable. As such, the operating point is found for every change in the
fan speed, by incorporating the fan laws and the system curve.
The problem is solved using the fmincon solver in Matlab’s optimization toolbox. The
model is analyzed for different scenarios, including varying the flow rate requirements and tariff structure. Although the results are preliminary and very case specific, the study suggests
that significant energy and energy-cost saving can be achieved in a financially viable
manner.<br>Dissertation (MEng)--University of Pretoria, 2014.<br>tm2015<br>Electrical, Electronic and Computer Engineering<br>MEng<br>Unrestricted
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Neusser, Lukas. "Bases teóricas e experimentais para o gerenciamento da demanda em prédios públicos de ensino: o caso da Universidade Federal de Santa Maria." Universidade Federal de Santa Maria, 2009. http://repositorio.ufsm.br/handle/1/8471.
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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.<br>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.
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Al-Hadban, Yehya. "Demand-side management in office buildings in Kuwait through an ice-storage assisted HVAC system with model predictive control." Thesis, Cranfield University, 2005. http://hdl.handle.net/1826/3885.
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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.
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Rodriguez, German Darío Rivas. "Decentralized Architecture for Load Balancing in District Heating Systems." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3329.
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Context. In forthcoming years, sustainability will lead the development of society. Implementation of innovative systems to make the world more sustainable is becoming one of the key points for science. Load balancing strategies aim to reduce economic and ecological cost of the heat production in district heating systems. Development of a decentralized solution lies in the objective of making the load balancing more accessible and attractive for the companies in charge of providing district-heating services. Objectives. This master thesis aims to find a new alternative for implementing decentralized load balancing in district heating systems. Methods. The development of this master thesis involved the review of the state-of-the-art on demand side management in district heating systems and power networks. It also implied the design of the architecture, creation of a software prototype and execution of a simulation of the system to measure the performance in terms of response time. Results. Decentralized demand side management algorithm and communication framework, software architecture description and analysis of the prototype simulation performance. Conclusions. The main conclusion is that it is possible to create a decentralized algorithm that performs load balancing without compromising the individuals’ privacy. It is possible to say that the algorithm shows good levels of performance not only from the system aggregated response time, but also from the individual performance, in terms of memory consumption and CPU consumption.<br>(+46) 709706206
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Richardson, Ian. "Integrated high-resolution modelling of domestic electricity demand and low voltage electricity distribution networks." Thesis, Loughborough University, 2011. https://dspace.lboro.ac.uk/2134/7968.
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Assessing the impact of domestic low-carbon technologies on the electricity distribution network requires a detailed insight into the operation of networks and the power demands of consumers. When used on a wide-scale, low-carbon technologies, including domestic scale micro-generation, heat pumps, electric vehicles and flexible demand, will change the nature of domestic electricity use. In providing a basis for the quantification of the impact upon distribution networks, this thesis details the construction and use of a high-resolution integrated model that simulates both existing domestic electricity use and low voltage distribution networks. Electricity demand is modelled at the level of individual household appliances and is based upon surveyed occupant time-use data. This approach results in a simulation that exhibits realistic time-variant demand characteristics, in both individual dwellings, as well as, groups of dwellings together. Validation is performed against real domestic electricity use data, measured for this purpose, from dwellings in Loughborough in the East Midlands, UK. The low voltage distribution network is modelled using real network data, and the output of its simulation is validated against measured network voltages and power demands. The integrated model provides a highly detailed insight into the operation of networks at a one-minute resolution. This integrated model is the main output of this research, alongside published articles and a freely downloadable software implementation of the demand model.
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Roe, Curtis Aaron. "Impacts of automated residential energy management technology on primary energy source utilization." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/45865.
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The objective of the proposed research is to analyze automated residential energy management technology using primary energy source utilization. A residential energy management system (REMS) is an amalgamation of hardware and software that performs residential energy usage monitoring, planning, and control. Primary energy source utilization quantifies power system levels impacts on power generation cost, fuel utilization, and environmental air pollution; based on power system generating constraints and electric load.
Automated residential energy management technology performance is quantified through a physically-based REMS simulation. This simulation includes individual appliance operation and accounts for consumer behavior by stochastically varying appliance usage and repeating multiple simulation iterations for each simulated scenario. The effect of the automated REMS under varying levels of control will be considered.
Aggregate REMS power system impacts are quantified using primary energy source utilization. This analysis uses a probabilistic economic dispatch algorithm. The economic dispatch algorithm quantifies: fuel usage and subsequent environmental air pollution (EAP) generated; based on power system generating constraints and electric load (no transmission constraints are considered).
The analysis will comprehensively explore multiple residential energy management options to achieve demand response. The physically-based REMS simulation will consider the following control options: programmable thermostat, direct load control, smart appliance scheduling, and smart appliance scheduling with a stationary battery. The ability to compare multiple automated residential energy management technology options on an equal basis will guide utility technology investment strategies.
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Van, der Bijl Johannes. "Sustainable DSM on deep mine refrigeration systems : a novel approach / J. van der Bijl." Thesis, North-West University, 2007. http://hdl.handle.net/10394/1940.
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Kini, Roshan Laxman. "Development and Implementation of Control Strategies for Effective Management of Distributed Energy Resources." University of Toledo / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1576158141410245.
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Yaser, Hussnain A. "Novel System Design For Residential Heating And Cooling Load Shift Using PCM Filled Plate Heat Exchanger And Auxiliaries For Economic Benefit And Demand Side Management." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1397234246.
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Lambert, Quentin. "Business Models for an Aggregator : Is an Aggregator economically sustainable on Gotland?" Thesis, KTH, Industriella informations- och styrsystem, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-98482.
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Under the determined impulse of the European Union to limit the environmental impact of energy-related services, the electricity sector will face several challenges in coming years. Integrating renewable energy sources in the distribution networks is certainly one of the most urging issues to be tackled with. The current grid and production structure cannot absorb the high penetration shares anticipated for 2020 without putting at risk the entire system. The innovative concept of smart grid offers promising solutions and interesting implementation possibilities. The objective of the thesis is to specifically study the technical and economic benefits that the creation of an aggregator on the Swedish island of Gotland would imply. Comparing Gotland's power system characteristics to the broad variety of solutions offered by demand side management, wind power integration enhancement by demand response appeared particularly suited. A business case, specifically oriented towards the minimisation of transmission losses by adapting the electric heat load of private households to the local wind production was designed. Numerical simulations have been conducted, evaluating the technical and economic outcomes, along with the environmental benets, under the current conditions on Gotland. Sensitivity analyses were also performed to determine the key parameters for a successful implementation. A prospective scenario for 2020, with the addition of electric vehicles, has finally been simulated to estimate the long term profitability of an aggregator on the island. The simulation results indicate that despite patent technical benefits for the distribution network, the studied service would not be profitable in the current situation on Gotland. This, because the transmission losses through the HVDC-cable concern limited amounts of power that are purchased on a market characterized by relatively cheap prices and low volatility. Besides, the high fixed costs the aggregator has to face to install technical equipment in every household constitutes another barrier to its setting up.
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Ouart, Sebastian. "Lastmanagement bei Haushaltskunden." Doctoral thesis, Universitätsbibliothek Chemnitz, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-218777.
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Vor dem Hintergrund der Transformation der Energiewirtschaft wird in der Arbeit untersucht, wie eine prämienbasierte Nachfragesteuerung im Bereich der Haushaltskunden ausgestaltet werden kann, welche sowohl einen Beitrag zur Gewährleistung der Versorgungssicherheit leistet als auch für die beteiligten Akteure wirtschaftlich attraktiv ist. Zur Beantwortung der Fragestellung werden im theoretischen Teil der Arbeit die relevanten Aspekte der Stromwirtschaft, die Grundlagen der Nachfragesteuerung, die Preiselastizität der Nachfrage, die bestehenden Verfahren zur Initiierung von Lastveränderungen sowie Ansätze zur Ermittlung des Werts von der Versorgung mit elektrischer Leistung systematisch beschrieben. Aufbauend auf diesen theoretischen Grundlagen werden anschließend die konzeptionellen Anforderungen für die Ausgestaltung der Nachfragesteuerung erarbeitet, d. h. die Rahmenbedingungen analysiert, darauf aufbauend die Spezifikation für den Einsatz der Nachfragesteuerung vorgenommen und Vorgaben für die Produktgestaltung gemacht.
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Brégère, Margaux. "Stochastic bandit algorithms for demand side management Simulating Tariff Impact in Electrical Energy Consumption Profiles with Conditional Variational Autoencoders Online Hierarchical Forecasting for Power Consumption Data Target Tracking for Contextual Bandits : Application to Demand Side Management." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASM022.
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L'électricité se stockant difficilement à grande échelle, l'équilibre entre la production et la consommation doit être rigoureusement maintenu. Une gestion par anticipation de la demande se complexifie avec l'intégration au mix de production des énergies renouvelables intermittentes. Parallèlement, le déploiement des compteurs communicants permet d'envisager un pilotage dynamique de la consommation électrique. Plus concrètement, l'envoi de signaux - tels que des changements du prix de l'électricité – permettrait d'inciter les usagers à moduler leur consommation afin qu'elle s'ajuste au mieux à la production d'électricité. Les algorithmes choisissant ces signaux devront apprendre la réaction des consommateurs face aux envois tout en les optimisant (compromis exploration-exploitation). Notre approche, fondée sur la théorie des bandits, a permis de formaliser ce problème d'apprentissage séquentiel et de proposer un premier algorithme pour piloter la demande électrique d'une population homogène de consommateurs. Une borne supérieure d'ordre T⅔ a été obtenue sur le regret de cet algorithme. Des expériences réalisées sur des données de consommation de foyers soumis à des changements dynamiques du prix de l'électricité illustrent ce résultat théorique. Un jeu de données en « information complète » étant nécessaire pour tester un algorithme de bandits, un simulateur de données de consommation fondé sur les auto-encodeurs variationnels a ensuite été construit. Afin de s'affranchir de l'hypothèse d'homogénéité de la population, une approche pour segmenter les foyers en fonction de leurs habitudes de consommation est aussi proposée. Ces différents travaux sont finalement combinés pour proposer et tester des algorithmes de bandits pour un pilotage personnalisé de la consommation électrique<br>As electricity is hard to store, the balance between production and consumption must be strictly maintained. With the integration of intermittent renewable energies into the production mix, the management of the balance becomes complex. At the same time, the deployment of smart meters suggests demand response. More precisely, sending signals - such as changes in the price of electricity - would encourage users to modulate their consumption according to the production of electricity. The algorithms used to choose these signals have to learn consumer reactions and, in the same time, to optimize them (exploration-exploration trade-off). Our approach is based on bandit theory and formalizes this sequential learning problem. We propose a first algorithm to control the electrical demand of a homogeneous population of consumers and offer T⅔ upper bound on its regret. Experiments on a real data set in which price incentives were offered illustrate these theoretical results. As a “full information” dataset is required to test bandit algorithms, a consumption data generator based on variational autoencoders is built. In order to drop the assumption of the population homogeneity, we propose an approach to cluster households according to their consumption profile. These different works are finally combined to propose and test a bandit algorithm for personalized demand side management
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Du, Liang. "Advanced classification and identification of plugged-in electric loads." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50321.
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The total electricity consumption of plugged-in electric loads (PELs) currently accounts for more usage than any other single end-use service in residential and commercial buildings. Compared with other categories of electric loads, PELs possess significant potential to be efficiently controlled and managed in buildings. Therefore, accurate and reliable PEL identification methods that are used to collect identity and performance information are desired for many purposes. However, few existing electric load identification methods are designed for PELs to handle unique challenges such as the diversity within each type of PEL and similarity between different types of PELs equipped by similar front-end power supply units.
The objective of this dissertation is to develop non-intrusive, accurate, robust, and applicable PEL identification algorithms utilizing voltage and current measurements. Based on the literature review of almost all existing features that describe electric loads and five types of existing methods for electric load identification, a two-level framework for PELs classification and identification is proposed.
First, the supervised self-organizing map (SSOM) is adopted to classify a large number of PELs of different models and brands into several groups by their inherent similarities. Therefore, PELs with similar front-end power supply units or characteristics fall into the same group. The partitioned groups are verified by their power supply unit topology. That is, different groups should have different topologies. This dissertation proposes a novel combination of the SSOM framework and the Bayesian framework. Such a hybrid identifier can provide the probability of an unknown PEL belonging to a specific type of load.
Within each classified group by the SSOM, both static and dynamic methods are proposed to distinguish PELs with similar characteristics. Static methods extract steady-state features from the voltage and current waveforms to train different computational intelligence algorithms such as the SSOM itself and the support vector machine (SVM). An unknown PEL is then presented to the trained algorithm for identification. In contrast to static methods, dynamic methods take into consideration the dynamics of long-term (minutes instead of milliseconds) waveforms of PELs and extract elements such as spikes, oscillations, steady-state operations, as well as similarly repeated patterns.
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Dickert, Jörg. "Synthese von Zeitreihen elektrischer Lasten basierend auf technischen und sozialen Kennzahlen." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-204629.
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Kenntnisse über das prinzipielle Verhalten der Lasten und deren Benutzung durch die Endabnehmer sind im Wesentlichen vorhanden. Viele der aktuell notwendigen Untersuchungen benötigen jedoch Zeitreihen elektrischer Lasten, sogenannte Lastgänge. Mit der Synthese von Zeitreihen elektrischer Lasten können unter Berücksichtigung verschiedenster Anforderungen Lastgänge aufgebaut werden, wobei in dieser Arbeit der Fokus auf Haushaltsabnehmer liegt. Wichtige Eingangsdaten für die Lastgangsynthese sind die technischen Kenngrößen der elektrischen Geräte und die sozialen Kennzahlen zur Benutzung der Geräte durch die Endabnehmer. Anhand dieser Eingangsdaten wird die Lastgangsynthese durchgeführt und werden Anwendungsbeispiele dargestellt. Die Entwicklung von klassischen Versorgungsnetzen hin zu aktiven Verteilungsnetzen ist bedingt durch neue Verbraucher, wie Wärmepumpen, Elektroautos, sowie vielen dezentralen Erzeugungsanlagen. Speziell die fluktuierende Einspeisung durch Photovoltaik-Anlagen ist Anlass zur Forderung nach einem Verbrauchs- und Lastmanagement. Mit dem Verbrauchsmanagement wird die Last an die Einspeisung angepasst und das Lastmanagement berücksichtigt zusätzlich die Versorgungssituation des Netzes. Für die Lastgangsynthese werden die Haushaltsgeräte in fünf Geräteklassen unterteilt, für die spezifische Kennzahlen aus technischer und sozialer Sicht angegeben werden. Diese Kennzahlen sind Leistung pro Gerät oder Energieverbrauch pro Nutzung sowie Ausstattungsgrade, Benutzungshäufigkeiten und Zeiten für das Ein- und Ausschalten der Geräte. Damit wird ein neuer Ansatz gewählt, welcher nicht mehr auf die detaillierte Beschreibung des Bewohnerverhaltens beruht, da die Datenbereitstellung dafür äußerst schwierig war und ist. Vorzugsweise in Niederspannungsnetzen sind mit synthetischen Zeitreihen umfangreiche und umfassende Untersuchungen realisierbar. Es gibt verschiedenste Möglichkeiten, die Zeitreihen zusammenzustellen. Mit Lastgängen je Außenleiter können beispielsweise unsymmetrische Zustände der Netze analysiert werden. Zudem können auch Lastgänge für Geräte bzw. Gerätegruppen erstellt werden, welche für Potenzialanalysen des Verbrauchsmanagement essenziell sind. Der wesentliche Unterschied besteht darin, dass viele Berechnungen nicht mehr auf deterministische Extremwerte beruhen, sondern die stochastischen Eigenschaften der Endabnehmer mit den resultierenden Lastgängen berücksichtigt werden<br>Distributed generation and novel loads such as electric vehicles and heat pumps require the development towards active distribution networks. Load curves are needed for the appropriate design process. This thesis presents a feasible and expandable synthesis of load curves, which is performed exemplary on residential customers with a period under review of 1 year and time steps of as little as 30 s. The data is collected for up-to-date appliances and current statics examining the way of life. The main focus lies on the input data for the synthesis and distinguishes between technical and social factors. Some thirty home appliances have been analyzed and are classified into five appliance classes by incorporating switching operations and power consumptions. The active power is the key figure for the technical perspective and the data is derived from manufacturer information. For the social perspective six different customer types are defined. They differ in sizes of household and housekeeping. The social key figures are appliance penetration rate and depending on the appliance class the turn-on time, turn-off time, operating duration or cycle duration. The elaborated two-stage synthesis is efficiently implemented in Matlab®. First, artificial load curves are created for each appliance of the households under consideration of the appliance class. In the second step, the individual load curves of the appliances are combined to load curves per line conductor. The algorithms have been validated in the implementation process by retracing the input data in the load curves. Also, the feasibility of the results is shown by comparing the key figures maximum load and power consumption to data in literature. The generated load curves allow for unsymmetrical calculations of distribution systems and can be used for probabilistic investigations of the charging of electric vehicles, the sizing of thermal storage combined with heat pumps or the integration of battery storage systems. A main advantage is the possibility to estimate the likelihood of operating conditions. The enhancement to further appliances and the changeability of the input data allows for versatile further possible investigations
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Rama, Curiel José Adrian. "Analysis of potential impact of direct load control of AC units in the Indian State of Karnataka." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264348.
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Demand Side Management (DSM) is a term coined to describe the control of demand to optimize energy usage in a way beneficial to both users and utilities. There are different technologies and policies designed for DSM, and one of them is Direct Load Control (DLC) which refers to a utility directly controlling demand. In this thesis, an analysis of DLC for air conditioning units during summer in the Indian state of Karnataka is carried out. A new control mechanism is proposed, based on the local generation capacity, which seems to reduce until the monsoon season arrives, as the lack of rain reduces water levels in hydro power plants. The direct load control of ACs using this mechanism allows for 0.88% energy savings in a state where only around 5% of all households seem to have AC units and electricity is available for only 37% of the population. The mentioned savings could have significant economic impacts for both users and utilities, reduce the fossil-based energy consumption and/or improve issues such as blackouts and the lack of capacity to cover peak loads. Continuous improvements in both energy access and the economic conditions of the state will lead to a larger number of AC’s installed, meaning that a mechanism that reduces AC consumption could be of great utility for all stakeholders of the electricity sector.<br>Styrning av Efterfrågan (från Demand Side Management, DSM) är ett begrepp som myntats för att beskriva konsumtionskontroll för att optimera energianvändning på ett sätt som är fördelaktigt för både användare och samhällsservice. Det finns olika tekniker och taktiker utformade för DSM, och en av dem är Direkt Belastningskontroll (från Direct Load Control, DLC), vilket är ett verktyg för att direkt kontrollera efterfrågan. I denna avhandling genomförs en analys av DLC för luftkonditioneringsenheter under sommaren i den indiska delstaten Karnataka. En ny kontrollmekanism föreslås baserat på den lokala produktionskapaciteten, som verkar minska fram tills monsunsäsongen, eftersom bristen på regn minskar vattennivån i vattenkraftverk. Den direkta belastningskontrollen hos luftkonditioneringsenheter med denna mekanism möjliggör en energibesparing på 0,88% i ett stadium där endast cirka 5% av alla hushåll tycks ha luftkonditionering och elektricitet är tillgängligt för endast 37% av befolkningen. De nämnda besparingarna kan ha betydande ekonomiska effekter för både användare och samhällsservice, minska den fossilbaserade energiförbrukningen och/eller förbättra problem som strömavbrott och brist på kapacitet för att täcka toppbelastningar. Ständiga förbättringar av både energitillgång och de ekonomiska förhållandena i staten kommer att leda till att ett större antal luftkonditioneringsenheter installeras, vilket innebär att en mekanism som minskar konsumtionen hos luftkonditioneringsenheterna kan vara till stor nytta för alla intressenter i elsektorn.
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Baniasadi, Ali. "Application of heat pumps and thermal storage systems for improved control and performance of microgrids." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2020. https://ro.ecu.edu.au/theses/2316.
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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.
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Geyser, Martinus Fredrik. "A new integrated procedure for energy audits and analyses of buildings / M.F. Geyser." Thesis, North-West University, 2003. http://hdl.handle.net/10394/414.
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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.<br>Thesis (Ph.D. (Mechanical Engineering))--North-West University, Potchefstroom Campus, 2004.
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Cortez, Victor Hugo Neto. "Gerenciamento pelo lado da demanda em sistemas elétricos industriais utilizando algoritmos genéticos." Universidade Federal de Juiz de Fora (UFJF), 2017. https://repositorio.ufjf.br/jspui/handle/ufjf/5947.
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Previous issue date: 2017<br>Grandes indústrias e parques industriais estão entre os maiores consumidores de energia de um país e sendo assim é interessante do ponto de vista do sistema elétrico fazer com que a energia utilizada por estes consumidores seja consumida de forma eficiente. Também é do interesse dos consumidores buscar a otimização do uso da energia, principalmente pela ótica da economia que pode ser alcançada nos custos e tarifas com energia elétrica. Uma das maneiras de se atingir este objetivo é através do Gerenciamento pelo Lado da Demanda onde se pode remanejar cargas de acordo com um objetivo preestabelecido, como por exemplo, a diminuição de custos com energia elétrica. Neste trabalho é apresentada uma metodologia para realocação de cargas em sistemas industriais. Esta metodologia utiliza cargas que estejam dentro de programas de controle direto de carga e busca encontrar um horário de alocação que traga a maior economia. A realocação é realizada através do uso de um algoritmo genético que tem como resultado final o horário otimizado de alocação de todas as cargas e consequentemente a curva de carga resultante.<br>Large industries and industrial parks are one of the largest energy consumers in a country and therefore it is essential to encourage that the energy consumed by those industries is done so efficiently. It is also in the best interest of the consumers to encourage those changes, especially regarding the economy that can be achieved by the embedded costs and tariffs. One of the ways to achieve this goal is to use a demand side management technique where loads can be shifted according to pre-determined objectives such as reducing the costs with electrical energy. In this thesis, a methodology for load shifting is presented for use in industrial systems. This methodology utilizes loads that are in direct load control programmes and aims to find the connection time that brings the most economical benefit. The reallocation is realized through the use of a genetic algorithm that has the best allocated time and load curve as a result.
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Parry, Emily. "Electricity load estimation and management for plug-in vehicle recharging on a national scale prior to the development of third party monitoring and control mechanisms." Thesis, University of Bath, 2014. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.606668.
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In accordance with the main aim of the study, a widely accessible, modifiable tool was created for parties interested in maintaining the national electricity supply network and parties interested in informing policy on plug-in vehicle adoption schemes and recharging behaviour control. The Parry Tool enables the user to incorporate present limits to plug-in vehicle recharging demand scheduling as imposed by the state of present technology (no third party mechanism for monitoring and control of recharging), present human travel behaviour needs and existing patterns in electricity usage; into the investigation of the impacts of recharging demand impacts and the design of mitigation measures for deflecting (parrying) worst case scenarios. The second aim of the project was to demonstrate the application of the Parry Tool. The multidisciplinary/interdisciplinary information gathered by the Parry Tool was used to produce national demand profiles for plug-in vehicle recharging demand, calculated using socioeconomic and travel behaviour-estimated population sizes for plug-in eligible vehicles and vehicle usage patterns, which were added to existing national electricity demand for a chosen test week – this was the first scenario subsequently tested. The information gathered by the Parry Tool was then used to inform the design of two demand management methods for plug-in vehicle recharging: Recharging Regimes and weekly recharging load-shifting – these were the second and third scenarios subsequently tested. Unmitigated simultaneous recharging demand in scenario 1 (all vehicles assumed to recharge at home upon arrival home every day) severely exacerbated peak demand, raising it by 20% above the highest peak in existing demand for the year 2009 over half an hour from 58,554 MW to 70,012 MW – a challenge to the generation sector. This increased the difference between daily demand minima and maxima and made the new total demand have sharper peaks – a challenge for grid regulators. Recharging Regimes in scenario 2 split the estimated national plug-in vehicle populations into groups of different sizes that started recharging at different times of the day, with the word ‘regime’ being applied because the spread of start times changed over the course of the test week from workdays to weekend. This avoided exacerbation of the peak and reduced the difference between daily demand minima and maxima by raising minima, providing a load-levelling service. Scenario 3 embellished the Recharging Regimes with workday-to-weekend recharging load-shifting that therefore took better advantage of the often overlooked weekly pattern in existing demand (demand being higher on workdays than weekends), by allowing partial recharging of a segment of the plug-in vehicle population. Limited consideration of the impact of changing vehicle energy usage (for which distance travelled was assumed to proxy in this study) showed that the more vehicles used their batteries during the day, the better the levelling effect offered by Recharging Regimes. Greater utilisation of battery capacity each day, however, can also be assumed to lessen the potential for workday-to-weekend load levelling, because load-shifting depends upon vehicles being able to partially recharge or defer recharging to later days and still meet their travel needs plus keep a reserve State Of Charge (SOC) for emergency and other unplanned travel. Whilst altering vehicle energy usage did not change the finding that unmitigated simultaneous recharging exacerbated existing peak demand, it was noted that when limited mileage variation was considered this sharpened the profile of total demand – the rise and fall of the new peak far steeper than that of the original peak in existing demand. The Parry Tool combines a series of integrated methods, several of which are new contributions to the field that use UK data archives but may potentially be adapted by researchers looking at energy issues in other nations. It presents a novel fossil-fuel based justification for targeting road transport – acknowledging energy use of fossil fuel as the originator of many global and local problems, the importance of non-energy use of petroleum products and subsequent conflicts of interest for use, and a fossil fuel dependency based well-to-wheel assessment for UK road transport for the two energy pathways: electricity and petroleum products. It presents a method for the recalculation and ranking of top energy use/users using national energy use statistics that better highlights the importance of the electricity industry. It also presents the first publicly documented method for the direct consultation and extraction of vehicle-focused statistics from the people-focused National Travel Survey database, including a travel behaviour and household income-based assessment of plug-in vehicle eligibility, used to scale up to national estimates for battery electric and plug-in electric hybrid vehicle (BEV and PHEV) national population sizes. The work presented here is meant to allow the reader to perceive the potential benefits of using several resources in combination. It details the Parry Tool, a framework for doing so, and where necessary provides methods for data analysis to suit. It should however be noted that methods were kept as simple as possible so as to be easily followed by non-specialists and researchers entering the field from other disciplines. Methods are also predominantly data-exploratory in nature: strong conclusions therefore should not be drawn. Rather, the work here should be seen as a guideline for future work that may more rigorously study these combined topics and the impacts they may have upon plug-in vehicle ownership, usage behaviour, impacts of recharging upon the national network and the design of mitigation measures to cope with this new demand.
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Saeidpour, Parizy Ehsan. "Electrical Energy Retail Price Optimization for an Interconnected/Islanded Power Grid." University of Akron / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1512463830323059.
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Bouraleh, Maryan. "Techno-economic Potential of Customer Flexibility : A Case Study." Thesis, KTH, Energiteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278079.
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District heating plays a major role in the Swedish energy system. It is deemed a renewable energy source and is the main provider for multi-family dwellings with 90 %. Although the district heating fuel mix consists of majority renewables, a share of 5 % is provided from fossil fuels. To reduce fossil fuel usage and eradicate CO2-emissions from the district heating system new solutions are sought after. In this project, the potential for shortterm thermal energy storage in buildings is investigated. This concept is referred to as customer flexibility. Demand flexibility is created in the district heating system (DHS) by varying the indoor temperature in 50 multi-family dwellings with maximum 1◦C, without jeopardizing the thermal comfort for the tenants. The flexible load makes it possible to store energy shortterm in the building’ envelope. Consequently, heat load curves are evened in production. This leads to a reduction of the peak load in the DHS. Peaks are associated with high costs and environmental impact. Therefore, the potential benefits of customer flexibility are reduced peak production, fuel costs, and CO2-emissions, depending on the fuel mix in the DHS. The project objective is to examine the techno-economic potential of customer flexibility in a specific DHS. The case study is made in a DHS owned by the company Vattenfall, located in the Stockholm area. To evaluate the potential benefits of implementing the concept, seven key performance indicators are chosen. They are peak power, peak fuel usage, produced volume, total fuel cost, fuel cost per produced MWh, climate footprint, and primary energy. Moreover, an in-house optimization model is used to simulate multiple scenarios of the district heating DHS. Different sets of assumptions about the available flexibility in the DHS and the thermal characteristics of the buildings are made. Customer flexibility is modeled as virtual heat storage that can be charged up or down depending on the speed and size of the available storage at a specific outdoor temperature. Simulation results give a maximum peak power reduction of 10.9 % and annual fuel cost reduction between 0.9-3.6 % depending on the scenario. The results found are comparable to values found in similar studies. However, the environmental key performance indicators generated an increase in CO2-emissions and primary energy compared to the baseline scenarios. The result would have looked different if fossil fuels were used in peak production instead of biofuels. The master thesis also aimed to validate assumptions and parameters made in the input data to the optimization model. This was achieved by using results attained from a pilot in the specific DHS. Therefore results generated from the simulations are deemed accurate and confirm that customer flexibility leads to reduced peak production and DHS optimization.<br>Se filen
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Barnawi, Abdulwasa. "Hybrid PV/Wind Power Systems Incorporating Battery Storage and Considering the Stochastic Nature of Renewable Resources." University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470357709.
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Andreoli, André Luiz [UNESP]. "Controlador de demanda e fator de potência de baixo custo para unidades consumidoras de energia elétrica." Universidade Estadual Paulista (UNESP), 2005. http://hdl.handle.net/11449/89568.
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andreoli_al_me_bauru.pdf: 2837768 bytes, checksum: 899d0f484921dccf16d7027e336d500b (MD5)<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)<br>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...<br>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)
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Celebi, Emre. "MODELS OF EFFICIENT CONSUMER PRICING SCHEMES IN ELECTRICITY MARKETS." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/811.
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Suppliers in competitive electricity markets regularly respond to prices that change hour by hour or even more frequently, but most consumers respond to price changes on a very different time scale, i. e. they observe and respond to changes in price as reflected on their monthly bills. This thesis examines mixed complementarity programming models of equilibrium that can bridge the speed of response gap between suppliers and consumers, yet adhere to the principle of marginal cost pricing of electricity. It develops a computable equilibrium model to estimate the time-of-use (TOU) prices that can be used in retail electricity markets. An optimization model for the supply side of the electricity market, combined with a price-responsive geometric distributed lagged demand function, computes the TOU prices that satisfy the equilibrium conditions. Monthly load duration curves are approximated and discretized in the context of the supplier's optimization model. The models are formulated and solved by the mixed complementarity problem approach. It is intended that the models will be useful (a) in the regular exercise of setting consumer prices (i. e. , TOU prices that reflect the marginal cost of electricity) by a regulatory body (e. g. , Ontario Energy Board) for jurisdictions (e. g. , Ontario) where consumers' prices are regulated, but suppliers offer into a competitive market, (b) for forecasting in markets without price regulation, but where consumers pay a weighted average of wholesale price, (c) in evaluation of the policies regarding time-of-use pricing compared to the single pricing, and (d) in assessment of the welfare changes due to the implementation of TOU prices.
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Xia, Tian. "Distributed Coordination Schemes for Periodic Loads for Demand Side Management." Thesis, KTH, Kommunikationsnät, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-53523.
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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.