Journal articles: 'Efficient demand side management'

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P. Dzyuba, Anatoly, and Irina A. Solovyeva. "Demand-side management mechanisms in industry." Journal of New Economy 21, no. 3 (October 7, 2020): 175–95. http://dx.doi.org/10.29141/2658-5081-2020-21-3-9.

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Intensive development of technologies that increase energy efficiency makes the global and the Russian industry consider the introduction of demand-side management mechanisms. Though demand-side management technologies in Russia are at the early stages of introduc tion, existing mechanisms of electricity and natural gas supply allow consumers to reduce their costs and result in equalization of the demand for energy across the entire energy system. The research objective is to explore the energy tariffs in the wholesale and retail markets and mecha nisms for supplying natural gas by regional contractors as well as using the commodity exchange. The authors design mechanisms for industrial consumers to choose the most efficient options to pay for energy resources using the criterion of demand-side management. The research method ology includes the theory of industrial markets and a problem-oriented approach. The authors apply analysis, synthesis, system analysis, statistical methods. Yielded results of the research into programmes on demand-side management administered in different countries enable the authors to prove that the most efficient direction for demand-side management development in Russia is economic norm setting. Within this direction the authors develop algorithms and decision-making matrices for choosing the most efficient tariff option to buy electricity and natural gas by industrial consumers. The researchers evidence the possibility of implement ing demand-side management on energy markets of Russia and provide methodological and organisational support. The findings can be helpful for industrial enterprises and government agencies developing and running their energy efficiency improvement programs.

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Li, Chaojie, Xinghuo Yu, Wenwu Yu, Guo Chen, and Jianhui Wang. "Efficient Computation for Sparse Load Shifting in Demand Side Management." IEEE Transactions on Smart Grid 8, no. 1 (January 2017): 250–61. http://dx.doi.org/10.1109/tsg.2016.2521377.

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Rahman, S., and Rinaldy. "An efficient load model for analyzing demand side management impacts." IEEE Transactions on Power Systems 8, no. 3 (1993): 1219–26. http://dx.doi.org/10.1109/59.260874.

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Kumar, D. Sai. "Demand Side Management Techniques for Peak Reduction." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 30, 2021): 2911–13. http://dx.doi.org/10.22214/ijraset.2021.36979.

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Industrial growth is the back bone for the development of any nation. Industries are mainly dependent on electrical energy. But from the various studies, the sources for electrical energy are decreasing gradually, and in turn, the gap is increasing between the supplier and the load. The solution for this scenario is optimal utilization of resources. To overcome this problem , the concept Demand Side Management (DSM) has emerged in Power System Planning and Management. The principle objective of DSM is mutual understanding between the supplier and the consumer for maximizing benefits and minimizing inconvenience. The aim of this research work is selection and application of appropriate DSM techniques to industrial and domestic loads for peak load management and energy conservation, that is to control the maximum demand during the peak hours and saving the energy by using the energy efficient and intelligent appliances like air conditioners and water heaters. DSM includes techniques like the End Use Equipment Control, the Load Priority Technique, he Peak Clipping & Valley filling, the Differential Tariff and Resizing of the equipment. Depending upon the application, all the techniques may be applied sequentially, or only a few of them can be applied. There is a lot of ambiguity in the selection of DSM techniques, because the application of each DSM technique depends on the case study and the problem associated with the respective case study. After comprehensive understanding of a particular case, a thorough investigation and subsequent data analysis pave the way for the selection of appropriate DSM technique/techniques

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Castro, Tiago Bornia, Marcio Zamboti Fortes, Fernanda Passos, and Natalia C. Fernandes. "An Efficient Demand-Side Management Mechanisms in Residential Energy Consumption Automation." Journal of Engineering Science and Technology Review 15, no. 3 (2022): 9–25. http://dx.doi.org/10.25103/jestr.153.02.

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Nailen, R. L. "Utility rebates for efficient motors-the outlook for demand-side management." IEEE Transactions on Industry Applications 33, no. 1 (1997): 143–53. http://dx.doi.org/10.1109/28.567095.

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Straub, Mary M., and Sheldon Switzer. "Using Available Information for Efficient Evaluation of Demand-Side Management Programs." Electricity Journal 24, no. 7 (August 2011): 83–96. http://dx.doi.org/10.1016/j.tej.2011.07.007.

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Palacios-Garcia, Emilio J., Xavier Carpent, Joppe W. Bos, and Geert Deconinck. "Efficient privacy-preserving aggregation for demand side management of residential loads." Applied Energy 328 (December 2022): 120112. http://dx.doi.org/10.1016/j.apenergy.2022.120112.

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Liu, Zixu, Xiaojun Zeng, and Fanlin Meng. "An Integration Mechanism between Demand and Supply Side Management of Electricity Markets." Energies 11, no. 12 (November 27, 2018): 3314. http://dx.doi.org/10.3390/en11123314.

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One of the main challenges in the emerging smart grid is to jointly consider the demand and supply, which is also reflected in the wholesale market (supply side) and the retail market (demand side). When integrating the demand and supply side into one framework, the mechanism for determining the market clearing price has been changed. This is due to the demand variations in the demand side in response to the market clearing price and the change of generation costs in the supply side from the demand variation. In order to find the best balance between the supply and demand under the demand response management scheme, this paper proposes a new integrated supply and demand coordination mechanism for the electricity market and smart pricing methods for generator and retailers. Another important contribution of this paper is to develop an efficient algorithm to find the match equilibrium between the demand and supply sides in the new proposed mechanism. Experimental results demonstrate that the new mechanism can effectively handle unpredictable demand under dynamic retail pricing and support the ISO to dispatch the generation economically. It can also help in achieving the goals of dynamic pricing such as maximizing the profits for retailers.

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Laitsos, Vasileios M., Dimitrios Bargiotas, Aspassia Daskalopulu, Athanasios Ioannis Arvanitidis, and Lefteri H. Tsoukalas. "An Incentive-Based Implementation of Demand Side Management in Power Systems." Energies 14, no. 23 (November 30, 2021): 7994. http://dx.doi.org/10.3390/en14237994.

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The growing demand for electricity runs counter to European-level goals, which include activities aimed at sustainable development and environmental protection. In this context, efficient consumption of electricity attracts much research interest nowadays. One environment friendly solution to meet increased demand lies in the deployment of Renewable Energy Sources (RES) in the network and in mobilizing the active participation of consumers in reducing the peak of demand, thus smoothing the overall load curve. This paper addresses the issue of efficient and economical use of electricity from the Demand Side Management (DSM) perspective and presents an implementation of a fully-parameterized and explicitly constrained incentive-based demand response program The program uses the Particle Swarm Optimization algorithm and demonstrates the potential advantages of integrating RES while supporting two-way communication between energy production and consumption and two-way power exchange between the main grid and the RES.

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Symon V.A., Tibbie Pon, and I. Jacob Ragland. "Improving Efficiency of Power Systems by Demand Side Management Method." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 1 (February 1, 2017): 100. http://dx.doi.org/10.11591/ijece.v7i1.pp100-106.

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In the smart grid infrastructure based power systems, it is necessary to consider the demand side management to enhance the energy reduction and system control. In many countries the resources are very less so the available resources have to be used in an efficient manner without any loss. The total loss cannot be avoided but it can be reduced. In the proposed system, the Particle Swarm Optimization (PSO) technique is used to distribute the power in the smart grid. Here, the grids are arranged in such a way that the losses in it are reduced. The load connected to the grid is rearranged according to their use. It uses a new and stochastic scheduling technique to handle the uncertainties in the power system. Solar and wind power are taken in account for twenty four hours and the values are given to the PSO algorithm. The experiment was conducted by MATLAB and the results show that the efficiency level of wind and solar power systems was increased by an appreciable level. The proposed technique is compared with the normal system without using Demand Side Management (DSM) and it shows that the proposed system gives better results than the existing systems.

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Hietaharju, Petri, Mika Ruusunen, and Kauko Leiviskä. "Enabling Demand Side Management: Heat Demand Forecasting at City Level." Materials 12, no. 2 (January 9, 2019): 202. http://dx.doi.org/10.3390/ma12020202.

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Implementation of new energy efficiency measures for the heating and building sectors is of utmost importance. Demand side management offers means to involve individual buildings in the optimization of the heat demand at city level to improve energy efficiency. In this work, two models were applied to forecast the heat demand from individual buildings up to a city-wide area. District heating data at the city level from more than 4000 different buildings was utilized in the validation of the forecast models. Forecast simulations with the applied models and measured data showed that, during the heating season, the relative error of the city level heat demand forecast for 48 h was 4% on average. In individual buildings, the accuracy of the models varied based on the building type and heat demand pattern. The forecasting accuracy, the limited amount of measurement information and the short time required for model calibration enable the models to be applied to the whole building stock. This should enable demand side management and lead to the predictive optimization of heat demand at city level, leading to increased energy efficiency.

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Veit, A., Y. Xu, R. Zheng, N. Chakraborty, and K. Sycara. "Demand Side Energy Management via Multiagent Coordination in Consumer Cooperatives." Journal of Artificial Intelligence Research 50 (August 31, 2014): 885–922. http://dx.doi.org/10.1613/jair.4416.

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A key challenge in creating a sustainable and energy-efficient society is to make consumer demand adaptive to the supply of energy, especially to the renewable supply. In this article, we propose a partially-centralized organization of consumers (or agents), namely, a consumer cooperative that purchases electricity from the market. In the cooperative, a central coordinator buys the electricity for the whole group. The technical challenge is that consumers make their own demand decisions, based on their private demand constraints and preferences, which they do not share with the coordinator or other agents. We propose a novel multiagent coordination algorithm, to shape the energy demand of the cooperative. To coordinate individual consumers under incomplete information, the coordinator determines virtual price signals that it sends to the consumers to induce them to shift their demands when required. We prove that this algorithm converges to the central optimal solution and minimizes the electric energy cost of the cooperative. Additionally, we present results on the time complexity of the iterative algorithm and its implications for agents' incentive compatibility. Furthermore, we perform simulations based on real world consumption data to (a) characterize the convergence properties of our algorithm and (b) understand the effect of differing demand characteristics of participants as well as of different price functions on the cost reduction. The results show that the convergence time scales linearly with the agent population size and length of the optimization horizon. Finally, we observe that as participants' flexibility of shifting their demands increases, cost reduction increases and that the cost reduction is not sensitive to variation in consumption patterns of the consumers.

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de Almeida, A. T., S. Greenberg, and C. Blumstein. "Demand-side management opportunities through the use of energy-efficient motor systems." IEEE Transactions on Power Systems 5, no. 3 (1990): 852–61. http://dx.doi.org/10.1109/59.65914.

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Biroon, Roghieh A., Zoleikha Abdollahi, and Ramtin Hadidi. "Inverter's Nonlinear Efficiency and Demand-Side Management Challenges." IEEE Power Electronics Magazine 8, no. 1 (March 2021): 49–54. http://dx.doi.org/10.1109/mpel.2020.3047527.

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Kabelitz, Stefanie, and Sergii Kolomiichuk. "Production Process Modeling for Demand Side Management." Applied Mechanics and Materials 871 (October 2017): 77–86. http://dx.doi.org/10.4028/www.scientific.net/amm.871.77.

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The supply of electricity is growing increasingly dependent on the weather as the share of renewable energies increases. Different measures can nevertheless maintain grid reliability and quality. These include the use of storage technologies, upgrades of the grid and options for responsiveness to supply and demand. This paper focuses on demand side management and the use of flexibility in production processes. First, the framework of Germany’s energy policy is presented and direct and indirect incentives for businesses to seek as well as to provide flexibility capabilities are highlighted. Converting this framework into a mixed integer program leads to multi-objective optimization. The challenge inherent to this method is realistically mapping the different objectives that affect business practices directly and indirectly in a variety of laws. An example is introduced to demonstrate the complexity of the model and examine the energy flexibility. Second, manufacturing companies’ energy efficiency is assessed under the frequently occurring conditions of heavily aggregated energy consumption data and of information with insufficient depth of detail to perform certain analyses, formulate actions or optimize processes. The findings obtained from the energy assessment and energy consumption projections are used to model the production system’s energy efficiency and thus facilitate optimization. Methods of data mining and machine learning are employed to project energy consumption. Aggregated energy consumption data and different production and environmental parameters are used to assess indirectly measured consumers and link projections of energy consumption with the production schedule.

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Shewale, Amit, Anil Mokhade, Nitesh Funde, and Neeraj Dhanraj Bokde. "A Survey of Efficient Demand-Side Management Techniques for the Residential Appliance Scheduling Problem in Smart Homes." Energies 15, no. 8 (April 14, 2022): 2863. http://dx.doi.org/10.3390/en15082863.

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The residential sector is a major contributor to the global energy demand. The energy demand for the residential sector is expected to increase substantially in the next few decades. As the residential sector is responsible for almost 40% of overall electricity consumption, the demand response solution is considered the most effective and reliable solution to meet the growing energy demands. Home energy management systems (HEMSs) help manage the electricity demand to optimize energy consumption without compromising consumer comfort. HEMSs operate according to multiple criteria, including electricity cost, peak load reduction, consumer comfort, social welfare, environmental factors, etc. The residential appliance scheduling problem (RASP) is defined as the problem of scheduling household appliances in an efficient manner at appropriate periods with respect to dynamic pricing schemes and incentives provided by utilities. The objectives of RASP are to minimize electricity cost and peak load, maximize local energy generation and improve consumer comfort. To increase the effectiveness of demand response programs for smart homes, various demand-side management strategies are used to enable consumers to optimally manage their loads. This study lists out DSM techniques used in the literature for appliance scheduling. Most of these techniques aim at energy management in residential sectors to encourage users to schedule their power consumption in an effective manner. However, the performance of these techniques is rarely analyzed. Additionally, various factors, such as consumer comfort and dynamic pricing constraints, need to be incorporated. This work surveys most recent literature on residential household energy management, especially holistic solutions, and proposes new viewpoints on residential appliance scheduling in smart homes. The paper concludes with key observations and future research directions.

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Jasim, Ali M., Basil H. Jasim, Bogdan-Constantin Neagu, and Bilal Naji Alhasnawi. "Efficient Optimization Algorithm-Based Demand-Side Management Program for Smart Grid Residential Load." Axioms 12, no. 1 (December 27, 2022): 33. http://dx.doi.org/10.3390/axioms12010033.

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Incorporating demand-side management (DSM) into residential energy guarantees dynamic electricity management in the residential domain by allowing consumers to make early-informed decisions about their energy consumption. As a result, power companies can reduce peak demanded power and adjust load patterns rather than having to build new production and transmission units. Consequently, reliability is enhanced, net operating costs are reduced, and carbon emissions are mitigated. DSM can be enhanced by incorporating a variety of optimization techniques to handle large-scale appliances with a wide range of power ratings. In this study, recent efficient algorithms such as the binary orientation search algorithm (BOSA), cockroach swarm optimization (CSO), and the sparrow search algorithm (SSA) were applied to DSM methodology for a residential community with a primary focus on decreasing peak energy consumption. Algorithm-based optimal DSM will ultimately increase the efficiency of the smart grid while simultaneously lowering the cost of electricity consumption. The proposed DSM methodology makes use of a load-shifting technique in this regard. In the proposed system, on-site renewable energy resources are used to avoid peaking of power plants and reduce electricity costs. The energy Internet-based ThingSpeak platform is adopted for real-time monitoring of overall energy expenditure and peak consumption. Peak demand, electricity cost, computation time, and robustness tests are compared to the genetic algorithm (GA). According to simulation results, the algorithms produce extremely similar results, but BOSA has a lower standard deviation (0.8) compared to the other algorithms (1.7 for SSA and 1.3 for CSOA), making it more robust and superior, in addition to minimizing cost (5438.98 cents of USD (mean value) and 16.3% savings).

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Beal, Cara D., Thulo Ram Gurung, and Rodney A. Stewart. "Demand-side management for supply-side efficiency: Modeling tailored strategies for reducing peak residential water demand." Sustainable Production and Consumption 6 (April 2016): 1–11. http://dx.doi.org/10.1016/j.spc.2015.11.005.

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Kumar, Rakesh, Rakesh Ranjan, and Mukesh Chandra Verma. "Role of Energy Efficiency and Conservation Including Demand Side Management for Sustainable Development in India." International Journal of Engineering & Technology 7, no. 3.12 (July 20, 2018): 1210. http://dx.doi.org/10.14419/ijet.v7i3.12.17839.

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Energy is used to provide cost-effective services meet the objectives of promoting sustainable development. The importance of Energy Efficiency and Conservation (EE and EC) is to conserve depleting energy resources. Energy efficiency in India has been increasing which has led the Government of India through the Energy Conservation Act (ECA) and the Bureau of Energy Efficiency (BEE) to begin several programs. Demand Side Management (DSM) and Energy Efficiency and Conservation are improving the economic growth of Indian utilities.DSM also aimed at promoting the installation and use of energy efficient equipment that consume less power having good quality of output. Energy efficiency is important for sustainable future. Demand Side Management including Demand Response (DR) Activity is utilized to limit the peak electricity demand. DSM helps grid operators to act as virtual power plants and power the utilities to transmit energy when needed through demand response measures. Demand Response (DR) measures can be adapted for a industrial and commercial facility that includes turning off air conditioning, lighting, pumps, and other non-essential equipment. Demand Response is a Demand Side Management (DSM) method in which the end users of electricity are encouraged to take part in dropping the peak load on the system by altering their normal energy consumption schedule. The basic objective of the Agriculture, Municipal and Industrial Demand Side Management (DSM) programmes are to improve the overall energy efficiency of the SLDC (State Load Dispatch Centre) and Electricity Grids which could lead to substantial savings in the electricity consumption, resulting in cost reduction and savings. The target of energy saving can be achieved by implementing acts and policies which leads to state wise DSM Regulations by Regulatory Commissions to the State Power Utilities. The Role of DSM and Energy Efficiency including conservation can fulfill the dreams projects electricity demand in Smart Cities. The Role of State Electricity Regulatory Commissions and Forum of Regulators are very important to make India’s electricity demand in future.

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Jin, Xiao Ming, Xue Lin Zhao, Kun Qi Jia, and Guang Yu He. "An Implementation of Demand Side Energy Management for Refined Load Control." Advanced Materials Research 1092-1093 (March 2015): 409–13. http://dx.doi.org/10.4028/www.scientific.net/amr.1092-1093.409.

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Demand Side Energy Management System (DSEMS) manages energy demand by controlling end-use appliances in a refined, energy-saving, cost-efficient and user-friendly way. The DSEMS runs on an Android tablet computer, which serves as energy gateway to communicate with two types of controllers via ZigBee network. Smart sockets connected to the ZigBee network will monitor and control plug-in loads and IR remote controller (IRRC) for air-conditioner temperature setting. The proposed system has been installed in an apartment with over 24 rooms as a paradigm, which proved that the DSEMS can realize the autonomous energy-saving via real-time surveillance and control on household appliances.

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Arteconi, Alessia, and Fabio Polonara. "Assessing the Demand Side Management Potential and the Energy Flexibility of Heat Pumps in Buildings." Energies 11, no. 7 (July 14, 2018): 1846. http://dx.doi.org/10.3390/en11071846.

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The energy demand in buildings represents a considerable share of the overall energy use. Given the significance and acknowledged flexibility of thermostatically controlled loads, they represent an interesting option for the implementation of demand side management (DSM) strategies. In this paper, an overview of the possible DSM applications in the field of air conditioning and heat pumps is provided. In particular, the focus is on the heat pump sector. Three case studies are analyzed in order to assess the energy flexibility provided by DSM technologies classified as energy efficient devices, energy storage systems, and demand response programs. The load shifting potential, in terms of power and time, is evaluated by varying the system configuration. Main findings show that energy efficient devices perform strategic conservation and peak shaving strategies, energy storage systems perform load shifting, while demand response programs perform peak shaving and valley filling strategies.

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Salameh, Khouloud, Mohammed Awad, Aisha Makarfi, Abdul-Halim Jallad, and Richard Chbeir. "Demand Side Management for Smart Houses: A Survey." Sustainability 13, no. 12 (June 15, 2021): 6768. http://dx.doi.org/10.3390/su13126768.

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Continuous advancements in Information and Communication Technology and the emergence of the Big Data era have altered how traditional power systems function. Such developments have led to increased reliability and efficiency, in turn contributing to operational, economic, and environmental improvements and leading to the development of a new technique known as Demand Side Management or DSM. In essence, DSM is a management activity that encourages users to optimize their electricity consumption by controlling the operation of their electrical appliances to reduce utility bills and their use during peak times. While users may save money on electricity costs by rescheduling their power consumption, they may also experience inconvenience due to the inflexibility of getting power on demand. Hence, several challenges must be considered to achieve a successful DSM. In this work, we analyze the power scheduling techniques in Smart Houses as proposed in most cited papers. We then examine the advantages and drawbacks of such methods and compare their contributions based on operational, economic, and environmental aspects.

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Wasim Khan, Hassan, Muhammad Usman, Ghulam Hafeez, Fahad R. Albogamy, Imran Khan, Zeeshan Shafiq, Mohammad Usman Ali Khan, and Hend I. Alkhammash. "Intelligent Optimization Framework for Efficient Demand-Side Management in Renewable Energy Integrated Smart Grid." IEEE Access 9 (2021): 124235–52. http://dx.doi.org/10.1109/access.2021.3109136.

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Nadel, S. M. "Using utility demand-side management programs to spur the development of more efficient appliances." IEEE Transactions on Industry Applications 30, no. 4 (1994): 877–82. http://dx.doi.org/10.1109/28.297902.

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Chakraborty, Nilotpal, Arijit Mondal, and Samrat Mondal. "Efficient Load Control Based Demand Side Management Schemes Towards a Smart Energy Grid System." Sustainable Cities and Society 59 (August 2020): 102175. http://dx.doi.org/10.1016/j.scs.2020.102175.

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Oh, HyungSeon. "Demand-Side Management with a State Space Consideration." Energies 11, no. 9 (September 14, 2018): 2444. http://dx.doi.org/10.3390/en11092444.

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Power networks are gateways to transfer power from generators to end-users. Often, it is assumed that the transfer occurs freely without any limiting factors. However, power flows over a network can be limited by predetermined limits that may come from physical reasons, such as line capacity or Kirchhoff’s laws. When flow is constrained by these limits, this is called congestion, which reduces the energy efficiency and splits the price for electricity across the congested lines. One promising, cost-effective way to relieve the impact of the congestion is demand-side management (DSM). However, it is unclear how much DSM can impact congestion and where it can control the demand. This paper proposes a new DSM mechanism based on locational willingness-to-pay (WTP) centered around income statistics; utilizes a state-space tool to determine the possibility to alter prices by DSM; and formulates a convex optimization problem to decide the DSM. The proposed methodology is tested on IEEE (Institute of Electrical and Electronics Engineers) systems with two commonly used objectives: cost minimization and social welfare maximization.

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Andrada-Monrós, C. "Methodology to optimise electricity demand in the residential sector through efficient load management." Renewable Energy and Power Quality Journal 20 (September 2022): 719–23. http://dx.doi.org/10.24084/repqj20.412.

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The current energy model requires a transformation based on a sustainable model that is accessible to all, focused on the needs of citizens and committed to climate change. Moreover, the rising cost of non-renewable energy sources, and the growing presence of distributed renewable generation, has a major impact on the electricity sector, creating the need to develop mechanisms to help manage energy demand in order to converge towards an efficient, emission-free electricity system that is responsible for the environment and future generations. The main motivation is the recent change in the regulation of electricity tariff systems and the introduction of time discriminations in the residential sector. Based on the previous need and supported by a survey to find out society's predisposition and sensitivity to demand management, this paper presents the methodology developed as an active demand-side management mechanism for residential consumers, considering their load shifting priorities and prioritising the use of renewable energy if possible, reducing grid energy consumption. In a nutshell, the use of a tool capable of helping consumers to regulate their energy consumption, analyse their consumption pattern and plan their domestic loads to obtain the lowest energy and economic impact is developed. Key words. Active demand-side management, Load shedding, Energy optimisation, Renewable energy, Load prioritisation

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Xiong, Wei, and Shi Wei Su. "Power Demand Side Management Based on the Sensitivity Analysis." Advanced Materials Research 614-615 (December 2012): 1915–18. http://dx.doi.org/10.4028/www.scientific.net/amr.614-615.1915.

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In the current energy relative tension of the environment, through implementation of power demand-side management improvement of energy efficiency in the use and reasonable distribution of energy in the solution of the current energy issues are more important significance. Power Demand-side management of the program's design is a more complicated issue of decision-making. This article by sensitivity analysis of cost-effectiveness of power users and power users for response analysis of power demand side management schemes, provided for the implementation of the demand side management programmers must be based on.

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Okada, Tomoyuki. "Integrated water resources management and drought risk management in Japan." Water Policy 18, S2 (December 1, 2016): 70–88. http://dx.doi.org/10.2166/wp.2016.214.

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Japan has experienced several severe drought disasters in the past and is still suffering from drought conditions in some parts of the country every year. To cope with the drought disasters, Japan takes three types of countermeasures: (i) water resources planning and development as supply side measures; (ii) promotion of efficient water use as demand side measures; and (iii) coordinated drought risk management as risk control measures. Owing to continuous efforts in water resources development, water saving, and water recycling, drought risk is currently mitigated to some extent. Japan further needs to improve the drought safety level and secure stable water supply.

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Shalaby, Hossam Eldin Hamed. "A Review on Demand Side Management Applications, Techniques, and Potential Energy and Cost saving." ELEKTRIKA- Journal of Electrical Engineering 20, no. 1 (April 30, 2021): 21–33. http://dx.doi.org/10.11113/elektrika.v20n1.248.

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Electrical peak load demand all over the world is always anticipated to grow, which is challenging electrical utility to supply such increasing load demand in a cost effective, reliable and sustainable manner. Thus, there is a need to study some of load management (LM) techniques employed to minimize energy consumption, reduce consumers' electricity bills and decrease the greenhouse gas emissions responsible for global warming. This paper presents a review of several recent LM strategies and optimization algorithms in different domains. The review is complemented by tabulating several demand side management (DSM) techniques with a specific view on the used demand response (DR) programs, key finding and benefits gained. A special focus is directed to the communication protocols and wireless technology, incorporation of renewable energy resources (RERs), battery energy storage (BES), home appliances scheduling and power quality applications. The outcome of this review reveals that the real time pricing (RTP) is the most efficient price-based mechanism program (PBP), whilst time of use (TOU) is the basic PBP and easiest to implement. Energy efficiency programs have proved the highest influential impact on the annual energy saving over the other dynamic pricing mechanism programs. Through a forecasted proposal of future study, DSM proved tremendous potential annual energy savings, peak demand savings, and investment cost rates within different consumption sectors progressively up to year 2030.

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Hussain, Hafiz, Nadeem Javaid, Sohail Iqbal, Qadeer Hasan, Khursheed Aurangzeb, and Musaed Alhussein. "An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid." Energies 11, no. 1 (January 12, 2018): 190. http://dx.doi.org/10.3390/en11010190.

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Jin, Fengyuan, Xin Huang, and Chengcheng Shao. "Efficient utilization of demand side resources behind the meter: Assessment, profiling and scheduling." Electricity Journal 35, no. 5 (June 2022): 107123. http://dx.doi.org/10.1016/j.tej.2022.107123.

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Lombard, C., E. H. Mathews, and M. Kleingeld. "Demand-Side Management through thermal efficiency in South African houses." Energy and Buildings 29, no. 3 (January 1999): 229–39. http://dx.doi.org/10.1016/s0378-7788(98)00064-4.

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Hussain, Muhammad Majid, Rizwan Akram, Zulfiqar Ali Memon, Mian Hammad Nazir, Waqas Javed, and Muhammad Siddique. "Demand Side Management Techniques for Home Energy Management Systems for Smart Cities." Sustainability 13, no. 21 (October 24, 2021): 11740. http://dx.doi.org/10.3390/su132111740.

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In this paper, three distinct distributed energy resources (DERs) modules have been built based on demand side management (DSM), and their use in power management of dwelling in future smart cities has been investigated. The investigated modules for DERs system are: incorporation of load shedding, reduction of grid penetration with renewable energy systems (RES), and implementation of home energy management systems (HEMS). The suggested approaches offer new potential for improving demand side efficiency and helping to minimize energy demand during peak hours. The main aim of this work was to investigate and explore how a specific DSM strategy for DER may assist in reducing energy usage while increasing efficiency by utilizing new developing technology. The Electrical Power System Analysis (ETAP) software was used to model and assess the integration of distributed generation, such as RES, in order to use local power storage. An energy management system has been used to evaluate a PV system with an individual household load, which proved beneficial when evaluating its potential to generate about 20–25% of the total domestic load. In this study, we have investigated how smart home appliances’ energy consumption may be minimized and explained why a management system is required to optimally utilize a PV system. Furthermore, the effect of integration of wind turbines to power networks to reduce the load on the main power grid has also been studied. The study revealed that smart grids improve energy efficiency, security, and management whilst creating environmental awareness for consumers with regards to power usage.

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Osareh, A. R., J. Pan, and S. Rahman. "An efficient approach to identify and integrate demand-side management on electric utility generation planning." Electric Power Systems Research 36, no. 1 (January 1996): 3–11. http://dx.doi.org/10.1016/0378-7796(95)01010-6.

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Javaid, Nadeem, Ghulam Hafeez, Sohail Iqbal, Nabil Alrajeh, Mohamad Souheil Alabed, and Mohsen Guizani. "Energy Efficient Integration of Renewable Energy Sources in the Smart Grid for Demand Side Management." IEEE Access 6 (2018): 77077–96. http://dx.doi.org/10.1109/access.2018.2866461.

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Zhou, Ying, Songsong Chen, Kun Shi, Taorong Gong, Jindou Yuan, Bo Li, and Shihai Yang. "Prediction Model of Elastic Load Resource Regulation Potential under Hierarchical and Partitioned Dynamic Control Architecture." Journal of Physics: Conference Series 2331, no. 1 (August 1, 2022): 012014. http://dx.doi.org/10.1088/1742-6596/2331/1/012014.

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Abstract In order to deal with the problem of energy shortage, demand side management has attracted more and more attention. Taking demand side resources as an example to understand the regulation potential of demand side resources, this paper designs a hierarchical and partitioned dynamic regulation architecture for demand side adjustable resources, which can carry out the interconnection between multi-level subjects and efficient information interaction. The regulation potential prediction model of elastic load is established through the hierarchical and partitioned architecture, and the credible and adjustable potential of resident users under two regulation scenarios is obtained through calculation: participating in emergency load reduction and peak valley difference, which proves the effectiveness of the architecture.

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Vigants, Haralds, Dagnija Blumberga, and Ivars Veidenbergs. "Demand Side Management in Pellet Production: Internal and External Factors." Environmental and Climate Technologies 14, no. 1 (December 1, 2014): 30–35. http://dx.doi.org/10.1515/rtuect-2014-0011.

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Abstract This paper demonstrates a demand side management case study: how to save energy and how research and data analysis help to create an energy management system in a pellet production facility; and shows ways to implement the EU energy efficiency directive in production facilities. The study carried out in this research serves as a far-reaching step that can be taken to improve energy efficiency during the operation mode of technological equipment. The benchmarking methodology is used for analysis of results. Internal and external factors and indicators, which affect energy management potential in pellet production are analysed. Analysis of external factors is based on the state legal framework regulating the development of the energy sector. Methodology on the analysis of energy demand includes the internal energy management of an enterprise. The experimental results discussed in this paper show that particular steps, which are oriented to specific use of technological equipment, could play significant role in energy efficiency improvement in industry which is illustrated by the pre-milling process in the pellet production system using power.

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Fritz, WLO, and MTE Kahn. "Energy efficient lighting and energy management." Journal of Energy in Southern Africa 17, no. 4 (November 1, 2006): 33–38. http://dx.doi.org/10.17159/2413-3051/2006/v17i4a3198.

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Energy management and the application of energy consumption reduction methods is high on the priority list of South Africa’s electrical supply utility, Eskom. One of Eskom’s Demand Side Management (DSM) recovery plan steps was the establishment of a subsidy programme for energy auditing and energy efficient lighting. A need arose to implement new lighting designs and to improve existing lighting systems. These improved lighting systems are used as recommendations in Energy Audits to achieve lighting efficiency and energy consumption reduction. It also highlights and promotes cost effective designs and energy management. New and better lighting methods are developed and researched to increase returns, domestically and in industry. This also highlights the importance of energy consumption reduction. This paper also discusses an Energy Audit conducted at a school in Worcester by the Service Learning and Development (SLD) unit of the Cape Peninsula University of Technology, Electrical Engineering Department in Bellville. The SLD delivers a service to the community, to improve their standard of living and to provide training to electrical engineering students. The aim of the project was to recommend energy consumption reduction methods.

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Anand, Hithu, R. Rengaraj, and G. R. Venkatakrishnan. "A convenient demand response layout for energy efficient residential prosumers." IOP Conference Series: Earth and Environmental Science 1100, no. 1 (December 1, 2022): 012019. http://dx.doi.org/10.1088/1755-1315/1100/1/012019.

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Abstract Demand response (DR) is a high priority smart grid technology yet, efficient implementation of the same at the circuit level is often overlooked. Technologies like DR is vital to the improvement, stability and reduction of congestion in the grid. At the distribution side, addition of photovoltaic (PV) systems with appropriate metering has made consumers to prosumers. Prosumers contribute to the grid supply and often meeting increased demand. PV installation has made surplus grid power available. Power from PV is an environment friendly approach, in-order to yield its maximum benefit, it should be appropriately connected with advanced metering infrastructure (AMI). Further, AMI enables other technologies like real time pricing (RTP), DR and demand side management (DSM). Pilot projects put forward by Government of India (GOI) has already deployed smart meters, transforming existing conventional meters into AMI. Hence, functional benefits of AMI are to be studied to its full usage potential. DR and RTP are more focused on consumer behaviour and involvement whereas, DSM is under the control of utility. Hence, novel layouts for energy efficient prosumers with net-metering, gross-metering, hybrid loads and renewable PV integration are analysed. Consumer feasibility of DR without compromising, basic needs of power availability and comfort is focused. Inference is made from both metering infrastructures, tariff schemes and its application in Puducherry locality of India.

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Panagiotidis, Paraskevas, Andrew Effraimis, and George A. Xydis. "An R-based forecasting approach for efficient demand response strategies in autonomous micro-grids." Energy & Environment 30, no. 1 (July 10, 2018): 63–80. http://dx.doi.org/10.1177/0958305x18787259.

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The main aim of this work is to reduce electricity consumption for consumers with an emphasis on the residential sector in periods of increased demand. Efforts are focused on creating a methodology in order to statistically analyse energy demand data and come up with forecasting methodology/pattern that will allow end-users to organize their consumption. This research presents an evaluation of potential Demand Response programmes in Greek households, in a real-time pricing market model through the use of a forecasting methodology. Long-term Demand Side Management programs or Demand Response strategies allow end-users to control their consumption based on the bidirectional communication with the system operator, improving not only the efficiency of the system but more importantly, the residential sector-associated costs from the end-users’ side. The demand load data were analysed and categorised in order to form profiles and better understand the consumption patterns. Different methods were tested in order to come up with the optimal result. The Auto Regressive Integrated Moving Average modelling methodology was selected in order to ensure forecasts production on load demand with the maximum accuracy.

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Denysiuk, Sergii, Oleg Kotsar, and Vitalii Opryshko. "Increasing the energy efficiency of warehouses using demand-side management mechanisms." Technology audit and production reserves 2, no. 1(34) (March 30, 2017): 39–45. http://dx.doi.org/10.15587/2312-8372.2017.99914.

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Baharlouei, Zahra, and Massoud Hashemi. "Efficiency-Fairness Trade-off in Privacy-Preserving Autonomous Demand Side Management." IEEE Transactions on Smart Grid 5, no. 2 (March 2014): 799–808. http://dx.doi.org/10.1109/tsg.2013.2296714.

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Warren, Peter. "Demand-side policy: Global evidence base and implementation patterns." Energy & Environment 29, no. 5 (March 20, 2018): 706–31. http://dx.doi.org/10.1177/0958305x18758486.

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Demand-side management (DSM) policy refers to government policies for managing energy consumption in order to meet environmental and energy security objectives. The broader term of demand-side management encompasses energy efficiency, demand response and on-site generation and storage. A comprehensive meta-evaluation of the global evidence base for demand-side policy is lacking in the literature, and this paper contributes to filling this research gap. The paper focuses on the quality of the evidence base and policy implementation patterns and identifies 30 countries and 36 sub-national states across six continents that have implemented demand-side management policies and produced high-quality ex-post evaluations of those policies. The 690 high-quality evaluations are primarily conducted by industry rather than by governments or academia. The results show that 12 types of individual demand-side management policy and 9 demand-side management policy packages have been implemented and evaluated, and that carbon emissions reduction is the primary driver for demand-side management policies. The evidence base is greatest in the USA, the UK, California, France and China, and alternative utility business models (such as performance targets and decoupling policies), information campaigns, loans and subsidies, utility obligations and performance standards are the most commonly implemented and evaluated policies. This paper argues that demand-side policy will play an increasingly important role as a complement to low carbon activities on the supply-side in the transition to a more environmentally sustainable energy system.

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Jung, Somi, and Dongwoo Kim. "Pareto-Efficient Capacity Planning for Residential Photovoltaic Generation and Energy Storage with Demand-Side Load Management." Energies 10, no. 4 (March 23, 2017): 426. http://dx.doi.org/10.3390/en10040426.

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Dorahaki, Sobhan, Masoud Rashidinejad, Mojgan Mollahassani-pour, and Alireza Bakhshai. "An efficient hybrid structure to solve economic-environmental energy scheduling integrated with demand side management programs." Electrical Engineering 101, no. 4 (November 4, 2019): 1249–60. http://dx.doi.org/10.1007/s00202-019-00866-x.

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Dhivya, S., and R. Arul. "Demand Side Management Studies on Distributed Energy Resources: A Survey." Transactions on Energy Systems and Engineering Applications 2, no. 1 (July 30, 2021): 17–31. http://dx.doi.org/10.32397/tesea.vol2.n1.2.

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The number of distributed environmentally friendly energy sources and generators necessitates new operating methods and a power network board to preserve or even increase the efficiency and quality of the power supply. Similarly, the growth of matriculates promotes the formation of new institutional systems, in which power and power exchanges become increasingly essential. Because of how an inactive entity traditionally organizes distribution systems, the DG’s connection inevitably changes the system’s qualifications to which it is connected. As a consequence of the Distributed Generation, this presumption is currently legal and non-existent. This article glides on demand side management and analysis on distributed energy resources. Investigation of DSM along with zonal wise classification has been carried out in this survey. Its merits and applications are also presented.

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Aoun, Alain, Hussein Ibrahim, Mazen Ghandour, and Adrian Ilinca. "Blockchain-Enabled Energy Demand Side Management Cap and Trade Model." Energies 14, no. 24 (December 20, 2021): 8600. http://dx.doi.org/10.3390/en14248600.

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Global economic growth, demographic explosion, digitization, increased mobility, and greater demand for heating and cooling due to climate change in different world areas are the main drivers for the surge in energy demand. The increase in energy demand is the basis of economic challenges for power companies alongside several socio-economic problems in communities, such as energy poverty, defined as the insufficient coverage of energy needs, especially in the residential sector. Two main strategies are considered to meet this increased demand. The first strategy focuses on new sustainable and eco-friendly modes of power generation, such as renewable energy resources and distributed energy resources. The second strategy is demand-side oriented rather than the supply side. Demand-side management, demand response (DR), and energy efficiency (EE) programs fall under this category. On the other hand, the decentralization and digitization of the energy sector convoyed by the emersion of new technologies such as blockchain, Internet of Things (IoT), and Artificial Intelligence (AI), opened the door to new solutions for the energy demand dilemma. Among these technologies, blockchain has proved itself as a decentralized trading platform between untrusted peers without the involvement of a trusted third party. This newly introduced Peer-to-Peer (P2P) trading model can be used to create a new demand load control model. In this article, the concept of an energy cap and trade demand-side management (DSM) model is introduced and simulated. The introduced DSM model is based on the concept of capping consumers’ monthly energy consumption and rewarding consumers who do not exceed this cap with energy tradeable credits that can be traded using blockchain-based Peer-to-Peer (P2P) energy trading. A model based on 200 households is used to simulate the proposed DSM model and prove that this model can be beneficial to both energy companies and consumers.

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Meer Shadman Shafkat, Tanjim, Rahman Md. Abdur, and Oishi Ashrafun Nushra. "Advanced Supervisory Control Plan with Power Saving Strategy for Demand Side Load." AIUB Journal of Science and Engineering (AJSE) 18, no. 3 (December 31, 2019): 108–16. http://dx.doi.org/10.53799/ajse.v18i3.38.

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Demand Side Power Management is getting crucial to control the gradual rise of electrical power usage day-by-day. Though, the spread of power saving devices is a huge success throughout the world, yet the demand side power management system have to be more efficient and controlled. Here, an unique power saving strategy was established by intranet based Advanced Supervisory Control system. The core system consists of XPSU, XCU, PBU, DS and ASC. Planning of this system has been done not only to solve the above-mentioned criteria but also to reduce huge electricity demand from national grid. To reduce the National Grid pressure, full utilization of renewable energy grid output is ensured in this strategy. By this Control Plan, maximum 31.9% of the instantaneous power has been saved by 11.11% of System-end ASC Switching. A new idea, Electrical Mapping is also introduced for every different load section; by which the load behavior and power consumption history of our different load site area can be understood.

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Journal articles on the topic 'Efficient demand side management'

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