The Experts below are selected from a list of 434934 Experts worldwide ranked by ideXlab platform

Tan Zong Shun - One of the best experts on this subject based on the ideXlab platform.

  • Demand side Management in smart grid using heuristic optimization
    IEEE Transactions on Smart Grid, 2012
    Co-Authors: Thillainathan Logenthiran, Dipti Srinivasan, Tan Zong Shun
    Abstract:

    Demand side Management (DSM) is one of the important functions in a smart grid that allows customers to make informed decisions regarding their energy consumption, and helps the energy providers reduce the peak load demand and reshape the load profile. This results in increased sustainability of the smart grid, as well as reduced overall operational cost and carbon emission levels. Most of the existing demand side Management strategies used in traditional energy Management systems employ system specific techniques and algorithms. In addition, the existing strategies handle only a limited number of controllable loads of limited types. This paper presents a demand side Management strategy based on load shifting technique for demand side Management of future smart grids with a large number of devices of several types. The day-ahead load shifting technique proposed in this paper is mathematically formulated as a minimization problem. A heuristic-based Evolutionary Algorithm (EA) that easily adapts heuristics in the problem was developed for solving this minimization problem. Simulations were carried out on a smart grid which contains a variety of loads in three service areas, one with residential customers, another with commercial customers, and the third one with industrial customers. The simulation results show that the proposed demand side Management strategy achieves substantial savings, while reducing the peak load demand of the smart grid.

Jianhui Wang - One of the best experts on this subject based on the ideXlab platform.

  • Efficient Computation for Sparse Load Shifting in Demand Side Management
    IEEE Transactions on Smart Grid, 2017
    Co-Authors: Chaojie Li, Wenwu Yu, Xinghuo Yu, Guo Chen, Jianhui Wang
    Abstract:

    This paper introduces a distributed algorithm for sparse load shifting in Demand-Side Management with a focus on the scheduling problem of residential smart appliances. By the sparse load shifting strategy, customers’ discomfort is reduced. Although there are many game theoretic models for the Demand-Side Management problem, the computational efficiency of finding Nash equilibrium that globally minimizes the total energy consumption cost and the peak-to-average ratio is still an outstanding issue. We develop a bidirectional framework for solving the Demand-Side Management problem in a distributed way to substantially improve the search efficiency. A Newton method is employed to accelerate the centralized coordination of demand side Management strategies that superlinearly converge to a better Nash equilibrium minimizing the peak-to-average ratio. Furthermore, dual fast gradient and convex relaxation are applied to tackle the sub-problem for customers’ best response, which is able to relieve customers’ discomfort from load shifting or interrupting. Detailed results from illustrative case studies are presented and discussed, which shows the costs of energy consumption and daily peak demand by our algorithm are reduced. Finally, some conclusions are drawn.

Thillainathan Logenthiran - One of the best experts on this subject based on the ideXlab platform.

  • Particle swarm optimization for demand side Management in smart grid
    2015 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA), 2015
    Co-Authors: Thillainathan Logenthiran, Dipti Srinivasan, Ei Phyu
    Abstract:

    Demand side Management is a useful and necessary tool in smart grid energy Management system to reduce total power demand during peak demand periods and hence, enhancing grid sustainability and reducing overall cost. This paper discusses a new load shifting approach for demand side Management in smart grid energy Management. This approach optimizes the consumption curves of household, commercial and industrial consumers. The proposed algorithm in this approach minimizes the cost incurred by users while taking into account users' individual preferences for the loads by setting priorities and preferred time intervals for load scheduling.

  • Demand side Management in smart grid using heuristic optimization
    IEEE Transactions on Smart Grid, 2012
    Co-Authors: Thillainathan Logenthiran, Dipti Srinivasan, Tan Zong Shun
    Abstract:

    Demand side Management (DSM) is one of the important functions in a smart grid that allows customers to make informed decisions regarding their energy consumption, and helps the energy providers reduce the peak load demand and reshape the load profile. This results in increased sustainability of the smart grid, as well as reduced overall operational cost and carbon emission levels. Most of the existing demand side Management strategies used in traditional energy Management systems employ system specific techniques and algorithms. In addition, the existing strategies handle only a limited number of controllable loads of limited types. This paper presents a demand side Management strategy based on load shifting technique for demand side Management of future smart grids with a large number of devices of several types. The day-ahead load shifting technique proposed in this paper is mathematically formulated as a minimization problem. A heuristic-based Evolutionary Algorithm (EA) that easily adapts heuristics in the problem was developed for solving this minimization problem. Simulations were carried out on a smart grid which contains a variety of loads in three service areas, one with residential customers, another with commercial customers, and the third one with industrial customers. The simulation results show that the proposed demand side Management strategy achieves substantial savings, while reducing the peak load demand of the smart grid.

Bo Cong - One of the best experts on this subject based on the ideXlab platform.

  • Power Demand Side Management Strategy Based on Power Demand Response
    Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019, 2020
    Co-Authors: Lianjun Song, Fengqiang Li, Bo Cong
    Abstract:

    Power demand side Management is an advanced resource planning methods and Management techniques, to promote the coordinated development of economy, resources, and environment, and to ease the power shortage, improve energy efficiency and improve efficiency and so has a very important role. This paper describes the theory of demand side Management (DSM), DSM points out the lack of process to run in present, Boot electricity customers optimize the power consumption, it helps to rational consumption, and detailed description of the specific implementation of Demand-Side Management strategies for power companies to carry out DSM has an important role in guiding and practical significance.

  • AISI - Power Demand Side Management Strategy Based on Power Demand Response
    Advances in Intelligent Systems and Computing, 2019
    Co-Authors: Lianjun Song, Bo Cong
    Abstract:

    Power demand side Management is an advanced resource planning methods and Management techniques, to promote the coordinated development of economy, resources, and environment, and to ease the power shortage, improve energy efficiency and improve efficiency and so has a very important role. This paper describes the theory of demand side Management (DSM), DSM points out the lack of process to run in present, Boot electricity customers optimize the power consumption, it helps to rational consumption, and detailed description of the specific implementation of Demand-Side Management strategies for power companies to carry out DSM has an important role in guiding and practical significance.

Chaojie Li - One of the best experts on this subject based on the ideXlab platform.

  • Efficient Computation for Sparse Load Shifting in Demand Side Management
    IEEE Transactions on Smart Grid, 2017
    Co-Authors: Chaojie Li, Wenwu Yu, Xinghuo Yu, Guo Chen, Jianhui Wang
    Abstract:

    This paper introduces a distributed algorithm for sparse load shifting in Demand-Side Management with a focus on the scheduling problem of residential smart appliances. By the sparse load shifting strategy, customers’ discomfort is reduced. Although there are many game theoretic models for the Demand-Side Management problem, the computational efficiency of finding Nash equilibrium that globally minimizes the total energy consumption cost and the peak-to-average ratio is still an outstanding issue. We develop a bidirectional framework for solving the Demand-Side Management problem in a distributed way to substantially improve the search efficiency. A Newton method is employed to accelerate the centralized coordination of demand side Management strategies that superlinearly converge to a better Nash equilibrium minimizing the peak-to-average ratio. Furthermore, dual fast gradient and convex relaxation are applied to tackle the sub-problem for customers’ best response, which is able to relieve customers’ discomfort from load shifting or interrupting. Detailed results from illustrative case studies are presented and discussed, which shows the costs of energy consumption and daily peak demand by our algorithm are reduced. Finally, some conclusions are drawn.