Proceedings ArticleDOI
Particle swarm optimization for demand side management in smart grid
Thillainathan Logenthiran,Dipti Srinivasan,Ei Phyu +2 more
- pp 1-6
TLDR
In this paper, a new load shifting approach for demand side management in smart grid energy management is discussed, which 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.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.read more
Citations
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Journal ArticleDOI
Towards Sustainable Energy-Efficient Communities Based on a Scheduling Algorithm.
TL;DR: A cooperative DR system is designed not only to bolster energy efficiency management at both home and district levels, but also to integrate the renewable energy resource information into the community’s energy management.
Journal ArticleDOI
A DSM Approach for Distribution Systems with High Wind Power Penetration
TL;DR: Demand side management (DSM) as mentioned in this paper shifts load from peak hours to off-peak hours and reduces consumption during peak hours by shifting load from one time slot to another time slot.
Proceedings ArticleDOI
Particle Swarm Optimization based Cost Optimization for Demand Side Management in Smart Grid
TL;DR: Particle Swarm Optimization algorithm is used to optimize generation and load pattern of a day-ahead market in order to optimize electricity cost for demand side management and the proposed approach provides better result and all the participants get cost benefit.
Journal ArticleDOI
An explorative optimization algorithm for sparse scheduling in-home energy management with smart grid
Viswanath Gajula,R. Rajathy +1 more
TL;DR: This proposed algorithm offered the greatest fulfillment and least expense caused by the consumers when compared to the traditional cost by taking the individual consumer preferences for the loads and the ideal time scheduling for the load, which is obtained from the rebuilding trap.
Proceedings ArticleDOI
Computational Intelligence Techniques in Smart grid planning and operation: A Survey
TL;DR: This paper aims to provide a survey of the works related to some of the smart grid components and classifies the works based on the computational intelligence tools used in solving the planning or operation problem.
References
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Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Journal Article
Microgrids management
TL;DR: Depending on the type and depth of penetration of distributed energy resource units, load characteristics and power quality constraints, and market participation strategies, the required control and operational strategies of a microgrid can be significantly, and even conceptually, different than those of the conventional power systems.
Journal ArticleDOI
Demand Side Management in Smart Grid Using Heuristic Optimization
TL;DR: A heuristic-based Evolutionary Algorithm that easily adapts heuristics in the problem was developed for solving this minimization problem and results show that the proposed demand side management strategy achieves substantial savings, while reducing the peak load demand of the smart grid.
Proceedings ArticleDOI
Optimal Real-Time Pricing Algorithm Based on Utility Maximization for Smart Grid
TL;DR: This paper analytically model the subscribers' preferences and their energy consumption patterns in form of carefully selected utility functions based on concepts from microeconomics and proposes a distributed algorithm which automatically manages the interactions among the ECC units at the smart meters and the energy provider.
Journal ArticleDOI
Advanced Demand Side Management for the Future Smart Grid Using Mechanism Design
TL;DR: Simulation results confirm that the proposed pricing method can benefit both users and utility companies and verify some important properties of the proposed VCG mechanism for demand side management such as efficiency, user truthfulness, and nonnegative transfer.