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Energies 2016, 9(8), 654; doi:10.3390/en9080654

An Algorithmic Game Approach for Demand Side Management in Smart Grid with Distributed Renewable Power Generation and Storage

Department of Industrial and Information Management, National Cheng Kung University, No. 1, University Road, Tainan City 701, Taiwan
Academic Editor: Neville R. Watson
Received: 2 May 2016 / Revised: 5 August 2016 / Accepted: 6 August 2016 / Published: 18 August 2016
(This article belongs to the Collection Smart Grid)
View Full-Text   |   Download PDF [538 KB, uploaded 18 August 2016]   |  

Abstract

In this paper, the problem of minimizing electricity cost and the peak system load in smart grids with distributed renewable energy resources is studied. Unlike prior research works that either assume all of the jobs are interruptible or power-shiftable, this paper focuses on more challenging scenarios in which jobs are non-interruptible and non-power-shiftable. In addition, as more and more newly-built homes have rooftop solar arrays, it is assumed that all users are equipped with a solar-plus-battery system in this paper. Thus, power can be drawn from the battery as needed to reduce the cost of electricity or to lower the overall system load. With a quadratic load-dependent cost function, this paper first shows that the electricity cost minimization problem in such a setting is NP-hard and presents a distributed demand-side management algorithm, called DDSM, to solve this. Experimental results show that the proposed DDSM algorithm is effective, scalable and converges to a Nash equilibrium in finite rounds. View Full-Text
Keywords: smart grid; renewable energy; scheduling; demand-side management smart grid; renewable energy; scheduling; demand-side management
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Liu, R.-S. An Algorithmic Game Approach for Demand Side Management in Smart Grid with Distributed Renewable Power Generation and Storage. Energies 2016, 9, 654.

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