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Energies 2014, 7(11), 7499-7518; doi:10.3390/en7117499

Game-Theoretic Energy Management for Residential Users with Dischargeable Plug-in Electric Vehicles

School of Electrical Engineering, Southeast University, No. 2, Sipailou, Nanjing 210096, Jiangsu, China
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Received: 2 September 2014 / Revised: 4 November 2014 / Accepted: 7 November 2014 / Published: 18 November 2014
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Abstract

The plug-in electric vehicle (PEV) has attracted more and more attention because of the energy crisis and environmental pollution, which is also the main shiftable load of the residential users’ demand side management (DSM) system in the future smart grid (SG). In this paper, we employ game theory to provide an autonomous energy management system among residential users considering selling energy back to the utility company by discharging the PEV’s battery. By assuming all users are equipped with smart meters to execute automatic energy consumption scheduling (ECS) and the energy company can adopt adequate pricing tariffs relating to time and level of energy usage, we formulate an energy management game, where the players are the residential users and the strategies are their daily schedules of household appliance use. We will show that the Nash equilibrium of the formulated energy management game can guarantee the global optimization in terms of minimizing the energy costs, where the depreciation cost of PEV’s battery because of discharging and selling energy back is also considered. Simulation results verify that the proposed game-theoretic approach can reduce the total energy cost and individual daily electricity payment. Moreover, since plug-in electric bicycles (PEBs) are currently widely used in China, simulation results of residential users owing household appliances and bidirectional energy trading of PEBs are also provided and discussed. View Full-Text
Keywords: plug-in electric vehicle; game theory; plug-in electric bicycle; demand side management; energy consumption scheduling plug-in electric vehicle; game theory; plug-in electric bicycle; demand side management; energy consumption scheduling
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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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MDPI and ACS Style

Gao, B.; Zhang, W.; Tang, Y.; Hu, M.; Zhu, M.; Zhan, H. Game-Theoretic Energy Management for Residential Users with Dischargeable Plug-in Electric Vehicles. Energies 2014, 7, 7499-7518.

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