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

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.Energies 2014, 7 7500

Game-theoretic energy management with storage capacity optimization in the smart grids

“…Hence the time slot of the discharging battery is from 17:00 to 22:00. The maximum energy charged/discharged to/from the battery in an hour are both 1.5 kWh; charging and discharging efficiency of the battery are both 92% [9]; daily depreciation cost of the battery is assumed to be 7.2 cents/kWh [20]. More details about parameters in the simulation can be found in Tables 1 and 2.…”

“…where x Àn ¼ x 1 ; Á Á Á ; x nÀ1 ; x nþ1 ; Á Á Á ; x N ½ denotes the energy demand across all users except user n. According to (9), residential users can reduce their energy cost by using the following approaches: 1) making the best use of the PV-battery system to reduce the energy purchased from the utility company; 2) shifting loads from peak hours to offpeak hours to avoid the higher energy price.…”

“…Based on the above assumptions, a quadratic cost function is utilized in most of the literature due to the nature of the increasing and strictly convex function [9,30], and the function is: Fig. 1 A scenario contains N residential users with smart meters, a PV-storage system, information network, and power line Game-theoretic energy management with storage capacity optimization in the smart grids…”

“…In order to improve the functions of smart grids on the demand side, the concept of demand-side management (DSM) is proposed to reduce the energy cost of consumers, shift energy consumption from peak hours to reduce peakto-average ratio (PAR) and balance power supply and demand [7][8][9]. DSM programs can be conducted effectively primarily due to their dynamic pricing schemes such as time-of-use (ToU) pricing [10], real-time pricing (RTP) [11] and critical-peak pricing.…”

A Novel Electric Bicycle Battery Monitoring System Based on Android Client

“…The popularity rate of electric bicycles has also been expanding gradually. In many countries and regions with a dense population, such as California in the United States, Central and Southeast China, and Japan and other Southeast Asian countries, the electric bicycle is generally used in urban traffic as a form of short-range transportation [6][7][8].…”