Demand-Side Management With Household Plug-In Electric Vehicles: A Bayesian Game-Theoretic Approach

Liu, Xiaofeng; Gao, Bingtuan; Wei, Cheng; Tang, Yi

doi:10.1109/jsyst.2017.2741719

Cited by 56 publications

(27 citation statements)

References 29 publications

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“…We can evaluate the effectiveness of proposed approach in peak load leveling by introducing peak to average ratio (PAR). PAR is calculated as [36]…”

Section: Results Of Energy Schedulingmentioning

confidence: 99%

Energy Management for Community Energy Network with CHP Based on Cooperative Game

Liu

Wang²,

Sun³

2018

Energies

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Integrated energy system (IES) has received increasing attention in micro grid due to the high energy efficiency and low emission of carbon dioxide. Based on the technology of combined heat and power (CHP), this paper develops a novel operation mechanism with community micro turbine and shared energy storage system (ESS) for energy management of prosumers. In the proposed framework, micro-grid operator (MGO) equipped with micro turbine and ESS provides energy selling business and ESS leasing business for prosumers. Prosumers can make energy trading with public grid and MGO, and ESS will be shared among prosumers when they pay for the rent to MGO. Based on such framework, we adopt a cooperative game for prosumers to determine optimal energy trading strategies from MGO and public grid for the next day. Concretely, a cooperative game model is formulated to search the optimal strategies aiming at minimizing the daily cost of coalition, and then a bilateral Shapley value (BSV) is proposed to solve the allocation problem of coalition's cost among prosumers. To verify the effectiveness of proposed energy management framework, a practical example is conducted with a community energy network containing MGO and 10 residential buildings. Simulation results show that the proposed scheme is able to provide financial benefits to all prosumers, while providing peak load leveling for the grid.

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“…We can evaluate the effectiveness of proposed approach in peak load leveling by introducing peak to average ratio (PAR). PAR is calculated as [36]…”

Section: Results Of Energy Schedulingmentioning

confidence: 99%

Energy Management for Community Energy Network with CHP Based on Cooperative Game

Liu

Wang²,

Sun³

2018

Energies

Self Cite

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“…can be rewritten as (13). Obviously, (13) denotes that the expected utility function of MG n is sum of combination which all MG include itself under all possible role type combination.…”

Section: Utility Functions For Bayesian Gamementioning

confidence: 99%

“…Since much information in reality is unknown to all or many players refuse to share their private information, the complete game approach is not suitable for the situation with incomplete information. Bayesian game approach is formulated for the proposed scenario with incomplete information to reduce users' daily cost, and existence of Bayesian Nash equilibrium is proved mathematically in [13]. The scenario is proposed for DSM programs to schedule household energy consumption considering bidirectional energy trading of PEVs, in which the charging cost and discharging profit of PEVs are not public information among different communities.…”

Section: Introductionmentioning

confidence: 99%

A Game Theoretical Pricing Mechanism for Multi-Microgrid Energy Trading Considering Electric Vehicles Uncertainty

2020

IEEE Access

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The electricity price mechanism based on game theory is one of the research focuses on microgrids energy trading. The complete information game is based on the certainty of the identity of roles of players and variables. However, there are many uncertain factors that cause the game in the state of incomplete information. In this paper, Microgrids Energy Trading Bayesian Game (METBG) model is proposed. The model was based on the Bayesian game, in which MGs make their decision as an agent of native users to tackle bidirectional energy trading between others. First, The Bayesian game modeled types of roles of players by the uncertainty of information including the stochastic characteristics of PEVs which result in hardness that the game participants determine whether they are sellers or buyers in the utility function that depends on the state of power surplus or lack. Moreover, the utility model of players was established by a Bayesian game with the game equilibrium derived rigorously by obligated to coordinate the sharing of energy with maximization of the players' profit. Finally, the solution of game equilibrium has been rigorously derived, and the effectiveness of the model is verified in terms of seller profit, the utilities of buyers, and the net energy usage in the microgrids. The results of the static pricing model and proposed model were compared to demonstrate the effectiveness. INDEX TERMS Multi-microgrid; Electric vehicles; Energy trading; Bayesian game

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“…Certainly, in addition to the above research work, scholars also investigate how to promote the use of EVs by the power consumers to participate in power DR between electricity user side and electricity seller side. For instance, researchers in [52] and [56] investigate how to use EVs as a medium for trading between the electricity user side and electricity seller side (e.g., power grid companies, emerging electricity sales companies, EV aggregators, load aggregators), and use the multi-agent game mechanism to obtain the Nash equilibrium of electricity users participating in the EM transaction through the EV charging and discharging strategies. However, although the researchers in [55] adopt the noncooperative game method to optimize the trading strategy, they do not consider the transferability and uncertainty of user's other loads.…”

Section: ) Power Dr Between Electricity User Side and Electricity Sementioning

confidence: 99%

Game-Theoretic Approaches Applied to Transactions in the Open and Ever-Growing Electricity Markets From the Perspective of Power Demand Response: An Overview

Cheng

2019

IEEE Access

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This paper conducts a detailed overview on game-theoretic approaches for power demand response (DR) in the open and ever-growing electricity market (EM) in terms of three major categories of games, including non-cooperative game, cooperative game, and evolutionary game. In addition, we also separately review the Stackelberg game and Bayesian game in power DR. First, we briefly describe the main contents of game theory and the game behaviors of the electricity sellers, electricity suppliers, and electricity users in EM. Second, we comprehensively introduce the principle of the above-mentioned five categories of games and thoroughly review their applications in power DR in the context of open EMs, considering the transactions such as electricity pricing and electricity capacity trading among the electricity supplier side, electricity seller side, and electricity user side in the perfect open EMs, such as retail market, spot market, wholesale market, and ancillary service market. In this survey, aiming at each type of game mentioned above, we try to summarize the advantages and shortcomings of their application in EM in terms of power DR, as well as the issues that need to be solved currently or in the future. Finally, we offer some prospects on the scenario application and future development of game-theoretic approaches for power DR in an open EM. The biggest innovation of this paper lies in conducting a comprehensive survey on game-theoretic approaches applied to transactions in the open and ever-growing EMs from the perspective of power DR in terms of five major categories of games. We conduct this survey intended to arouse the interest and excitement of experts and scholars in the energy and electric power system industry and to look ahead to efforts that jointly promote the rapid development of game theory in the perfect open EM field.

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Demand-Side Management With Household Plug-In Electric Vehicles: A Bayesian Game-Theoretic Approach

Cited by 56 publications

References 29 publications

Energy Management for Community Energy Network with CHP Based on Cooperative Game

Energy Management for Community Energy Network with CHP Based on Cooperative Game

A Game Theoretical Pricing Mechanism for Multi-Microgrid Energy Trading Considering Electric Vehicles Uncertainty

Game-Theoretic Approaches Applied to Transactions in the Open and Ever-Growing Electricity Markets From the Perspective of Power Demand Response: An Overview

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