Bargaining Game-Based Profit Allocation of Virtual Power Plant in Frequency Regulation Market Considering Battery Cycle Life

Distributed energy resources (DERs) such as rooftop photovoltaic (PV) systems, battery energy storage systems (BESSs), and controllable loads can be aggregated as virtual power plants (VPPs) to provide frequency regulation services for managing power system stability. Optimizing the profits of PV-BESS VPPs in frequency control markets can demonstrate their profitability and encourage more PV-BESS consumers to join VPPs to support the grid. This article proposes an optimal bidding strategy of a PV-BESS VPP in frequency control ancillary services (FCAS) markets, and a joint bidding strategy of the VPP in cooperation with a wind farm, which aims to maximize their cooperation profits. Moreover, the battery cycle life is systematically considered and incorporated in the proposed bidding models. In addition, a payoff allocation approach based on Nash–Harsanyi Bargaining Solution is innovatively developed to allocate the extra profit of the cooperation. The proposed approach is expected to allocate the VPP with a reasonable share and reflect its real contribution in cooperation. The simulation results verify the feasibility and effectiveness of the proposed bidding models and the payoff allocation approach.

[1]  Jing Qiu,et al.  Carbon-Oriented Operational Planning in Coupled Electricity and Emission Trading Markets , 2020, IEEE Transactions on Power Systems.

[2]  J. Nash.  THE BARGAINING PROBLEM , 1950, Classics in Game Theory.

[3]  Aitor Milo,et al.  Annual Optimized Bidding and Operation Strategy in Energy and Secondary Reserve Markets for Solar Plants With Storage Systems , 2019, IEEE Transactions on Power Systems.

[4]  Xu Wang,et al.  Robust Bidding Strategy and Profit Allocation for Cooperative DSR Aggregators With Correlated Wind Power Generation , 2019, IEEE Transactions on Sustainable Energy.

[5]  Lei Fan,et al.  A Data-Driven Model of Virtual Power Plants in Day-Ahead Unit Commitment , 2019, IEEE Transactions on Power Systems.

[6]  Lalit Goel,et al.  A Two-Layer Energy Management System for Microgrids With Hybrid Energy Storage Considering Degradation Costs , 2018, IEEE Transactions on Smart Grid.

[7]  Kameshwar Poolla,et al.  Cooperation of Wind Power and Battery Storage to Provide Frequency Regulation in Power Markets , 2017, IEEE Transactions on Power Systems.

[8]  Jing Qiu,et al.  Two-Stage Coordinated Operational Strategy for Distributed Energy Resources Considering Wind Power Curtailment Penalty Cost , 2017 .

[9]  Hamidreza Zareipour,et al.  Operation Scheduling of Battery Storage Systems in Joint Energy and Ancillary Services Markets , 2017, IEEE Transactions on Sustainable Energy.

[10]  Yingchen Zhang,et al.  Coordinated Control Strategy of a Battery Energy Storage System to Support a Wind Power Plant Providing Multi-Timescale Frequency Ancillary Services , 2017, IEEE Transactions on Sustainable Energy.

[11]  Chongqing Kang,et al.  Optimal Bidding Strategy of Battery Storage in Power Markets Considering Performance-Based Regulation and Battery Cycle Life , 2016, IEEE Transactions on Smart Grid.

[12]  Peter Bazan,et al.  SWARM - strategies for providing frequency containment reserve power with a distributed battery storage system , 2016, 2016 IEEE International Energy Conference (ENERGYCON).

[13]  Bala Venkatesh,et al.  Short-term scheduling of thermal generators and battery storage with depth of discharge-based cost model , 2015, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[14]  Ratnesh K. Sharma,et al.  A joint bidding and operation strategy for battery storage in multi-temporal energy markets , 2015, 2015 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT).

[15]  Saeed Rahmani Dabbagh,et al.  Risk-based profit allocation to DERs integrated with a virtual power plant using cooperative Game theory , 2015 .

[16]  Jinyu Wen,et al.  Coordinated Control Strategy of Wind Turbine Generator and Energy Storage Equipment for Frequency Support , 2014, IEEE Transactions on Industry Applications.

[17]  Songli Fan,et al.  An innovative profit allocation to distributed energy resources integrated into virtual power plant , 2015 .

[18]  Dragan Maksimovic,et al.  Accounting for Lithium-Ion Battery Degradation in Electric Vehicle Charging Optimization , 2014, IEEE Journal of Emerging and Selected Topics in Power Electronics.

[19]  Remus Teodorescu,et al.  Primary Frequency Regulation with Li-Ion Battery Energy Storage System - Evaluation and Comparison of Different Control Strategies , 2013 .

[20]  Duong Tran,et al.  Energy Management for Lifetime Extension of Energy Storage System in Micro-Grid Applications , 2013, IEEE Transactions on Smart Grid.

[21]  S. M. Moghaddas-Tafreshi,et al.  Bidding Strategy of Virtual Power Plant for Participating in Energy and Spinning Reserve Markets—Part I: Problem Formulation , 2011, IEEE Transactions on Power Systems.

[22]  C. N. Rasmussen,et al.  Generic modelling framework for economic analysis of Battery Systems , 2011 .

[23]  José L. Bernal-Agustín,et al.  Generation management using batteries in wind farms: Economical and technical analysis for Spain , 2009 .

[24]  Langford B. White,et al.  Cooperative resource allocation games in shared networks: symmetric and asymmetric fair bargaining models , 2008, IEEE Transactions on Wireless Communications.

[25]  A. Rubinstein,et al.  The Nash bargaining solution in economic modelling , 1985 .

[26]  A. Roth.  Axiomatic models of bargaining , 1979 .

[27]  R. Selten,et al.  A Generalized Nash Solution for Two-Person Bargaining Games with Incomplete Information , 1972 .

[28]  J. Harsanyi.  Games with Incomplete Information Played by 'Bayesian' Players, Part III. The Basic Probability Distribution of the Game , 1968 .