4.7 Article

Prosumer Community: A Risk Aversion Energy Sharing Model

Journal

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 11, Issue 2, Pages 828-838

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2019.2909301

Keywords

Games; Stochastic processes; Real-time systems; Energy management; Blockchain; Photovoltaic systems; Prosumer; community photovoltaic; risk aversion; energy sharing; stochastic game; SWAA equilibrium; blockchain

Funding

  1. National Natural Science Foundation of China [61773172, 61572210, 51537003]
  2. Natural Science Foundation of Hubei Province of China [2017CFA035]
  3. Fundamental Research Funds for the Central Universities [2018KFYYXJJ119]
  4. academic frontier youth team of HUST

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Household photovoltaic (HPV) prosumers and the community photovoltaic (CPV) system have been growing rapidly with the development of the sustainable technology. The uncertainties of these distributed renewable energy resources bring a significant challenge to the design of power-market mechanism and the energy dispatch of the power system for promoting energy efficiency. It is essential to develop a novel efficient energy management strategy for addressing this challenge from the perspective of community prosumers. Accordingly, a risk aversion energy sharing model based on a devised local energy market is presented. A stochastic game is established to minimize prosumers' energy costs and the weighted conditional value-at-risk of energy sharing loss of uncertain CPV through optimal energy sharing profiles. The household loads and HPV outputs are considered as stochastic parameters in the game model. Moreover, a sample weighted average approximation (SWAA) method is proposed for a better estimation of the stochastic game while the SWAA equilibrium is obtained by a relaxation method-based algorithm with theoretical proof. In addition, the blockchain technology is introduced as a distributed and secure way to facilitate the energy sharing model. The case studies show the efficiency of the proposed energy sharing model and the algorithm.

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