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Design of structured control policy for shared energy storage in residential community: A stochastic optimization approach

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  • Walker, Awnalisa
  • Kwon, Soongeol

Abstract

For energy storage shared by multiple residential consumers who are using electricity based on time-varying price and equipped with solar photovoltaic panels, this study is motivated to design an efficient control policy that allows individual consumers to determine operational decisions to realize economic and feasible energy sharing. Although shared energy storage has been considered a promising and practical solution for sharing energy, a proper control policy is required for realizing the expected benefits and advantages of energy sharing via shared energy storage because of the stochastic nature of fluctuated electricity demand load, intermittent solar power generation, and time-varying electricity price in addition to the complex dynamics existing in consumers’ behavior. This study intends to design a structured control policy that is uniquely designed to allow consumers to share energy with energy cost-saving and less solar power spillage. We develop a mathematical optimization model that can be formulated to efficiently find the designed control policy. Numerical experiments are conducted by simulating the derived control policy using real historical data comprising 14 residential houses in New York and 11 residential houses in Texas. Through the numerical experiments, we validate the feasibility and evaluate the performance of the proposed control policy to demonstrate the practicality. The results of the numerical experiments show that the proposed control policy enables consumers to cost-efficiently share energy while efficiently utilizing solar power generation to meet their electricity demand load without the excessive use of electricity from the grid to save energy costs.

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  • Walker, Awnalisa & Kwon, Soongeol, 2021. "Design of structured control policy for shared energy storage in residential community: A stochastic optimization approach," Applied Energy, Elsevier, vol. 298(C).
    • Handle: RePEc:eee:appene:v:298:y:2021:i:c:s0306261921006097
    DOI: 10.1016/j.apenergy.2021.117182
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    7. Du, Sipeng & Wu, Di & Dai, Zhong & Li, Guiqiang & Lahaxibai, Shala, 2023. "Regional collaborative planning equipped with shared energy storage under multi-time scale rolling optimisation method," Energy, Elsevier, vol. 277(C).

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