4.7 Article

Optimization analysis of energy storage application based on electricity price arbitrage and ancillary services

Journal

JOURNAL OF ENERGY STORAGE
Volume 55, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.est.2022.105508

Keywords

Energy storage system; Electricity price arbitrage; Ancillary services; Genetic algorithm; Operation strategy

Categories

Funding

  1. Beijing Natural Science Foundation [JQ21010]
  2. National Science Fund for Distinguished Young Scholars [51925604]
  3. National Key Research and Development Program of China [2018YFE0117300]
  4. International Partnership Program, Bureau of International Cooperation of Chinese Academy of Sci-ences [182211KYSB20170029]
  5. Newton Advanced Fellowship [NA170093]

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Energy storage is a key factor in promoting renewable energy development. The coupling of battery energy storage systems (BESS) with renewable energy can generate additional revenue through arbitrage and auxiliary services. This study investigates the technical and economic performance of such a coupling system and develops a multi-objective three-level model for the optimal configuration of BESS.
Energy storage is an effective way to facilitate renewable energy (RE) development. Its technical performance and economic performance are key factors for large scale applications. As battery energy storage system (BESS) is one commercially-developed energy storage technology at present, BESS is utilized to connect to RE generation. BESS couple with RE can balance the generation and load, and provide auxiliary services. Thus, the technical and economic performance of this coupling system was investigated. The coupling system generates extra revenue compared to RE-only through arbitrage considering peak-valley electricity price and ancillary services. In order to maximize the net revenues of BESS, a multi-objective three-level model for the optimal configuration of BESS was developed. The outer layer was a model for the optimal configuration of BESS, the middle layer was a multi -objective optimal model for BESS to participate in electricity price arbitrage and reserve ancillary services, and the inner layer was an optimal scheduling model that coordinated wind power, photovoltaic (PV) power and BESS. The multi-objective genetic algorithm (GA) based on the roulette method was employed to solve the optimal model. A case study was conducted, and the annual net revenues of BESS under different BESS capacities were evaluated. When the annual net revenues of BESS reach the maximum, the optimal BESS capacity is ob-tained. Sensitive analysis was also conducted considering different price difference, environment conditions of irradiance, wind speed. The effective trend and optimization values were calculated. The study presented a solution including methodology and values for how to determine the installation of energy storage to RE.

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