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Operation Strategy of Electricity Retailers Based on Energy Storage System to Improve Comprehensive Profitability in China’s Electricity Spot Market

Author

Listed:
  • Ting Lu

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
    National Institute of Clean-and-Low Carbon Energy, Beijing 102211, China)

  • Weige Zhang

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Xiaowei Ding

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Beijing Huashang Sanyou New Energy Technology Co., Ltd., Beijing 271000, China)

Abstract

Due to the development of China’s electricity spot market, the peak-shifting operation modes of energy storage devices (ESD) are not able to adapt to real-time fluctuating electricity prices. The settlement mode of the spot market aggravates the negative impact of deviation assessments on the cost of electricity retailers. This article introduces the settlement rules of China’s power spot market. According to the electricity cost settlement process and the assessment methods, this paper proposes a comprehensive electricity cost optimization algorithm that optimizes day-ahead market (DA) electricity cost, real-time market (RT) electricity cost and deviation assessment through ESD control. According to the trial electricity price data of the power trading center in Guangdong province (China), many typical load curves and different deviation assessment policies, the algorithm calculates DA electricity cost, RT electricity cost and deviation assessment cost by utilizing a comprehensive electricity cost optimization algorithm. Compared with the original electricity cost and optimization cost, this method is proven to effectively save overall electricity costs under the spot market settlement system. Based on three different initial investment prices of ESD, this paper analyzes the economics of the ESD system and proves that ESD investment can be recovered within 5 years. Considering the small amounts of operating data in China’s power spot market, the algorithm generates random data according to characteristics of these data. Then, this paper verifies that the comprehensive electricity cost optimization algorithm remains reliable under random circumstances.

Suggested Citation

  • Ting Lu & Weige Zhang & Xiaowei Ding, 2021. "Operation Strategy of Electricity Retailers Based on Energy Storage System to Improve Comprehensive Profitability in China’s Electricity Spot Market," Energies, MDPI, vol. 14(19), pages 1-25, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6424-:d:651604
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    References listed on IDEAS

    as
    1. Rui Gao & Hongxia Guo & Ruihong Zhang & Tian Mao & Qianyao Xu & Baorong Zhou & Ping Yang, 2019. "A Two-Stage Dispatch Mechanism for Virtual Power Plant Utilizing the CVaR Theory in the Electricity Spot Market," Energies, MDPI, vol. 12(17), pages 1-18, September.
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    Cited by:

    1. Zbigniew Nadolny, 2022. "Determination of Dielectric Losses in a Power Transformer," Energies, MDPI, vol. 15(3), pages 1-14, January.

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