Electric Power ›› 2022, Vol. 55 ›› Issue (8): 64-72.DOI: 10.11930/j.issn.1004-9649.202201088

• Application of Key Technologies of Energy Storage in New Power System • Previous Articles     Next Articles

Research on Economic Scheduling of ES Peak and Frequency Regulation Based on Dynamic Peak-Valley Time Division

WANG Yali1,2, YE Ze1,2, HUANG Jiyuan3, WEI Wen4, DAI Shuangfeng1,2, ZHANG Bingyu5   

  1. 1. School of Economics and Management, Changsha University of Science and Technology, Changsha 410114, China;
    2. China Electricity Price Research Center, Changsha University of Science and Technology, Changsha 410114, China;
    3. State Grid Hunan Changsha Power Supply Company, Changsha 410015, China;
    4. School of Economics & Management, Hunan Institute of Science and Technology, Yueyang 414000, China;
    5. State Grid Zhejiang Huzhou Deqing Power Supply Company, Huzhou 310000, China
  • Received:2022-01-24 Revised:2022-06-27 Online:2022-08-28 Published:2022-08-18
  • Supported by:
    This work is supported by Philosophy and Social Science Fund of Hunan Province (No.17JD02, No.18JD02, No.20YBQ004), Outstanding Youth Program of Hunan Provincial Department of Education (No.20B027, No.19B024), Hunan Enterprise Management and Investment Research Base Project (No.18qytzyb3), Foundation of Hunan Intelligent Accounting and Engineering Application Research Center (No.20ckyb03), Project of Hunan Modern Enterprise Management Research Center(No.17qgyb02, No.17qgyb03), Science and Technology Project of State Grid Hunan Electric Power Co., Ltd. (No.5216A12101YJ).

Abstract: In order to effectively utilize energy storage (ES) devices and improve the accuracy of ES’s switching between multi-application scenarios, this paper proposes a peak-valley time division method based on equal capacity after analyzing ES’s multi-application scenarios and tries to improve the peak-valley time division. In addition, an economically optimized model of ES multi-application scenarios is constructed based on dynamic peak-valley time division, which employs ES to suppress load fluctuation during non-peak regulation, makes ES function normally even in idle hours, and improves ES’s utilization rate and economic benefits. Finally, the simulation analysis shows that compared with the economic model of monotonic peak regulation, the economically optimized model of ES multi-application scenarios can reduce the payback period by 1.17 years. Furthermore, compared with the monotonic peak time division, the dynamic peak-valley time division method can shorten the payback period by 1.75 years, which verifies the feasibility of the method.

Key words: energy storage, peak-valley time, multi-application scenario, economic optimization