Electric Power ›› 2023, Vol. 56 ›› Issue (12): 147-155, 163.DOI: 10.11930/j.issn.1004-9649.202302038

• Planning and Operation Technologies for Multi-Energy Systems in Low-Carbon Parks • Previous Articles     Next Articles

Optimal Allocation of Energy Storage Capacity in High Proportion Clean Energy Parks Considering Demand Response

Zhaojun JIANG1(), Yue XIANG1(), Zhukui TAN2, Yongtao GUO1, Yang WANG2, Ke ZHOU2   

  1. 1. College of Electrical Engineering, Sichuan University, Chengdu 610065, China
    2. Electric Power Research Institute of Guizhou Power Grid Co., Ltd., Guiyang 550002, China
  • Received:2023-02-10 Accepted:2023-05-11 Online:2023-12-23 Published:2023-12-28
  • Supported by:
    This work is supported by the National Key Research and Development Program of China (Multi-energy System Coordination and Carbon Management in Low-carbon Park, No.2022YFE0205300).

Abstract:

In order to improve the level of clean energy consumption and the economy of energy storage allocation in parks, an optimal allocation method for energy storage capacity of high-proportion clean energy parks considering demand response is proposed. Firstly, the photovoltaic, wind turbine, and energy storage power models are established. Secondly, a demand response mechanism considering the participation of rigid, transferable and interruptible loads is designed to realize the transfer of loads under a certain time scale. Then, taking the lowest total net present cost of the system as the optimization goal, an energy storage economic allocation model is established with consideration of the constraints such as grid-connected power fluctuations and charge & discharge limits. Case study verifies the effectiveness of the proposed method, and the results show that compared to the traditional method, the proposed allocation method can effectively reduce the economic cost of the system and improve the level of clean energy consumption.

Key words: energy storage capacity configuration, flexible load adjustment capacity, grid-connected power change constraints, clean energy consumption level, demand response