Application of Clausius entropy to energy storage configuration problems at multi-time scale

SUN Zhenxin; LI Haizhao; ZHANG Zhiming; MA Fubo; JIANG Congjin; ZHANG Chaoqun

doi:10.19666/j.rlfd.202404081

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Application of Clausius entropy to energy storage configuration problems at multi-time scale

更新时间：2025-09-28

- Application of Clausius entropy to energy storage configuration problems at multi-time scale
- Thermal Power Generation Vol. 53, Issue 9, Pages: 92-99(2024)
- 作者机构：
  
  国家能源集团新能源技术研究院有限公司
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202404081
  CLC： TM91
- Published：2024
- 稿件说明：
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SUN Zhenxin, LI Haizhao, ZHANG Zhiming, et al. Application of Clausius entropy to energy storage configuration problems at multi-time scale[J]. Thermal power generation, 2024, 53(9): 92-99.
DOI：

SUN Zhenxin, LI Haizhao, ZHANG Zhiming, et al. Application of Clausius entropy to energy storage configuration problems at multi-time scale[J]. Thermal power generation, 2024, 53(9): 92-99. DOI： 10.19666/j.rlfd.202404081.

摘要

“功率熵”能够定量反映多尺度储能配置的特性差异。采用2种正弦功率曲线合成的功率曲线，重点研究了调频、调峰以及跨季节调节等储能应用主要场景的熵值差异和特性。结果显示：功率熵能够有效体现不同时间尺度储能特性的差异；调频、调峰2种调节类型宜采用2套储能组合配置；对于频率和幅值差异在2倍以内的2种调节类型，则宜采用1套储能配置整体调节。该研究从理论方面探索了多时间尺度储能配置的方法和依据，揭示了多时间尺度问题的本质差异，有助于形成科学的最优储能配置、调度和优化方案。

Abstract

“Power entropy” can quantitatively reflect the characteristic difference of multi-time scale energy storage configuration. The power curve synthesized by two sinusoidal power curves is used to study the entropy difference and characteristics of main scenarios of energy storage applications such as frequency regulation

peak regulation and cross-season energy regulation. The results show that

power entropy can effectively reflect the difference of characteristics of energy storage for different time scales. For the scenarios of frequency regulation and peak regulation

using two sets of energy storage is better. For the scenarios that the difference between frequency and amplitude is less than 2 times

it is appropriate to apply a single set of energy storage. The research theoretically explores the methods and basis of multi-time scale energy storage configuration

reveals the essential differences of multi-time scale problems

it is helpful to form a scientific and optimal energy storage configuration scheme

scheduling scheme and optimization scheme.

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