Probabilistic Short Circuit Ratio Calculation of Multiple Renewable Energy Stations in Power Systems Using Maximum Entropy Principle

JIANG Tao; CHEN Shun; WANG Changjiang; LIU Xianchao; LI Guoqing

doi:10.13334/j.0258-8013.pcsee.241228

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Probabilistic Short Circuit Ratio Calculation of Multiple Renewable Energy Stations in Power Systems Using Maximum Entropy Principle

更新时间：2026-01-04

- Probabilistic Short Circuit Ratio Calculation of Multiple Renewable Energy Stations in Power Systems Using Maximum Entropy Principle
- Issue 23, Pages: 9266-9279(2025)
- 作者机构：
  
  现代电力系统仿真控制与绿色电能新技术教育部重点实验室(东北电力大学),吉林市,吉林省,132012
- 作者简介：
- 基金信息：
- DOI：10.13334/j.0258-8013.pcsee.241228
  CLC：
- Published：2025
- 稿件说明：
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JIANG Tao, CHEN Shun, WANG Changjiang, et al. Probabilistic Short Circuit Ratio Calculation of Multiple Renewable Energy Stations in Power Systems Using Maximum Entropy Principle[J]. 2025, (23): 9266-9279.
DOI：

JIANG Tao, CHEN Shun, WANG Changjiang, et al. Probabilistic Short Circuit Ratio Calculation of Multiple Renewable Energy Stations in Power Systems Using Maximum Entropy Principle[J]. 2025, (23): 9266-9279. DOI： 10.13334/j.0258-8013.pcsee.241228.

摘要

为准确、快速评估风电出力不确定性对电网强度的影响，该文提出一种基于最大熵原理的新能源多场站短路比(multiple renewable energy stations short circuit ratio，MRSCR)概率评估方法。首先，推导MRSCR对节点注入功率的灵敏度，以量化风电出力波动性对MRSCR的影响程度；然后，根据风电出力概率分布和MRSCR对节点注入功率灵敏度，计算MRSCR的半不变量和中心矩；进一步，将MRSCR各阶中心矩代入最大熵模型的约束条件中，构建基于最大熵原理的MRSCR概率密度求解模型，求得各风电并网点的MRSCR概率密度，进而实现MRSCR的概率评估；最后，通过修改后新英格兰39节点测试系统和吉林西部实际系统的仿真分析，验证采用所提方法进行MRSCR概率评估的准确性和有效性。

Abstract

This paper proposes a multiple renewable energy stations short circuit ratio (MRSCR) calculation of multiple renewable energy stations using the maximum entropy principle to evaluate the impact of uncertainty of wind power output on the grid strength. First

the sensitivity of MRSCR is derived to quantify the impact of wind power on the MRSCR. Then

the cumulants and central moments of MRSCR are calculated with the probability distribution of wind power output and the sensitivity of MRSCR. Furthermore

the central moments of each order of MRSCR are brought into the constraint conditions of the maximum entropy model

and the probability density solution model of MRSCR based on the maximum entropy principle is constructed. Then

the probability density of MRSCR at each bus connected to the wind farm can be calculated. Finally

the performance of the proposed method is evaluated by the modified New England 39-bus test system and the western Jilin power systems; the results confirm the accuracy and effectiveness of the proposed method in the probabilistic MRSCR calculation.

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