基于模糊优化的多场景风光火储优化调度

吕游; 郭子铭; 李泽洋; 孙浩; 滕婧

doi:10.19805/j.cnki.jcspe.2026.250226

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基于模糊优化的多场景风光火储优化调度

储能专题 | 更新时间：2026-10-10

- 基于模糊优化的多场景风光火储优化调度
- Multi-scenario Wind-Solar-Thermal-Storage Optimal Scheduling Based on Fuzzy Optimization
- 动力工程学报 2026年46卷第5期页码：64-73,81
- 作者机构：
  
  1. 华北电力大学控制与计算机工程学院,北京,102206
  2. 华北电力大学新能源电力系统全国重点实验室,北京,102206
- 作者简介：
  
  吕游(1987—),男,河南项城人,教授,博士,主要从事人工智能及先进能源系统分析方面的研究。滕婧(通信作者),女,副教授,博士,E-mail:jing.teng@ncepu.edu.cn。
- 基金信息：
  
  国家自然科学基金资助项目(52476009)
- DOI：10.19805/j.cnki.jcspe.2026.250226
  中图分类号： TM732
- 纸质出版：2026
- 稿件说明：
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吕游, 郭子铭, 李泽洋, 孙浩, 滕婧. 基于模糊优化的多场景风光火储优化调度[J]. 动力工程学报, 2026, 46(5): 64-73,81.
吕游, 郭子铭, 李泽洋, 孙浩, 滕婧. 基于模糊优化的多场景风光火储优化调度[J]. 动力工程学报, 2026, 46(5): 64-73,81. DOI： 10.19805/j.cnki.jcspe.2026.250226.

DOI： 10.19805/j.cnki.jcspe.2026.250226

摘要

为了减少风光出力不确定性给电力系统优化调度带来的影响

构建了风光火储调度模型

使用场景法分别生成丰能季与枯能季典型日作为调度数据基础

并结合模糊优化方法进行优化调度。对比了不同置信水平与模糊隶属度下模型成本与备用容量之间的关系。算例验证了模糊优化与多场景调度提升了系统的稳定性与新能源消纳率。结果表明:所提优化调度方法可使新能源消纳率提高4.6%

同时调度运行成本降低2.5万元

系统稳定性有所提升。

Abstract

To mitigate the impact of the uncertainty in wind and solar power output on power system optimal scheduling

a scheduling model integrating wind

solar

thermal and storage resources was constructed. The scenario method was employed to generate typical days for both high-energy and low-energy seasons as the scheduling data basis

and fuzzy optimization method was applied for optimal scheduling. The relationship between model cost and reserve capacity under different confidence levels and fuzzy membership degrees was compared. Case studies demonstrated that fuzzy optimization and multi-scenario scheduling enhanced system stability and the accommodation rate of renewable energy. The results show that the proposed optimal scheduling method increases renewable energy accommodation rate by 4.6%

reduces scheduling and operational costs by 25 000 yuan

and improves system stability.

关键词

Keywords

references

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