基于改进灰狼优化算法的微电网优化经济调度

杨慧娴; 匡洪海; 李子龙; 徐雨淏; 曹世鹏

doi:10.19912/j.0254-0096.tynxb.2024-1866

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (2) : 365-374. DOI: 10.19912/j.0254-0096.tynxb.2024-1866

基于改进灰狼优化算法的微电网优化经济调度

杨慧娴, 匡洪海, 李子龙, 徐雨淏, 曹世鹏

作者信息 +

ECONOMIC DISPATCH OPTIMIZATION OF MICROGRID BASED ON IMPROVED GREY WOLF OPTIMIZER

Yang Huixian, Kuang Honghai, Li Zilong, Xu Yuhao, Cao Shipeng

Author information +

文章历史 +

摘要

为降低清洁能源的不确定性并提升微电网调度的经济性,建立以最小化微电网运营成本和环境治理成本为目标的调度模型。首先融合分时电价和清洁能源消纳,提出新型动态电价调整机制,在此基础上引入价格需求响应来综合优化负荷;其次采用一种基于融合余弦规律变化收敛因子、自适应惯性权重和柯西变异的改进灰狼优化算法（IGWO）,利用典型测试函数将IGWO与其他成熟算法进行对比分析。最后仿真结果表明,在3种策略对比分析下利用IGWO算法求解基于风光消纳的价格需求响应优化调度模型,可达到日出力最优且运行总成本显著降低,验证了所提研究的可行性和经济性。

Abstract

To reduce the uncertainty of clean energy and improve the economic efficiency of microgrid scheduling, a scheduling model is established with the objective of minimizing microgrid operating costs and environmental management costs. Firstly, a new dynamic electricity price adjustment mechanism is proposed by integrating time-of-use electricity pricing and the absorption of clean energy, and then demand response is introduced to optimize the load comprehensively. Secondly, an improved grey wolf optimizer （IGWO） is adopted, which is based on the fusion of cosine law variation convergence factor, adaptive inertia weight, and Cauchy mutation. The IGWO is compared with other mature algorithms using typical test functions. Finally, simulation results show that using the IGWO algorithm to solve the price-based demand response model for wind and solar power integration can achieve optimal daily output and significantly reduce the total operating cost, thus verifying the feasibility and economic viability of the proposed research.

导出引用

杨慧娴, 匡洪海, 李子龙, 徐雨淏, 曹世鹏. 基于改进灰狼优化算法的微电网优化经济调度[J]. 太阳能学报. 2026, 47(2): 365-374 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1866

Yang Huixian, Kuang Honghai, Li Zilong, Xu Yuhao, Cao Shipeng. ECONOMIC DISPATCH OPTIMIZATION OF MICROGRID BASED ON IMPROVED GREY WOLF OPTIMIZER[J]. Acta Energiae Solaris Sinica. 2026, 47(2): 365-374 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1866

中图分类号： TM73

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