基于POA-GWO-CSO的有源配电网&#x0201c;源-荷-储&#x0201d;协同互动优化调度策略

戴文东; 金萍

doi:10.19912/j.0254-0096.tynxb.2025-0514

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (8) : 369-380. DOI: 10.19912/j.0254-0096.tynxb.2025-0514

基于POA-GWO-CSO的有源配电网“源-荷-储”协同互动优化调度策略

戴文东, 金萍

作者信息 +

OPTIMIZATION AND SCHEDULING STRATEGY OF "SOURCE-LOAD-STORAGE" COLLABORATIVE INTERACTION IN ACTIVE DISTRIBUTION NETWORK BASED ON POA-GWO-CSO

Dai Wendong, Jin Ping

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摘要

针对宁夏地区高比例新能源接入电网所带来的弃风弃光问题,提出基于鹈鹕优化算法（POA）-灰狼优化算法（GWO）-纵横交叉法（CSO）的有源配电网“源-荷-储”协同互动优化调度方法。首先,基于建筑围护结构的蓄热能力,建立含空调系统等灵活性资源的楼宇热动态模型,并通过综合考虑风光出力特性曲线和有源配电网、储能电站的运行约束,构建有源配电网“源-荷-储”协同运行模型;其次,提出有源配电网“源-荷-储”多目标互动优化调度策略,充分利用负荷和储能电站的运行灵活性,降低系统运行成本,提升新能源消纳率;然后,为提高多目标优化问题的求解精度,利用POA-GWO-CSO优化算法对模型进行求解。最后,基于宁夏闽宁小镇的实际数据集,对比分析不同优化调度策略对于有源配电网经济运行和新能源消纳率的影响,验证所提策略的有效性。

Abstract

To address the issue of wind and solar curtailment caused by the high proportion of renewable energy connected to the power grid in Ningxia, an active distribution network-based "source-load-storage" collaborative interactive optimization scheduling method. This method is developed based on Pelican optimization algorithm （POA） - Grey Wolf optimization algorithm （GWO） - Cross over optimization algorithm （CSO） is proposed. First, based on the thermal storage capacity of the building envelope structure, a building thermal dynamic model with flexible resources such as air conditioning is established. By comprehensively considering the wind and photovoltaic output characteristic curves and the operational constraints of active distribution networks and energy storage stations, a "source-load-storage" collaborative operation model of active distribution networks is constructed. Secondly, a multi-objective interactive optimization scheduling strategy for active distribution networks "source-load-storage" is proposed, which fully utilizes the operational flexibility of loads and energy storage stations, reduces system operating costs, and improves the absorption rate of renewable energy. Then, to improve the accuracy of solving multi-objective optimization problems, the POA-GWO-CSO optimization algorithm is used to solve the model. Finally, based on the actual operational dataset of Minning Town in Ningxia, the impact of different optimization scheduling strategies on the operation of active distribution networks and the consumption of renewable energy is compared and analyzed, thereby verifying the effectiveness of the strategies proposed in this paper.

导出引用

戴文东, 金萍. 基于POA-GWO-CSO的有源配电网“源-荷-储”协同互动优化调度策略[J]. 太阳能学报. 2026, 47(8): 369-380 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0514

Dai Wendong, Jin Ping. OPTIMIZATION AND SCHEDULING STRATEGY OF "SOURCE-LOAD-STORAGE" COLLABORATIVE INTERACTION IN ACTIVE DISTRIBUTION NETWORK BASED ON POA-GWO-CSO[J]. Acta Energiae Solaris Sinica. 2026, 47(8): 369-380 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0514

中图分类号： TM734

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