Research on distributionally robust optimization based group tuning control strategy for distributed photovoltaic system under solar load gap

田闽哲; 李俊楠; 何心铭; 郭露方; 马茗婕; 黄梦旗

doi:10.3969/j.issn.1009-1831.2025.04.018

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Research on distributionally robust optimization based group tuning control strategy for distributed photovoltaic system under solar load gap

更新时间：2026-03-05

- Research on distributionally robust optimization based group tuning control strategy for distributed photovoltaic system under solar load gap
- Vol. 27, Issue 4, (2025)
- 作者机构：
  
  国网河南省电力公司营销服务中心,郑州,450000
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1009-1831.2025.04.018
  CLC：
- Published：2025
- 稿件说明：
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田闽哲, 李俊楠, 何心铭, et al. Research on distributionally robust optimization based group tuning control strategy for distributed photovoltaic system under solar load gap[J]. 2025, 27(4).
DOI：

田闽哲, 李俊楠, 何心铭, et al. Research on distributionally robust optimization based group tuning control strategy for distributed photovoltaic system under solar load gap[J]. 2025, 27(4). DOI： 10.3969/j.issn.1009-1831.2025.04.018.

摘要

随着台区内分布式光伏装机容量的增加

光荷缺口现象频发

现有群调群控策略在出现光荷缺口时大多采用完全切除的策略

降低了台区光伏的消纳率

很难保证用户的公平性。针对光荷缺口下台区分布式光伏群调群控问题

综合考虑需求响应负荷和光伏出力的不确定性

提出了一种基于分布鲁棒优化方法的台区分布式光伏群调群控策略。考虑到需求响应负荷能够在一定程度上对光荷缺口进行削减

首先完成对可削减及可中断负荷的建模；然后构建基于分布鲁棒优化方法的台区分布式光伏群调群控模型

该模型以相关运行费用最小为目标

同时采用组合范式来描述光伏出力的不确定性

减小因预测误差、出力波动性而影响台区电网的稳定运行；最后

使用列和约束生成算法来解决该所提模型

并通过河南某地台区电网数据

验证了所提模型的有效性

能够在出现光荷缺口时制定合理的群调群控策略

提高台区分布式光伏的消纳能力。

Abstract

With the increasing installation capacity of distributed photovoltaic（PV）systems in distribution networks

grid operators frequently issue curtailment instructions. Traditional group control strategies mainly adopt complete curtailment approaches when receiving these instructions

which reduces PV consumption rates and compromises user fairness. A distributionally robust optimization-based group control strategy for distributed PV systems that considers both demand response uncertainty and PV output uncertainty is proposed. Recognizing that demand response loads can partially fulfill curtailment requirements

models for reducible and interruptible loads are developed. Then

firstly a distributionally robust optimization model for PV group control that aims to minimize operational costs while employing a combination paradigm to characterize PV output uncertainty is constructed. This approach reduces the impact of prediction errors and output fluctuations on distribution network stability. The proposed model is solved using a column and constraint generation algorithm.The effectiveness of our proposed strategy is validated using data from a distribution network in Henan Province. Results demonstrate that the strategy can develop reasonable group control strategies when curtailment instructions are issued

thereby improving the consumption capacity of distributed PV systems.

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