Multi-objective Coordination Planning of Source, Grid and Storage for Active Distribution Network Considering Flexibility

廖剑波; 陈熹; 郑原俊; 陈高汝; 黄毅标

doi:10.19725/j.cnki.1007-2322.2023.0376

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Multi-objective Coordination Planning of Source, Grid and Storage for Active Distribution Network Considering Flexibility

更新时间：2026-02-02

- Multi-objective Coordination Planning of Source, Grid and Storage for Active Distribution Network Considering Flexibility
- Vol. 43, Issue 1, Pages: 92-103(2026)
- 作者机构：
  
  国网福州供电公司,福建省,福州市,350009
- 作者简介：
- 基金信息：
- DOI：10.19725/j.cnki.1007-2322.2023.0376
  CLC： 1
- Published：2026
- 稿件说明：
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廖剑波, 陈熹, 郑原俊, et al. Multi-objective Coordination Planning of Source, Grid and Storage for Active Distribution Network Considering Flexibility[J]. 2026, 43(1): 92-103.
DOI：

廖剑波, 陈熹, 郑原俊, et al. Multi-objective Coordination Planning of Source, Grid and Storage for Active Distribution Network Considering Flexibility[J]. 2026, 43(1): 92-103. DOI： 10.19725/j.cnki.1007-2322.2023.0376.

摘要

运行灵活是分布式绿电深度集成的主动配电网(active distribution network，ADN)的显著特征，该文提出一种考虑灵活性的主动配电网源-网-储多元协调规划方法。计及中长期规划和短期运行，构建ADN的多时间尺度灵活性评价指标体系，涵盖功率调节和网架调节不同维度，包括时段、馈线、配电网不同层级。接着，提出考虑灵活性的源-网-储多元双层规划模型，上层以年综合成本与中长期灵活性为多目标决策多元件规划方案，下层寻优各元件日运行方式，旨在提升运行成本与短期灵活性隶属满意度。以逼近理想解排序法来处理规划层多目标，制定基于和声搜索和粒子群算法的变量编码及模型求解策略。最后，通过六馈线ADN算例论证规划方案及日运行方式的合理性，基于灵活性指标组成分析，并验证所提指标的有效性。

Abstract

Flexible operation is a significant feature of active distribution network (ADN) with deep integration of distributed green power. In this paper we propose a source

grid and storage coordination planning method considering flexibility for ADN. Multiple time scales flexibility evaluation indexes system for ADN is constructed with long term planning and short term operation taken into account. It encompasses various dimensions of power regulation and grid regulation

including different levels of periods

feeders and network. A source

grid and storage multi-objective two-layer planning model is proposed considering flexibility. The upper layer makes decisions on multi-objective planning scheme based on annual comprehensive cost and long-term flexibility

while the lower layer optimizes the daily operation of each component to improve the satisfaction of operating costs and short-term flexibility. The technique for order preference by similarity to ideal solution is employed to handle multi-objective planning. The variable encoding and model solving strategy are developed based on harmony search and particle swarm optimization algorithm. Finally

the rationality of the planning scheme and daily operation mode is demonstrated through am illustrative example of six-feeder ADN

thereby validating the effectiveness of the proposed indexes based on the composition analysis of the flexibility indexes.

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references

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