Active power distribution network multi-element coordinated planning method considering flexibility

CN117394451BActive Publication Date: 2026-06-23STATE GRID FUJIAN ELECTRIC POWER CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
STATE GRID FUJIAN ELECTRIC POWER CO LTD
Filing Date
2023-10-12
Publication Date
2026-06-23

AI Technical Summary

Technical Problem

Existing technologies fail to effectively consider flexibility planning over long time scales in distribution networks, especially in the face of high renewable energy penetration and uncertainty, making it difficult to effectively regulate power fluctuations and extreme operating conditions.

Method used

A flexibility evaluation index system for active distribution networks is constructed. A two-level programming model with multiple time scales is adopted. By using the sorting method for approximating ideal solutions and the particle swarm algorithm, controllable resources are optimized to achieve a balance between medium- and long-term economic efficiency and flexibility.

Benefits of technology

It has enabled the network to adapt to load growth and extreme operating conditions in the medium to long term, improving the flexibility and economy of the distribution network and optimizing resource allocation and operating costs.

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Abstract

The application relates to a kind of active distribution network " source network storage " multi-element coordinated planning method considering flexibility. Considering medium and long term planning and short term operation, the multi-time scale flexibility evaluation index system of active distribution network is constructed, covering different dimensions of power regulation and network regulation, including time period, feeder and different levels of distribution network. A " source network storage " multi-element double-layer planning model considering flexibility is proposed, the upper layer is a multi-objective decision multi-element planning scheme with annual comprehensive cost and medium and long term flexibility, and the lower layer optimizes each element daily operation purpose to improve the satisfaction degree of operation cost and short term flexibility. The planning layer multi-objective is processed by the approximation ideal solution sorting method, and the variable coding and model solving strategy based on harmony search and particle swarm optimization algorithm are formulated. Finally, the rationality of the planning scheme and daily operation is demonstrated through a 6-feeder application example, and the effectiveness of the proposed index is verified based on the flexibility index composition analysis.
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