A power distribution network partition balancing method considering source load uncertainty and demand side resource coordination

By using the Copula algorithm and the improved K-means clustering algorithm for source-load modeling, and combining it with a two-level optimization model for regional power balance, time-of-use pricing and energy storage capacity are optimized. This solves the problems of source-load uncertainty and resource synergy optimization in the distribution network, and achieves efficient power balance and maximizes economic benefits.

CN122159255APending Publication Date: 2026-06-05STATE GRID SHANDONG ELECTRIC POWER CO LIAOCHENG POWER SUPPLY CO
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
STATE GRID SHANDONG ELECTRIC POWER CO LIAOCHENG POWER SUPPLY CO
Filing Date
2026-01-15
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing distribution network zoning balancing methods fail to fully consider the uncertainty of source loads and the coordinated optimization of demand-side resources, resulting in insufficient adaptability and real-time performance of balancing strategies, and failing to fully leverage the comprehensive benefits of flexible resources.

Method used

The Copula algorithm and the improved K-means clustering algorithm are used to model source-load uncertainty and construct a two-level optimization model for regional power balance. By optimizing time-of-use pricing and energy storage capacity, combined with demand-side response and energy storage optimization, the optimal revenue for regional operators and local consumption of new energy are achieved.

Benefits of technology

It has improved the adaptability and stability of the distribution network, increased the renewable energy absorption rate, reduced the peak-valley difference, improved the power grid operation efficiency and economic benefits, and realized the refined management and regional balance of the distribution network.

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Abstract

The application provides a power distribution network partition balancing method considering source load uncertainty and demand side resource cooperation, and belongs to the technical field of power distribution network partition balancing.The method generates wind and light output scenarios and load scenarios, solves wind and light typical daily output curves and typical daily load curves of each partition, constructs a partition power balance double-layer optimization model, constructs an upper-layer demand side response optimization model by optimizing time-of-use electricity price mode with the optimal regional operator revenue as the target, constructs a lower-layer energy storage optimization model by optimizing energy storage capacity mode with local new energy consumption as the target, solves the two models to obtain the optimized electricity price of each partition and the energy storage operation power at each time, and determines the balancing mode through parameter transmission and cooperative optimization between the two models, determines the load and new energy difference of each partition, and performs partition balancing in combination with the determined balancing mode.The application optimizes source load modeling, cooperates with the demand side and energy storage, accurately performs partition balancing, and improves power grid stability and economic benefits.
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