Source network collaborative optimization planning method and system driven by virtual power plant operation mode
By standardizing and equivalent modeling the parameters of virtual power plants, and combining the characteristics of power grid operation trends and the changing patterns of distributed power sources, the model is dynamically corrected, trading qualifications are verified, and resource allocation is optimized. This solves the problem of insufficient model accuracy in the source-grid collaborative optimization planning of virtual power plants, and realizes the efficient and reliable operation of the power system.
Patent Information
- Application Number
- CN202511782731.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-30
- Publication Date
- 2026-03-06
AI Technical Summary
Existing technologies in virtual power plant source-grid collaborative optimization planning lack systematic methods to handle physical parameters and scheduling cost parameters, leading to data anomalies and missing data. They cannot effectively map the correlation between parameters to the equivalent relationships of components, and fail to dynamically capture changes in the grid's operating status, resulting in insufficient model accuracy and difficulty in meeting the requirements for economic, safe, and flexible operation.
By normalizing the physical parameters and scheduling cost parameters of the virtual power plant to form a standardized parameter set, and mapping them to equivalent relationships between components, the trend characteristics of power grid operation status changes and the update rules of distributed power generation characteristics are extracted. The equivalent model is dynamically corrected, and the trading qualifications are determined based on the dispatchable capacity and response capability of the corrected model. The trading process is planned, the scheduling instructions are analyzed to evaluate the optimal allocation of resources, multi-objective comprehensive decision-making is carried out, and the optimized planning scheme is verified through simulation.
This improved the accuracy and feasibility of the model, ensuring the economic, safe, and flexible operation of the power system, achieving precise resource optimization and trading strategies, and guaranteeing the reliability of source-grid coordinated optimization planning.
Smart Images

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