Power system self-balancing capability improving method and system considering source load uncertainty and multi-stage cooperation
By constructing a time-series scenario set and a two-layer optimization model for uncertainties in new energy output and load, and combining it with a feedback closed-loop mechanism for self-balancing capacity indicators, the problems of safe, stable and economical operation of the power system under the new energy environment are solved, and the systemic improvement and dynamic optimization of self-balancing capacity are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-26
- Publication Date
- 2026-04-10
AI Technical Summary
Existing technologies cannot effectively cope with the uncertainty of new energy output and load changes, making it difficult for the power system to achieve safe, stable and economical operation under a high proportion of new energy access. Traditional power balance evaluation methods cannot meet the complex balance relationship of new power systems. Long-term energy storage is costly and inefficient, short-term power balance recovery is slow, and extreme weather has a significant impact.
By generating a time-series scenario set of uncertainties in new energy output and load, a probability distribution model is constructed. In the planning stage, the upper-level objective is to maximize the power system balance capacity, and the lower-level objective is to combine the full life cycle cost of energy storage, and a two-level optimization configuration is carried out. In the operation stage, day-ahead, intraday, and real-time scheduling are carried out, and the self-balancing capacity index is used for real-time optimization. A feedback closed-loop mechanism is established to dynamically adjust the energy storage configuration.
It has achieved a systematic improvement in the self-balancing capability of the power system, the indicator-driven optimization process is quantifiable, it balances optimal time cost and reliability, has adaptive evolution capability, and improves the safe and stable operation of the power system in the new energy environment.
Smart Images

Figure CN121840707A_ABST