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.

CN121840707APending Publication Date: 2026-04-10SHANGHAI UNIVERSITY OF ELECTRIC POWER
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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

Technical Problem

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.

Method used

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.

Benefits of technology

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.

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Abstract

The invention relates to a power system self-balancing capability improving method and system considering source load uncertainty and multi-stage cooperation, and the method comprises the steps: generating a time sequence scene set representing new energy output and load uncertainty, and carrying out the modeling of the new energy output and the load of a power system; in the planning stage, with the cumulative probability density expected value for maximizing the balance capacity of the electric power system as an upper layer target and the minimum energy storage full life cycle total cost as a lower layer target, under the energy storage operation constraint and the system power balance constraint, the self-balance capacity index distribution of the electric power system is counted by utilizing a pre-constructed self-balance evaluation system, and the self-balance capacity index distribution of the electric power system is calculated; solving to obtain the optimal energy storage configuration; and in the operation stage, day-ahead scheduling and intra-day scheduling are carried out based on the optimal energy storage configuration, and real-time scheduling is carried out based on the real-time self-balancing capability index. According to the method, probabilistic equilibrium situation analysis runs through the whole process of planning and operation, and the self-balancing capability is improved from static evaluation to dynamic collaborative improvement.
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