Energy storage configuration method for improving new energy bearing capacity based on collaborative optimization

By using a three-layer collaborative optimization model and a generalized Benders decomposition algorithm, the grid absorption problem caused by the volatility of new energy generation was solved, the grid's new energy carrying capacity and security stability were improved, energy storage configuration and load regulation were optimized, and system operating costs were reduced.

CN121984075APending Publication Date: 2026-05-05STATE GRID GANSU ELECTRIC POWER CORP +1
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Patent Information

Application Number
CN202610422012.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-01
Publication Date
2026-05-05

AI Technical Summary

Technical Problem

Existing technologies are insufficient to effectively address the grid's renewable energy absorption problem caused by the randomness and volatility of renewable energy generation. Furthermore, the increased proportion of renewable energy leads to power supply shortages and significant challenges to safety and stability. Therefore, a layered, collaborative, and multi-objective optimized energy storage configuration method is needed to enhance the grid's renewable energy carrying capacity.

Method used

A three-layer collaborative optimization model is adopted. The load demand response model is constructed through the Logistic function, and the load curve is optimized by combining time-of-use pricing. A middle-layer simulation operation model is constructed to minimize the total system operating cost and the carrying capacity of new energy sources. The lower-layer optimization model optimizes the configuration of grid-connected power sources and synchronous condensers. The generalized Benders decomposition algorithm is used for iterative solution, and the energy storage configuration is collaboratively optimized.

Benefits of technology

This has enabled the grid to enhance its capacity to absorb new energy sources and improve its carrying capacity, optimize its load curve, reduce wind and solar curtailment rates, and strengthen its support for new energy sources, all while ensuring the grid's safety and stability.

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Abstract

The invention discloses an energy storage configuration method for improving new energy bearing capacity based on collaborative optimization, which relates to the technical field of new energy power systems, and optimizes a load curve and solves initial energy storage configuration based on a Logistic function by constructing an upper-layer constant volume model; constructing a middle-layer simulation operation model, and calculating a bearing capacity upper limit by taking minimum system operation cost and maximum new energy bearing capacity as double targets; constructing a lower-layer optimization model, optimizing the configuration of the network construction type power supply and the phase modifier, and completing security constraint verification; and iteratively solving the three-layer model by adopting a generalized Benders decomposition algorithm, and outputting a global optimal energy storage configuration and new energy bearing capacity improvement result. According to the method, the load side, power side and system side strategies are optimized in a layered and collaborative manner, economy, reliability and safety are considered, and the new energy bearing and absorption capacity of the power grid is effectively improved.
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