E-SOP optimization scheduling method and system based on unscented transformation and information gap decision theory

By combining unscented transformation and information gap decision theory, joint modeling of load, renewable energy output, and market price cost is achieved. This solves the problem of low E-SOP scheduling accuracy caused by the inability of existing technologies to coordinate the randomness of source and load and the uncertainty of price information gaps, and improves scheduling accuracy.

CN120955730APending Publication Date: 2025-11-14GUANGDONG POWER GRID CO LTD
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Patent Information

Application Number
CN202511059330.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-30
Publication Date
2025-11-14

AI Technical Summary

Technical Problem

Existing technologies cannot coordinate the randomness of source loads and the uncertainty of price information gaps, resulting in low accuracy of E-SOP optimized scheduling.

Method used

Unscented transformation is used to perform joint uncertainty modeling of load and renewable energy output. Information gap decision theory is used to model the market price cost of substations. The objective function of minimizing operating cost is constructed and solved, taking into account the constraints of distribution network parameters and equipment operating costs.

Benefits of technology

It improves the accuracy of E-SOP optimized scheduling, solves the technical problems existing in the prior art, realizes the coordinated processing of source load randomness and price fluctuations, and improves scheduling accuracy.

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Abstract

The invention discloses an E-SOP optimal scheduling method and system based on unscented transformation and an information gap decision theory, and belongs to the field of E-SOP optimal scheduling. According to the method, historical data are obtained, unscented transformation is used for carrying out joint uncertainty modeling on loads and new energy output, fluctuation characteristics and correlation of the loads and the new energy output are captured, and the unscented transformation and the new energy output are combined; and performing information gap uncertainty modeling on the price cost of the transformer substation market by using an information gap decision theory, quantifying the maximum tolerance of the system to the price fluctuation, finally comprehensively representing the characteristics of source-load random fluctuation and price interval fluctuation, solving a function taking the minimum operation cost as an objective function, and obtaining an optimal E-SOP regulation and control strategy. Cooperative processing of source load randomness and price fluctuation is realized, scheduling accuracy of the E-SOP is improved, and the problem of low scheduling accuracy of the E-SOP caused by incapability of cooperatively processing source load randomness and price information gap uncertainty due to independent processing of a certain type of uncertainty in the prior art is solved.
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