A source-network-load-storage double-layer collaborative optimization method based on a multi-agent algorithm

By constructing a multi-agent system and a two-layer nested optimization structure, the challenges posed to the power grid by distributed generation and load fluctuations have been addressed, achieving coordinated optimization of the power generation, grid, load, and storage systems, and improving the flexibility and economy of power grid operation.

CN116365597BActive Publication Date: 2026-05-29国网重庆市电力公司丰都供电分公司 +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
国网重庆市电力公司丰都供电分公司
Filing Date
2023-03-14
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

The randomness of distributed generation and the fluctuations of various types of loads pose challenges to the optimization, regulation, and operation of the power grid. Traditional methods are insufficient to achieve coordinated optimization of the generation, grid, load, and storage systems.

Method used

A multi-agent system of source-grid-load-storage is constructed using a multi-agent algorithm. A double-nested optimization structure is utilized, and an improved genetic algorithm is used to solve for the minimum amount of light wastage and operating cost, thereby achieving modular operation and economic stability.

Benefits of technology

It improves the flexibility and economic stability of system operation, reduces curtailment of solar power and operating costs, optimizes the load curve, and improves the utilization rate of distributed energy.

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Abstract

The application discloses a source-grid-load-storage double-layer collaborative optimization method based on a multi-agent algorithm, and comprises the following steps: constructing a source-grid-load-storage multi-agent system; constructing a source-grid-load-storage collaborative optimization model based on the multi-agent system; solving the in-layer target of the collaborative optimization model by using a double-layer nested optimization structure to obtain minimum light abandonment and minimum operation cost, and realizing source-grid-load-storage double-layer collaborative optimization; compared with the prior art, the method combines the multi-agent system and the collaborative optimization model, solves the problem that distributed power generation has great randomness, and after superimposing various types of load fluctuations, the problem that the power grid optimization regulation and operation are challenged is solved, and scientific guidance is provided for reliable operation of a new power system.
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