Bilayer Collaborative Optimization Method of “Source-network-load-storage” Based on Multi Agent Algorithm

Abstract

Aiming at the problem that most optimization methods can't give consideration to the economy and environmental protection of the “source-network-load-storage” (SNLS) system, a bilayer collaborative optimization method of SNLS based on multi-agent algorithm is proposed. Firstly, a multi-agent system model of SNLS is constructed based on the distributed characteristics of multi-agent algorithm and system photovoltaic power generation cluster. Then, the system objective function and constraint conditions are set, that is, the optimization objective is to minimize the system operation cost and the amount of light discarded. Finally, based on the double-layer nested optimization structure, the objective is solved, and the improved grey wolf optimization algorithm is used to solve the single objective, so as to obtain the best optimization scheme of the system. The experimental results based on the IEEE33 node system platform show that the system operation cost and light rejection of the proposed method are about 383600 yuan and 0.895MW, respectively, and the energy use effect in the network is ideal.