Improved Particle Swarm Optimization Based on Flexible Load Scheduling Method for New Energy Distribution Network

With the development of the energy market, new changes have emerged on the supply side, distribution side and energy use side of multi-energy supply energy networks, with more and more subjects joining them. Wind power and photovoltaic power stations are interrelated, but because of different investors, they are the central bodies with different interests. To further promote renewable energy consumption and improve the economy and reliability of each subject, it is necessary to build a more effective flexible load dispatching model and improve the enthusiasm for building the energy market by many parties. Therefore, multi-investor participation in optimizing the integrated energy system becomes the main problem. In this paper, the multi-investment subject is taken as the research object, and the capacity allocation scheduling model is established. Taking the profit of each participant as the objective function, the improved particle swarm optimization algorithm is adopted to solve the problem, and the multi-objective optimization in capacity allocation is realized. The improved multi-objective particle swarm optimization algorithm determines the importance of active and passive resources in regional power system operation, and the effectiveness and feasibility of the proposed method is verified by simulation. In-depth research will be beneficial to tap the user-side load adjustable resources and improve the digital capability of the power system. At the same time, in-depth research is conducive to strengthening the optimal allocation of resources in the power market and promoting the upgrading and development of power system regulation technology.