Collaborative Optimization Method for Integrated Energy of Campus Cluster Based on Improved Particle Swarm Optimization

In order to fully adapt to the natural endowment and load distribution of the region and facilitate the overall arrangement of energy supply and consumption activities in a specific range, the integrated energy system of the park is generally established based on the differences in the construction and operation of energy supply facilities in the park. At present, many studies have been carried out on the optimal scheduling of the integrated energy system in the park. In view of the uncertain energy Internet in the park, the coupling relationship exists between the energy flow and the equipment in the park. In this paper, the particle swarm optimization is easy to fall into local optima. The particle swarm optimization algorithm is improved, and the adaptive mutation mechanism is integrated into the adaptive mutation particle swarm algorithm. The effectiveness of the new algorithm is verified by the simulation results using MATLAB software. Through the simulation analysis of the park, it can be concluded that different constraint operation strategies have a certain impact on the optimization of the park energy Internet. By improving the alternate direction of variable step, the optimal operation scheme of the system is obtained, which not only ensures the economy of the integrated energy system in the park, but also takes into account the flexible and stable operation of the distribution network.