Cooperative Scheduling of Power-Thermal Coupled System in Park Based on Chaotic Particle Swarm Optimization

For the northwest region with abundant new energy resources, it is the trend of energy Internet development to change the traditional heating mode through power substitution and multi-functional coordination and complementary. However, due to the fluctuation of new energy sources and the multi-time scale characteristics of the electric-thermal coupling system, the study of reasonable and feasible energy scheduling strategies has become an urgent problem to be solved. This paper studies the coordinated optimal dispatch of the electric-thermal coupling system for the regional energy network at the park level. Aiming at economy and environmental protection, a multi-objective chaotic particle swarm algorithm is presented. The initial population and the search process are more traversable by population initialization method based on chaos generation, penalty-based overrun correction method, and chaotic search-based particle movement method, and the particles are not allowed to enter the infeasible domain. To achieve the coordinated optimal dispatch of the deep electric-thermal coupling "source-load" system in the park. The simulation results show that compared with other multi-objective optimization algorithms, this algorithm has better convergence performance, and the optimization results are significantly reduced in terms of power consumption, total maintenance cost and carbon dioxide emissions, so it can better solve the co-scheduling problem of the electric-thermal coupling system.