The mathematical modeling of the coal power generation model is completed by combining the relevant information in the field of coal power generation and thermal power generation, followed by the mathematical modeling of the photovoltaic power generation model by using the physical properties of the junction, and the photovoltaic grid-connected inverter control principle, so that the photovoltaic power generation model maintains a stable performance performance. On this basis, the PV power generation model is combined with the coal power generation model using a combination of system identification and model downscaling to obtain a hybrid PV-coal power generation system. The improvement of the standard particle swarm optimization algorithm is achieved by introducing the inertia weight way, and the solution process of the improved particle swarm optimization algorithm is supplemented, and finally an optimization model of the environmental benefits of the PV-coal hybrid power generation system based on the improved particle swarm optimization algorithm is designed. On the three test functions, the improved particle swarm algorithm outperforms the standard PSO algorithm with convergence rates of 99.21%, 97.57% and 92.68%, i.e., it verifies that the inertia weights improve the standard PSO algorithm. In addition the optimal solutions of the three objective functions are 2,077,000 yuan, 23,910,000 yuan and 235,310,000 yuan, i.e., to demonstrate the application effect of the environmental benefit optimization model of PV-coal hybrid power generation system with improved particle swarm optimization algorithm, which is of guiding value for the green sustainable development of PV-coal hybrid power generation system.
