Research on Optimization and Control Strategies for Adjustable Resources in New Power Systems from the Perspective of Energy Conversion

With the increasing integration of substantial proportions of renewable energy into the electrical grid, the volatility and uncertainty associated with renewable energy output and demand impose greater demands on the regulatory capabilities of the system. In the context of future multi-energy coupling, this paper proposes an adjustable resource optimization scheduling model that considers energy conversion, resource characteristics, and regulatory scenario requirements. The model is addressed through the Particle Swarm Optimization (PSO) algorithm. A case study conducted in an industrial park serves to validate the model. The findings demonstrate that the proposed model significantly enhances the absorption rate of renewable energy and improves economic efficiency, thereby facilitating the development of a new power system and promoting the integration of multi-energy sources.