Comprehensive Optimization of Integrated Smart Energy Systems with Multi-Load Demand Response

This paper presents a cooperative optimal dispatching model for managing integrated smart energy systems, with a focus on power and heat load dispatching. The suggested method includes demand response for diverse electric loads while increasing system flexibility by considering thermal load as a variable load during transmission by utilizing fuzzy heating comfort perception and thermal inertia.The study develops a comprehensive demand response model for both electric and thermal loads, taking into account various response types. To improve energy efficiency, an energy quality coefficient is created, which takes into account both the "quality" and "quantity" sides of energy.With the goal of obtaining optimal energy efficiency, the cooperative optimization scheduling model is constructed, accounting for the operational restrictions of the electric-thermal system under normal conditions. For analysis and calculation, Quantum Particle Swarm Optimization (QPSO) is used.Simulations using IEEE 9-node, 20-node natural gas, and 6-node thermal systems are undertaken to validate the proposed model. The results indicate the model's and method's rationality and efficacy, highlighting their potential for efficient energy management in integrated smart energy systems with multi-load demand response.