An Optimal Scheduling Strategy of Integrated Energy Systems Considering FCSNPS-Based Path Optimization

Nowadays, integrated energy systems contain many types of equipment and loads. In order to improve the coupling degree between energy equipment, and better determine the optimal energy supply mode from many energy supply paths, an optimal scheduling strategy of integrated energy systems considering path optimization based on fuzzy colored spiking neural P systems (FCSNPSs) is proposed. The advantages and disadvantages of the strategy under different operating conditions are explored. Firstly, considered the multi-energy coupling model of electric-heat-cold-gas flows, a scheduling function aiming at the optimal of operating cost is established. Secondly, a novel path optimization reasoning model is proposed by combining the established model with fuzzy colored spiking neural P systems（RIES-FCSNPS）. Finally, the operation model of the system is scheduled by using the mixed integer planning software. The results of simulation experiments show that the FCSNPS-based integrated energy system considering path optimization can not only clearly describe the energy supply path information, but also evaluate the overall benefits under different operation modes.