Optimal Scheduling of Multi-energy Hub System Based on Differential QPSO Algorithm

In order to solve the problems of strong coupling, complex constraints and high dimensions in optimal scheduling of multi-energy hub systems, differential evolution quantum particle swarm optimization (DEQPSO) algorithm is proposed. The algorithm combines the mutation, crossover and selection operations in the differential evolution algorithm with the particle position update formula in the quantum particle swarm optimization algorithm, which increases the diversity of the population in the quantum particle swarm optimization algorithm, solves the problem that the particles are easy to fall into the local optimum in the middle and later stages of the search, and improves the global search ability of the algorithm. The standard test function is used to test the algorithm. The test results show that the algorithm has good convergence and global search ability. In this paper, the algorithm is applied to the optimal scheduling of multi-energy hub system, and the calculation results show the effectiveness and applicability of the algorithm.