基于差分QPSO的多能源集线器系统优化调度

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

针对多能源集线器系统优化调度中强耦合、约束复杂和高维度等问题,提出了一种差分进化量子粒子群优化算法。该算法将差分进化算法中的变异、交叉和选择操作与量子粒子群算法中粒子位置更新公式相结合,进而增加了量子粒子群算法中种群的多样性,解决了粒子在搜索中后期易陷入局部最优的问题,提高了算法全局搜索的能力。采用标准测试函数对该算法进行测试,测试结果表明新算法具有良好的收敛性和全局搜索能力。将上述算法应用于多能源集线器系统优化调度中,计算结果表明上述算法的有效性和适用性。

In order to solve the problems of strong coupling,complex constraints and high dimensions in optimal scheduling of multi-energy hub systems,a 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 was used to test the algorithm.The test results show that the algorithm has good convergence and global search ability.In this paper,the algorithm was applied to the optimal scheduling of multi-energy hub system,and the calculation results show the effectiveness and applicability of the algorithm.