改进粒子群算法求解水火电系统短期负荷分配问题

粒子群优化（PSO）算法是一种基于群体智能的启发式搜索方法，应用领域很广。文中将PSO算法用于求解水火电系统短期负荷的经济分配，属于高维、强约束工程问题。分析了算法参数设置对解的影响，发现算法的局部开发能力和粒子的多样性是影响解的优劣的关键因素;提出多子群辅助的PSO算法，兼顾了对解空间的全局搜索和局部开发。实际算例证明，改进的算法是有效的。

Short-term Scheduling of Hydro-thermal System via Novel Particle Swarm Optimization

Particle swarm optimization (PSO) is a heuristic search method based on swarm intelligence,and has been widely used to solve various problems in engineering fields.PSO is implemented to solve the optimal load distribution in short-term scheduling of hydro-thermal power systems,a high-dimensional engineering case restricted within narrow limits by multiple constraints.The PSO parameters are analyzed for the improvement of the performance,and it is pointed out that a better solution largely depends on the local searching ability of the algorithm and the diversity of particles.Furthermore,multi- subgroup assistant particle swarm optimization (MSA-PSO) is proposed,in which the information exchange between a dominant group and the subgroups is introduced.It is applied to the same optimization problem,and better results are achieved,which verifies the superiority of the modified method.