基于混沌粒子群优化的火电机组负荷分配

摘要

为进一步优化电厂负荷的分配,有效提高发电厂的经济效益,在粒子群算法的基础上结合混沌优化等算法对电厂负荷的分配进行了改进研究.该方法从火电厂的实际发电情况出发,考虑了阀点效应和机组在实际运行过程中的约束条件,建立了发电机组负荷优化分配模型,并利用罚函数法将此模型转化为非约束问题求解,实现了利用混沌粒子群算法来优化发电机组负荷,解决了局部最优和收敛速度慢等问题.通过实例分析证明了该算法的可行性.%To optimize the load distribution further and improve the economic efficiency of power plant,this paper improves the load distribution of the power plant based on the particle swarm optimization algorithm and chaotic optimization algorithm.Considering the actual situation of the power generation power plant,this method establishes the optimal load distribution model of generator,which takes the constraints of the valve point effect and units in the actual operation process into consideration.By using the penalty function method,this model is transformed into a non constrained problem.A practical example analysis has verified that the improved chaotic-particle swarm optimization algorithm is feasible in solving the problem of optimal load distribution,partial optimum and slowness of convergence rate.