基于改进粒子群算法的火电机组经济优化调度

Economic Optimal Dispatch of Thermal Power Units Based on Improved ParticleSwarm Optimization Algorithm

为了提高火电机组运行的经济性,以火电机组运行成本最小为目标函数,综合考虑火电机组运行过程中的各项约束,利用收缩因子对粒子群算法进行改进,建立基于改进粒子群算法的火电机组经济优化调度模型,并采用IEEE 30节点系统进行算例分析,结果表明采用IPSO算法优化的火电机组最小运行成本为24.13万元,IPSO算法在迭代次数和收敛精度上均优于PSO算法,验证了模型的正确性和实用性。

In order to improve the economy of thermal power unit operation,taking the minimum operation cost of thermal power unit as the objective function and comprehensively considering the constraints in the operation process of thermal power unit,the particle swarm optimization algorithm is improved by using the shrinkage factor,and the economic optimization scheduling model of thermal power unit based on the improved particle swarm optimization algorithm is established.The IEEE 30 node system is used for example analysis.The results show that the minimum operating cost of thermal power units optimized by IPSO algorithm is 241,300 yuan.The IPSO algorithm is superior to the PSO algorithm in the number of iterations and convergence accuracy,which verifies the correctness and practicability of the model.