摘要
合理选择火电厂负荷优化分配的优化算法对快速完成电网调度指令、最大限度降低发电成本至关重要。在标准粒子群优化算法中引入模拟退火算法的思想,引入收缩因子对算法的重要参数进行了改进,并对种群初始化方式进行了改进,采用拉格朗日乘子法处理功率平衡约束。在严格满足约束条件的基础上,缩短了优化计算时间,进一步提高了算法精度。实例计算结果表明,模拟退火粒子群算法的分配结果比电网调度指令节省煤耗18.139g/(kW.h),比标准粒子群算法节省煤耗2.846g/(kW.h),同时计算时间也短于其它常规算法。
Whether the optimization algorithm of optimal of optimal load dispatch for power plant can be chosen reasonably or not is significant to finish load command of power network dispatching quickly and reduce generation cost in maximum extent. The optimal load dispatch method based on simulated annealing particle swarm optimization algorithm of power plant was proposed by introducing the simulated annealing idea into standard particle swarm optimization algorithm. In addition, the constriction factor is introduced to improve major parameters of the algorithm,the population initialization mode is improved, and the Lagrange multiplier method is adopted to process power balance restraint. The optimal calculation time is reduced and the accuracy of algo- rithm is enhanced on th basis of meething the constraints strictly. The example results show that the distribution results of simulated annealing particle swarm optimization algorithm saves coal consumption 18. 139 g/ （kW·h） compared with power network dispatching,as well as saves coal consumption 2. 846 g/（kW·h） compared with standard particle swarm optimization algorithm. Simultaneously, the computing time is shorter than other conventional algorithm.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2011年第3期40-44,共5页
Proceedings of the CSU-EPSA
基金
吉林省科技发展计划项目(20080523)
东北电力大学研究生创新基金资助项目
关键词
火电厂
负荷优化分配
模拟退火粒子群优化算法
粒子群优化算法
模拟退火优化算法
power plant
optimal load dispatch
simulated annealing particle swarm optimization algorithm
particle swarm optimization algorithm
simulated annealing optimization algorithm
