电力系统保护与控制2011，Vol.39Issue(17)：87-92,6.
基于BP神经网络的火电厂实时负荷优化分配
Real time optimal load dispatch of power plant based on back propagation neural network
摘要
Abstract
Real time dispatching method which can meet the requirements of power network dispatching is critical to use load optimal dispatch of power plant widely. The costs of fuel and pollutant emissions are comprehensively considered to improve the traditional mathematical model. According to the calculation formulae of error function, weight and threshold in BP network algorithm, the learning rate which can really reach adaptation is derived to improve the algorithm. Meanwhile. BP network is trained by the sample data that multiple mutation adaptive genetic algorithm is introduced to train the BP network. The acquisition of real time coal consumption characteristic curve is analyzed, and the implement of real time load optimal dispatch system based on BP network is discussed. The example calculation result is that the average relative error of 10 sets testing samples is only 0.185 percent and the average time consuming is only 0.011 s. It shows that the power generation cost is reduced, as well as the optimization computing time is effectively shortened.关键词
火电厂/负荷优化分配/实时调度/BP神经网络/多变异位自适应遗传算法Key words
power plant/ optimal load dispatch/ real time dispatching/ back propagation neural network/ multiple mutation adaptive genetic algorithms分类
信息技术与安全科学引用本文复制引用
李勇,王建君,曹丽华..基于BP神经网络的火电厂实时负荷优化分配[J].电力系统保护与控制,2011,39(17):87-92,6.基金项目
吉林省科技发展计划项目(20080523) （20080523）
