摘要
给出电力系统短期负荷的固定权系数组合预测模型──基于遗传算法的组合预测模型。为增加样本的多样性、避免陷入局部极小，文中对遗传算法每代的相同或相近个体作等适应值变换，改进后的遗传算法具有更好的全局优化特性。利用改进的遗传算法确定组合预测模型的权系数，然后进行负荷预测。计算结果表明，该方法是实用和有效的。
In this paper, a fixed weight coefficient combi- nation forecasting model based on genetic algorithm for short term forecasting load is proposed. In order to enhance the multiform of the sample and avoid running into the local mini- mum, the equal fitness value transformation is carried out for same or similar individuals in each generation of genetic algo- rithm. The improved genetic algorithm has better feature of global minimum. The model can forecast the load after solv- ing the weight coefficient by the improved genetic algorithm. The effectiveness and practicality of the model are verified by the numerical samples.
出处
《电网技术》
EI
CSCD
北大核心
2001年第8期20-23,共4页
Power System Technology
关键词
负荷预测
组合预测模型
遗传算法
电力系统
load forecast
combination forecasting model
improved genetic algorithm
