摘要
为克服传统单一电量预测方法的不足,本文选取多个单一预测方法,构建电量组合预测模型,较全面考虑了影响电量预测的因素,提高电量预测的精度。并运用粒子群算法对单一预测方法的权重进行优化求解,能有效避免传统算法陷入局部最优点的问题,获得较准确的电量组合预测模型。通过应用实例,验证组合预测模型能有效提高电量预测的精度,为电力系统规划及运营提供参考。
To overcome the disadvantage of traditional single predication method, the author combines several single predication model to establish power combination forecast model. The power combination forecast model considers more comprehensive factors and can improve the accuracy of prediction of electricity. The paper uses the particle swarm optimization for solving appropriate weight of each single predication method. It overcomes the traditional algorithm, which can not solve the optimal weight problems, but gets more accurate predication model. The paper proves that combination forecasting model can improve the accuracy of prediction of electricity with an example. It can provide a good guidance for power system planning and operation.
出处
《内蒙古电力技术》
2017年第1期43-46,共4页
Inner Mongolia Electric Power
关键词
单一预测方法
电量组合预测模型
粒子群算法
传统算法
single predication method
power combination forecast model
particle swarm algorithm
traditional algorithm
