摘要
在“双碳”背景下,电网整体的规划离不开负荷预测。传统配电网的负荷预测主要以一些常规数学方法进行建模回归,该方法在应用于新配电网中产生的误差会很大。针对新型配电网,提出了一种改进的logistic方法来对新型的配电网进行负荷预测。首先进行空间负荷预测来适应新型配电网系统的负荷变化趋势,其次以上述步骤的结果作为饱和值,利用粒子群算法对逻辑回归参数寻找最优值,以此来进行负荷预测,最后通过实际算例表明提出的改进算法的优越性。
Under the background of"double carbon",the overall planning of power grid can not be separated from load forecasting.The load forecasting of traditional distribution network is mainly modeled and regressed by some conventional mathematical methods,which will cause great errors when applied to the new distribution network.Aiming at the new distribution network,an improved logistic method is proposed to forecast the load of the new distribution network.Firstly,the spatial load prediction is carried out to adapt to the load change trend of the new distribution network system.Then,the results of the above steps are used as the saturation value,and the particle swarm algorithm is used to find the optimal value of the logistic regression parameters to make load prediction,and finally the superiority of the improved algorithm proposed in this paper is shown by actual examples.
作者
刘秦娥
王晓东
LIU Qine;WANG Xiaodong(State Grid Hubei Xiangyang Power Supply Company,Xiangyang 441100,China)
出处
《通信电源技术》
2022年第23期41-43,47,共4页
Telecom Power Technology
关键词
新型配电网
逻辑回归模型
粒子群算法
长期负荷预测
new distribution network
logistic regression model
particle swarm algorithm
long-term load forecasting
