摘要
传统的可靠性预测方法需要配电网结构和元件可靠性指标历史数据十分准确,难以实现对城市配电网规划供电可靠性指标的预测。为此,提出一种将PSO-LSSVM(基于粒子群优化的最小二乘支持向量机)模型应用到城市电网供电可靠性预测的方法。首先通过分析影响城市供电可靠性的因素得出主要特征量;然后将这些特征量的历史数据作为输入样本,利用粒子群优化的最小二乘支持向量机方法进行建模;最后利用建立好的模型预测规划目标年城市电网供电可靠性指标。对某省多个城市电网的应用结果表明,该方法是可行且有效的。
The traditional prediction of power supply reliability is on the basis of true structure of distribution network and historical data of element reliability. So it is hard to predict the planning power supply reliability of complex urban distribution network. For this reason, a least square support vector machine based on particle swarm optimization （PSO-LSSVM） model to predict power supply reliability of urban power network is proposed. Firstly, several principal characteristic quantities are received by analysing the factors of impacting power supply reliability. Then, taking his- torical data of these principal quantities as input samples, the particle swarm optimization（PSO）-least square support vector machine （LSSYM） is trained. Finally, by using the trained PSO-LSSYM, the power supply reliability indices of urban power network in target year can be predicted. The results of applying the proposed method to several urban pow- er networks show that the proposed method is effective.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2014年第7期82-86,共5页
Proceedings of the CSU-EPSA
关键词
供电可靠性
城市电网
指标预测
粒子群优化
最小二乘支持向量机
power supply reliability
urban power network
index prediction
particle swarm optimization （PSO）
least square support vector machine（LSSVM）
