一种面向运行可靠性的短期负荷预测方法研究

A short-term load forecasting method oriented for operational reliability

与传统可靠性相比,电力系统运行可靠性反应的是系统短期运行行为对可靠性的影响,需建立一种面向运行可靠性的短期负荷预测模型,既能提供充裕度指标评估所需的概率模型,又能提供系统安全性评估所需的精确模型。因此,文章通过对历史气候数据进行模糊聚类,提取相似日负荷构成样本数据并进行小波分解,利用改进的PSO-RVM算法对各小波分量进行预测和叠加,以得到预测日负荷序列的均值和概率模型,仿真表明该方法预测准确率较高,可为运行可靠性充裕度、安全性评估提供负荷数据支撑。

Compared with the traditional reliability, the operational reliability of power system can reflect the impacts of short term operation on the reliability. So there is the need to establish a prediction model to forecast short-term load orien-ted for the operational reliability, which can provide the probability model for adequacy indices evaluation, and provide an accurate model needed for the system security assessment. An improved fuzzy clustering is proposed in this paper to extract similar day, and DB4 wavelet is used to decompose the similar day load sequence in 3-layer wavelet. Then,the improved PSO-RVM algorithm has been used to predict wavelet components of forecasted days, and the results of wavelet prediction have been superposed to get the mean value and probability model of load sequences of forecasted days. The simulation re-sults show that the proposed method has better prediction accuracy, which can provide load data support for reliability ade-quacy and security evaluation of operation.