基于自适应最优模糊逻辑系统的短期负荷预测方法  

SHORT-TERM LOAD FORECASTING TECHNIQUE BASED ON ADAPTIVE OPTIMAL FUZZY LOGIC SYSTEM

作　　者：吴捷[1] 严华[1] 

机构地区：[1]华南理工大学电力学院

出　　处：《电力系统自动化》1999年第17期35-37,共3页Automation of Electric Power Systems

摘　　要：提出了一种基于自适应最优模糊逻辑系统的电力系统短期负荷预测方法。首先通过最近邻聚类算法对负荷历史数据进行分组，再将每一组数据（一个聚类）视为一个数据对，用最优模糊逻辑系统来进行预测系统的建模。实验结果表明，这种预测方法具有简单、实用等特点，且能达到较高的精度。A short-term load forecasting technique for power system based on adaptive optimal fuzzy logic system is presented.Firstly,it groups the past data of power load using proximal distance clustering algorithm.Secondly,it treats any group of data (a cluster) as a data-pair,then models the load forecasting system using adaptive optimal fuzzy logic system.The results of the experiment prove that the forecasting system is simple and practical,and the forecasting precision is satisfactory.

关 键 词：短期负荷预测 模糊逻辑系统 数学模型 电力系统 

分 类 号：TM715[电气工程—电力系统及自动化]