自适应模糊系统理论在负荷预测中的应用研究  

Application Research of Adaptive Fuzzy System Theory in Load Forecasting

作　　者：郁滨[1] 张昊[2] 吴捷[3] 钟慕良[3] 毛宗源[3] 

机构地区：[1]华南理工大学自动控制工程系 [2]广东省科学院自动化工程研制中心 [3]华南理工大学

出　　处：《控制与决策》1999年第3期223-228,共6页Control and Decision

基　　金：广东省科学院院长基金;广东省电力工业重大科技项目基金

摘　　要：应用自适应模糊系统理论的最新成果实现实用化的预测系统，并以电力电负荷预测为具体应用背景完成了实验研究。系统的建立和运行分别依赖于对历史数据和实时数据的离线和在线学习，具有明显的自适应性和鲁棒性。通过合理的设计实现简洁的系统结构，通过在线训练确定优化的系统设置，短期负荷预测的日均相对误差小于２％，可以满足现场的实用化要求。This paper discussed application problems of adaptive fuzzy system theory in power load forecasting. The establishment of the system was based on off-line study form historical data and its running was depended on adaptive study from real time data. Thus, the system is provided with extinguished adaptive feature and self-learning capability. Simple system structure was achieved by reasonable design and optimal parameters were obtained by on-line training. Experiment result with daily short-term load forecasting relative error less than 2% demonstrates that the intelligent system can meet applying engineering demand.

关 键 词：模糊系统 负荷预测 自适应学习 电力系统 

分 类 号：TM715[电气工程—电力系统及自动化] N94[自然科学总论—系统科学]