摘要
粗糙集理论是一种较新的软计算方法,可以有效地分析和处理不完备信息。近几年来,该理论日益受到国际学术界的重视,已在模式识别、预测建模、医疗诊断、决策分析等许多领域得到成功的应用。粗糙集理论在电力系统中的研究起步较晚,目前尚鲜见实际应用的报道。为了进一步推动粗糙集理论在电力系统广泛和深入地应用,文中综述了近年来粗糙集理论在电力系统设备故障诊断、配电网故障诊断、暂态稳定评估、电压无功控制、数据挖掘等方面应用研究的主要成果与方法。探讨了粗糙集理论在电力市场数据挖掘中的巨大潜力,以及与专家系统、人工神经网络、模糊理论和多代理系统等其他人工智能技术的相互结合问题,并提出了若干需要进一步研究的问题。
Rough set (RS) theory is a newly developed soft-computing tool to deal with information with vagueness and uncertainty. It has been received much attention of researchers around the world and applied to many domains successfully such as pattern recognition, predictive modeling and medical diagnosis and decision analysis, et al. But little headway has been made in power systems. In order to propel the further study on the aspect of RS in power systems, the main fruits of RS are surveyed in equipment fault diagnosis, electric distribution network fault diagnosis, transient stability classification, data mining and voltage and reactive power control respectively. Furthermore, the paper discusses the application potentials of RS in data mining in power market, and the combination of RS with other artificial intelligence technologies, such as expert system, ANN, fuzzy theory and multi-agent system. Meanwhile, several open problems are proposed.
出处
《电力系统自动化》
EI
CSCD
北大核心
2004年第3期90-95,共6页
Automation of Electric Power Systems
基金
国家自然科学基金资助项目(50347026)
云南省科技攻关项目(2003GG10
2000B2-02)
云南省应用基础研究项目(98E0409M
99E006G
2002E0025M)
云南省中青年学术和技术带头人培养经费资助项目
关键词
粗糙集
电力系统
人工智能
数据挖掘
rough set
power systems
artificial intelligence
data mining
