期刊文献+

基于模糊理论的地区电网在线供电风险分析方法研究 被引量:1

Method study of on-line risk analysis for district grid
下载PDF
导出
摘要 为了更加准确地衡量地区电网的运行风险,提出了地区电网在线供电风险分析计算方法;风险指标的计算中采用基于元件运行状态及模糊理论建立的室外元件的加权故障概率模型,使风险指标能够反映外界环境因素的影响。该加权故障概率模型主要考虑雷电、风速、线路覆冰和气温的影响,选择各自适用的隶属度函数,综合考虑各影响因素得到修正系数,对由历史统计数据得出的架空线路强迫停运率进行修正。基于该算法对WSCC9节点系统进行仿真分析,验证了该算法的有效性。 In order to more accurately measure the running risks of the district power grid,this paper presents a method of on-line risk analysis for district grid.The calculation of risk indicators uses the weighted fault probability model of the overhead line which is based on equipment operating status and fuzzy theory,and the risk indicators can reflect the influence of environmental factors.In this model,the proper membership function is adopted to describe the influence of lightning,wind speed,line ice and temperature,and the outage rate of overhead line,derived from historical statistics,is amended.By making full use of operating experience of dispatchers,the fuzzy membership function boundary conditions are determined.Therefore,the problem of lacking historical statistics is solved.Based on this method,the power supply risk analysis software can be developed to calculate the online risk indicators of district grid,and the simulation results for WSCC9 system verify the effectiveness of the method.
出处 《电工电能新技术》 CSCD 北大核心 2014年第12期60-64,70,共6页 Advanced Technology of Electrical Engineering and Energy
关键词 地区电网 故障概率模型 风险分析 模糊理论 district grid fault probability model risk analysis fuzzy theory
  • 相关文献

参考文献7

二级参考文献62

共引文献303

同被引文献15

  • 1岳士弘,张绍杰,李平.变论域自适应模糊控制器失真率的计算[J].控制理论与应用,2005,22(5):807-809. 被引量:5
  • 2F A Farret, L L Pfitscher, D P Bernardon. Sensorless active yaw control for wind turbines [A]. The 27th Annual Conference of the IEEE Industrial Electronics Society, IECON’01 [C]. 2001. 2:1370-1375.
  • 3Mona M, Karolos M Grigoriadis. Anti-windup linear parameter-varying control of pitch actuators in wind turbines [J]. Wind Energy, 2015, 18(2):187-200.
  • 4Hassan H M, Eishafei A L, Farag W A, et al. A robust LMI-based pitch controller for large wind turbines [J]. Renewable Energy,2012, 44:63-71.
  • 5X N Lin, Y X Zhuo, F Zhao, et al. Voltage sag problems in large-scale clustering wind farms[J]. IEEJ Transactions on Electrical and Electronic Engineering, 2015, 10(1): 63-69.
  • 6Christof D, Wout W, Mahmoud E. Monitoring resonant frequencies and damping values of an offshore wind turbine in parked conditions [J]. IET Renewable Power Generation, 2014, 8(4): 433-441.
  • 7I Houtzager, J W Wingerden, M Verhaegen. Wind turbine load reduction by rejecting the periodic load disturbances [J]. Wind Energy, 2013,16(2):235-256.
  • 8Jauch C, Islam S M, Nsen P S, et al. Design of a wind turbine pitch angle controller for power system stabilization [J]. Renewable Energy, 2007, 32(14): 2334-2349.
  • 9Bianchi F D, Mantz R J, Christiansen C F. Gain scheduling control of variable speed wind energy conversion systems using quasi-LPV models [J].Control Engineering Practice,2005,13(2):247-255.
  • 10K Tan, S Islam. Optimal control strategies in energy conversion of PMSG wind turbine system without mechanical sensors [J]. IEEE Transactions on Energy Conversion, 2004, 19(2): 392-399.

引证文献1

二级引证文献7

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部