基于状态转移抽样法的包含风电场的发电系统Well-being分析  

The Analysis of Generation System Containing Wind Farm based on State Transition Sampling and Well-being Theory

作　　者：徐政[1] 陈凡[1] XU Zheng CHEN Fan(School of Electric Power Engineering, Nanj ing Institute of Technology, Nanjing 21116 7, China)

机构地区：[1]南京工程学院电力工程学院,南京211167

出　　处：《电力学报》2016年第5期384-390,共7页Journal of Electric Power

基　　金：江苏省高校自然科学研究项目(14KJD470004);江苏省配电网智能技术与装备协同创新中心开放基金项目资助(XTCX201612);江苏省大学生实践创新训练计划项目(201611276025Y);南京工程学院大学生科技创新基金项目(TB20160408)

摘　　要：基于状态转移抽样法对包含风电场的发电系统进行Well-being分析,提出了一种增强N-1准则,并基于此建立新的Well-being模型。在此Well-being模型基础上,以RST79系统为例,考虑风机故障模型以及尾流效应,分析风电场的接入容量以及不同风速模型对发电系统可靠性的影响。研究表明,增强N-1准则下的Well-being模型相对于传统N-1准则下的Well-being模型对系统健康状态标准要求更高,因此处于健康状态概率会有所下降。风电场的接入能有效改善系统的可靠性,但是风电场规模到达一定值后,其改善效果趋于饱和。不同风速模型下的Well-being概率指标相近,但是失负荷频率存在差别,ARMA模型最接近实际模型,而Weibull风速模型的失负荷频率与实际风速模型相差较大。This paper analyzes the reliability of power generation system with wind farm based on state tran- sition sampling and Well-being theory. A new model of Well-being is presented under the enhanced N-1 criterion. Effects of different sizes of wind farm and different wind-speed models on the generation reliabil- ity of RST79 are studied on account of the breakdown of wind turbine and wake effects. Studies demon- strate that the Well-being model based on enhanced N-1 criterion has a higher standard on healthy state than the model based on traditional N-1 criterion. Wind farm can improve the reliability of power system, but when the size reaches a number, the effect of improvement becomes saturated as the wind power in- creases. Though the possibility indexes in Well-being model are similar when different wind speed models are used. , there is still difference in loss of load frequency（LOLF）. LOLF obtained by ARMA model is like LOLF obtained by actual wind-speed model, while the LOLF obtained by Weibull model has a quite difference with LOLF obtained by actual wind-speed model.

关 键 词：发电系统可靠性 Well—being理论 状态转移抽样法 风速模型 

分 类 号：TM614[电气工程—电力系统及自动化]