论文部分内容阅读
基于马尔科夫链,提出一种含风电场的发电系统可靠性解析计算方法,该方法综合考虑风电场风速波动的随机性及不同类型风电机组故障的影响,将可用容量状态概率及增量频率的应用从机组、负荷拓展到对风电场可用容量的分析中,分别构建常规发电机、负荷及风电场可用容量的概率及频率分布(函数).通过应用该方法,包括概率型、频率及持续时间型等指标在内的含风电场的发电系统可靠性指标可完全由概率及频率分布函数的卷积和加法运算得到,使得含风电场的发电系统可靠性评估变得简洁和方便.此外,还提出优化随机变量状态聚类数取值的方法,以提高基于马尔科夫链对多状态时序随机变量进行建模的准确性.最后,对修改后的IEEE-RTS79测试系统进行评估分析,说明方法的有效性,结果表明该方法能快速准确地实现含风电场的发电系统可靠性评估.“,”On the basis of Markov chain,this paper presented an analytical method for reliability evaluation of generation systems with wind farm.In this method,the concept of state probability and incremental frequency for available capacity which had been used on generator units or loads was applied to wind farm considering the stochastic characteristics of wind speed and the effect of wind turbine outage.The probability-frequency distribution functions for available capacity of conventional generator,load and wind farm were constructed respectively.Through the proposed method,the reliability index including the probability,frequency and duration index of generation systems with wind farm can be acquired by convolution and addition operation of the probability-frequency distribution functions,to simplify the reliability evaluation.Moreover,this paper also presented an optimization method for the clustering number of random state to improve the accuracy of Markov model of multi-state time series random variables.Finally,an example of modified IEEE-RTS79 test system testified the validity of this proposed method and corresponding results showed that the reliability of the generation system with wind farm can be evaluated efficiently and accurately through the proposed method.