摘要
风电场解析模型的建立是利用解析法或非序贯蒙特卡洛模拟法进行发电系统充裕度评估的基础。提出了利用改进的k-均值聚类算法建立多级水平风电场概率模型;利用解析法对RBTS可靠性测试系统进行了算例分析。算例结果表明,基于所提出的聚类算法得出的风电场概率模型具有很高的计算精度和收敛速度,适合用于风电并网发电系统的充裕度评估。
The establishment of wind farm analytical model is the basis of evaluating the generation system adequacy when the enumeration method or non-sequential Monte Carlo method is employed. The improved k-means clustering method is proposed to model the multi-step wind farm output power probabilistic characteristic. The proposed modeling algorithm is validated in the RBTS by enumeration method. Case studies indicate that the wind farm models from the proposed algorithm has high calculation accuracy and convergence speed, and is appropriate for the generating adequacy evaluation containing wind power.
出处
《科技创新与应用》
2020年第24期7-10,共4页
Technology Innovation and Application
关键词
风电场
概率模型
K-均值聚类
充裕度
解析法
wind farm
probabilistic model
k-means clustering method
adequacy evaluation
enumeration method
