基于Kmeans和TOPSIS的电力系统黑启动方案分类评估

Classification and Evaluation of Power System BlackStart Schemes Based on Kmeans and TOPSIS

传统黑启动方案评估法因步骤繁琐,计算复杂,不仅会增加电力系统调度人员的决策时间,导致电力系统各断电机组不能迅速恢复,还会给社会带来巨大的经济损失和负面影响。本文将视野从决策学领域转向数据挖掘领域,提出一种基于Kmeans和TOPSIS的黑启动方案分类模型。并采用广东电网黑启动数据进行了验证,并利用已有的平均绝对偏差比较策略,对文章所提模型的方案排序与现有权威黑启动方案评估下的排序结果进行量化比较分析,证明了此模型的科学、有效性。

In order to solve the problem that the traditional black start scheme evaluation method has cumbersome steps and complex calculation,it will not only increase the decision-making time of power system dispatchers,lead to the failure of power system units to recover quickly,but also bring huge economic losses and negative impact to the society.This paper turns its vision from the field of decision-making to the field of data mining,and proposes a black start scheme classification model based on kmeans and TOPSIS.The black start data of Guangdong power grid are used for verification,and the existing average absolute deviation comparison strategy is used to quantitatively compare and analyze the scheme ranking of the model proposed in this paper with the ranking results under the evaluation of the existing authoritative black start scheme,which proves that the model is scientific and effective.