基于Vague值相似度的黑启动决策

黑启动是电力系统恢复的第一个阶段，发展黑启动优化策略对电力系统大停电后的快速恢复具有重要意义。现有的黑启动决策大多利用单一的精确值评价指标，其不能体现黑启动决策信息的不完全性与不确定性。在此背景下，采用Vague值表示黑启动决策中的指标值和权重，并从候选方案与理想方案的相似度出发，提出一种基于Vague值相似度的黑启动决策方法。与现有的黑启动模糊决策方法相比，所提方法利用的主观信息少，而是充分利用指标间的客观信息，并通过比较侯选方案和理想方案的相似性快速得到各方案的优劣排序，可为实现在线黑启动决策提供支持。最后，用算例说明了所提方法的可行性与有效性。

Black-start Decision-making Based on Similarity Measures between Vague Sets

Black-start is the first stage of power system restoration， thus determining the optimal black-start strategy is vital for the quick restoration of a power system. In most existing black-start decision-making methods the evaluation index is represented as a single value， and the incompleteness and uncertainty of the obtained information are hardly considered. Given this background， the Vague set is used to represent the value and its weight of the evaluation index. In consideration of the similarity measures between a candidate strategy and an ideal one， a black-start decision-making method based on the similarity measures between two Vague sets is proposed. Compared with the existing fuzzy decision-making methods， the presented method requires less subjective information and makes full use of objective information in the evaluation index. This method could determine the priority of a candidate strategy quickly and provide support for the real-time black-start decision-making by comparing the similarity between a candidate strategy and an ideal one. Finally， the feasibility and effectiveness of the proposed method are demonstrated in an actual black-start scenario.