基于差异性权重和协同过滤的黑启动方案评估

黑启动方案的优选对电力系统快速恢复供电具有重要意义。已有黑启动方案优选问题的研究均是在指标值数据完备的理想条件下进行,文中针对不完全信息下的电力系统黑启动方案评价问题展开研究,提出一种差异性权重和协同过滤相结合的综合评价模型。首先,根据原始评价数据计算指标间的差异性,得到差异性权重;然后,采用协同过滤方法预测缺失数据,获得完全评价矩阵;最后,计算每个方案的评分值,实现黑启动方案的完全排序。以天津电网的实际黑启动方案数据为基础进行了验证,验证结果表明了所提方法的有效性。

Assessment of Black start Schemes Based on Difference Weight and Collaborative Filtering

Rational selection of a black start scheme is of great significance to rapid restoration of power systems. Previous studies on optimal selection of black start schemes mostly focus on ideal condition of complete evaluation information. This paper proposes a comprehensive evaluation model based on difference weight and collaborative filtering, which can address the issue of assessing black start schemes under the condition of incomplete evaluation information. First, differences between indices are computed based on the raw evaluation data to obtain difference weights. Then the missing data is inputed by the collaborative filtering approach for a complete evaluation matrix. Finally, the score of each scheme is calculated to sort the black start schemes. Experiments are carried out based on the data of black start path of Tianjin power grid. The results show the effectiveness of the proposed approach. This work is supported by National Natural Science Foundation of China (No. 71201145), Innovation Program of Shanghai Municipal Education Commission (No. 15ZS064), and Research Fund of Shanghai University of Electric Power (No. K2014 037).