| 引用本文: | 杨家莉,徐永海.基于组合赋权与TOPSIS模型的节点电压暂降严重程度综合评估方法[J].电力系统保护与控制,2017,45(18):88-95.[点击复制] |
| YANG Jiali,XU Yonghai.Comprehensive evaluation method of node voltage sag severity based on TOPSIS model and combination weights[J].Power System Protection and Control,2017,45(18):88-95[点击复制] |
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| 摘要: |
| 提出了一种基于组合赋权与TOPSIS模型的节点电压暂降严重程度综合评估方法。以SARFI指标、平均暂降能量指标ASEI与暂降严重性指标SSI为元素建立属性集合。采用熵权法与变异系数法计算各指标组合权值，结合TOPSIS模型提出了电压暂降严重程度综合评估方法。通过比较各节点与TOPSIS模型中正理想解相对近似度大小，判断暂降严重程度。使用该方法对某城市电网电压暂降进行评估，利用节点分级方法将模型评估结果与各指标评估结果进行对比分析。结果证明，该方法既能凸显指标间评估结果的一致性，又能缩小其差异性，所得结果客观和准确，更符合实际。 |
| 关键词: 电压暂降 熵权法 变异系数法 组合权值 TOPSIS模型 相对近似度 |
| DOI：10.7667/PSPC161402 |
| 投稿时间：2016-08-29修订日期：2017-02-15 |
| 基金项目:国家自然科学基金资助(51277069) |
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| Comprehensive evaluation method of node voltage sag severity based on TOPSIS model and combination weights |
| YANG Jiali,XU Yonghai |
| (State Grid Lanzhou Electric Power Supply Company, Lanzhou 730300, China;State Key Laboratory Electrical Power System with Renewable Energy Sources North China Electric Power University, Beijing 102206, China) |
| Abstract: |
| This paper proposes a comprehensive evaluation method of node voltage sag severity based on combination weights and TOPSIS model. The SARFI, average temporarily reduced energy index ASEI and sag severity index SSI are regarded as elements to establish the set of attributes. Entropy weight method and coefficient of variation method are used to calculate combination weights of indexes and the voltage sag severity comprehensive evaluation method based on TOPSIS model is established. The sags severity is determined by comparing size of the relative approximate degree of various nodes distance from the positive ideal solution of TOPSIS model. The model is used to assess the grid voltage sag for a certain city. Model assessment results and the index evaluation results are compared from the aspect of the node classification. The results show that the model can highlight the consistency of index evaluation results and reduce the difference, and the results are objective, accurate and more realistic. This work is supported by National Natural Science Foundation of China (No. 51277069). |
| Key words: voltage sag entropy method variation coefficient method combination weights TOPSIS model relative approximate degree |
