考虑负荷不确定性与差异化需求的配电网网架结构混合多属性评价优选模型

传统配电网网架结构选择以定性决策为主，受人为因素影响大，决策繁琐。提出了一种考虑负荷不确定性与差异化需求的混合多属性评价优选模型。从拓扑结构、可靠性、经济性3个方面建立多属性评价指标体系，基于集对分析的混合多属性评价方法在评价过程中量化负荷不确定性，在此基础上进一步利用熵权法得到各指标客观权重及由指标权重表征的各网架性能；引入K-means聚类算法及模糊层次分析法建立多专家决策加权的需求方案静态获取模型，得到差异化需求方案以及指标主观权重；利用基于主客观权重及模糊熵的多属性关联关系分析模型，计算差异化需求方案与各备选网架的关联程度，最终建立考虑负荷不确定性与差异化需求的混合多属性评价优选模型。以多个地区的配电网规划为研究对象，利用所提出的混合多属性评价优选模型，分析了不同地区差异化需求下所适合建设的最优网架，验证了所提模型的有效性。

Mixed multi-attribute evaluation and optimization model for distribution network configuration considering load uncertainty and different demands

Traditional configuration selection of the distribution network is mainly based on qualitative decision making, which is greatly affected by human factors, and the decision-making process is complicated. A mixed multi-attribute evaluation optimization model considering load uncertainty and different demands is presented. A multi-attribute evaluation index system from three aspects of topology, reliability and economy is established. The mixed multi-attribute evaluation method based on set pair analysis is used to quantify the load uncertainty in the evaluation process, the entropy weight method is further used to obtain the objec-tive weight of each index and the performance of each network represented by the index weights. Then, the K-means clustering algorithm and the fuzzy analytic hierarchy process are used to established multi-expert decision-weighted static acquisition model of demand scheme to obtain different demand schemes and index subjective weights. The multi-attribute correlation analysis model based on subjective and objective weights and fuzzy entropy is used to analyze the correlation between the different demand schemes and each alterna-tive network, and finally a mixed multi-attribute evaluation optimization model that considers load uncertainty and different demands is established. Taking the distribution network planning in multiple regions as the research object, the proposed mixed multi-attribute evaluation and optimization model is used to analyze the optimal network suitable for construction in different regions, and the effectiveness of the proposed method is verified.