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 objective 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 alternative 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. © 2020, Electric Power Automation Equipment Press. All right reserved.