Research on Utility Evaluation of Grid Investment considering Risk Preference of Decision-Makers

Abstract

Effectiveness evaluations are one of the important ways to guide grid investment and to improve investment efficiency. Improving the effectiveness of grid investment evaluations is studied based on the optimization of the investment evaluation index system and the utility evaluation model. The index system is optimized by establishing an evaluation index system of grid investment effectiveness, considering the redundancy between the indices, and constructing an ISM-DEA model. The utility function model was introduced to fully consider the different risk appetites of decision-makers, and a utility evaluation model that takes risk appetite into account was established. An improved weight integration model based on multiobjective optimization was established by considering the minimum deviation and the trend-optimal objective function when setting the index weights. The calculation results show that the feasibility of the index system optimization model and utility evaluation model constructed in this study is verified under the premise of satisfying the assumptions. By adjusting the risk preference coefficient of decision-makers, the dynamic optimization of the grid investment utility evaluation results can be realized.

Investment Efficiency Assessment of Distribution Network for the High Proportion of Renewable Energy: A Hybrid Multiattribute Decision-Making Method

“…By solving equation (7), the optimal fuzzy weights value of each criterion can be obtained, which are the fnal fuzzy weights of each evaluation index W � ( 􏽥 w * 1 , 􏽥 w * 2 , . .…”

“…Combining equation ( 3) with the fuzzy comparison vectors corresponding to the optimal index and the worst index, the optimal fuzzy weight vectors of the four frst-level indexes are obtained, which are as follows: Te optimal weight is obtained according to equation (7): 􏽥 w * 1 � 0.14, 􏽥 w * 2 � 0.29, and 􏽥 w * 3 � 0.57 Te best and worst indexes of the evaluation indexes corresponding to the three frst-level indexes are shown in Table 7.…”

“…Te power industry is a complex system with countless uncertainties, which is unlikely to meet the basic needs of econometric models [6]. Te DEA model is suitable for complex distribution network systems with multiple input and output indexes and can be better applied to evaluate power distribution network investment efciency in various directions, such as distribution network operation, economic efciency, and social and environmental efciency [7][8][9][10]. However, the DEA method has higher requirements on data and mainly focuses on the relative efciency of the evaluation object.…”