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

Hongliang Wu,Daoxin Peng,Ling Wang

doi:10.1155/2020/3568470

Hongliang Wu, Daoxin Peng + Show 1 more

Open Access

https://doi.org/10.1155/2020/3568470

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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.

Highlights

Introduction e Central Committee of theCommunist Party of China and the State Council formally issued “Several Opinions on Further Deepening the Reform of the Electric Power System” on March 15, 2015
E traditional assessment of power grid investment primarily focuses on technical indicators, and insufficient attention is given to economic and environmental benefit indicators. e many studies that address power grid investment assessment have limitations, and research on grid investment evaluation can be divided into the construction of evaluation index systems and the construction of evaluation models
Sun [14] realized evaluation research on grid investment by constructing an evaluation model based on an improved Data envelopment analysis (DEA) and Monte Carlo simulation; Yu [15, 16] used the value-at-risk theory introduced into a comprehensive energy system assessment and constructed an assessment based on the CVaR theory and multiobjective optimization index weighting models

Summary

Utility Evaluation Model considering Risk Preference

Is method takes into account the subjective consciousness of decision-makers and the objective characteristics of the data, minimizes deviations, and optimizes trends as the objective function of the integration weights. Because of the difference in the index deviation and taking into account the calculation rationality, the degree of emphasis of all indicators is assumed to be the same, and the objective function is obtained as follows: np nq min H ζ 􏽘 􏽘 􏼐wj − wsj􏼑2 + ψ 􏽘 􏽘 􏼐wj − wtj􏼑2. Because the results (especially of subjective weighting) of different weighting theories on the importance of indicators differ, the following trend-optimal objective function is constructed to integrate the weight results and better reflect the importance degree relationship between indicators: min G ζ n.

Evaluation result

Example Analysis

Utility Evaluation

A3 A5 B1 B2 C1 C2 D1 D2 D4