A hybrid group-making decision framework for regional distribution network outage loss assessment based on fuzzy best-worst and MARCOS methods

Abstract

Scientifically assessing the outage loss of regional distribution networks is conducive to the supplying-power enterprises and government to formulate development plans. The purpose of this study is to develop a systematic group decision-making framework to effectively solve the problem of outage loss assessment. Firstly, a multi-dimensional index system containing qualitative and quantitative attributes is established. Then, a relative entropy-based (RE-based) approach that incorporates fuzzy proximity and fuzzy similarity entropy weights is employed to determine experts’ dynamic weights. Subsequently, the fuzzy best-worst method (BWM) is presented to identify optimal criteria weights, thereby retaining the originality of weight information. Finally, the alternatives are rank-ordered based on the fuzzy MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) method by determining utility functions in relation to ideal and anti-ideal solutions. A case study is conducted based on the developed framework. The sufficient sensitivity analysis illustrates that the method adopted in this paper provides good robustness to fluctuations in criteria weights, and comparative analysis verifies the applicability and effectiveness of the framework. This study offers the scientific basis and decision support for the deployment of reducing regional distribution network outage loss and enriches the research methods and practical applications of the decision-making field. • A hybrid framework is given for regional distribution network outage loss assessment. • A comprehensive index system with qualitative and quantitative attributes is built. • The dynamic weights of experts are obtained by combining fuzzy PEW and fuzzy SEW. • Fuzzy best-worst method is adopted to determine the weights of evaluation attributes. • The fuzzy MARCOS enables a more flexible and effective decision-making.