Published May 2021 | Version v1
Journal article

Evaluation of energy management system for regional integrated energy system under interval type-2 hesitant fuzzy environment

  • 1. Business School, University of Shanghai for Science and Technology, Shanghai, 200093 (China)
  • 2. School of Economics and Management, North China Electric Power University, Beijing, 102206 (China)

Description

Highlights: • Energy management system for regional integrated energy system is assessed. • An innovation evaluation criteria system is constructed from five aspects. • Hesitant fuzzy linguistic term set is used to depict double uncertainties. • A ranking model considering properties of criteria and risk preference is proposed. • A case study shows that the developed framework has good practicability. Selecting an energy management system for regional integrated energy system (EMS-RIES) is essential to improve energy management. But there lacks an EMS-RIES selection research. Meanwhile, some main issues, such as information loss, criteria interaction, properties of criteria, and risk preference, can influence the decision precision largely and have not been handled together in current decision researches. To fill these gaps, this study develops an integrated decision framework. Firstly, an evaluation criteria system is established from five dimensions. Secondly, double uncertainties on the degree of impact between criteria and criteria performances of each alternative are depicted by credibility-based hesitant fuzzy linguistic term set to reduce information loss. Thirdly, a combination weight method is used to determine criteria weight and interaction between criteria are investigated. Then, a cumulative prospect theory modified PROMETHEE II model considering properties of criteria and risk preference simultaneously is applied to rank the alternatives. Finally, a case study verifies the feasibility and practicability of the developed framework, and the final performances of alternatives are influenced by weight changing, properties of criteria, and risk preference. Furthermore, the comparative analysis shows that the proposed model has superiority to reveal the differences between alternatives due to its big distinction degree.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.energy.2021.119860

Additional details

Identifiers

DOI
10.1016/j.energy.2021.119860;
PII
S0360544221001092;

Publishing Information

Journal Title
Energy (Oxford)
Journal Volume
222
Journal Page Range
vp.
ISSN
0360-5442
CODEN
ENEYDS

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
53123532
Subject category
S29: ENERGY PLANNING, POLICY AND ECONOMY; S42: ENGINEERING;
Descriptors DEI
ENERGY MANAGEMENT; ENERGY MANAGEMENT SYSTEMS; FUZZY LOGIC; PERFORMANCE
Descriptors DEC
CONTROL SYSTEMS; ENERGY SYSTEMS; MANAGEMENT; MATHEMATICAL LOGIC

Optional Information

Copyright
Copyright (c) 2021 Elsevier Ltd. All rights reserved.