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Multistage Decision Framework for the Selection of Renewable Energy Sources Based on Prospect Theory and PROMETHEE

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Abstract

The selection of appropriate renewable energy sources (RESs) for a region is a complex multi-criteria decision-making problem because the RES selection process involves many factors, such as economic, environmental, technological and societal. Hence, to address this problem, this paper proposes a multistage framework for selecting a suitable RES alternative by integrating picture linguistic fuzzy numbers (PLFNs), preference ranking organization method for enrichment evaluations II (PROMETHEE II) and prospect theory (PT). First, PLFNs are used to describe the evaluation information. Second, using the proposed picture linguistic fuzzy weighed Heronian distance measurement, this paper proposes an extended maximizing deviation method that can capture the interrelationships among criteria. Third, an extended PROMETHEE II, which considers the bounded rationality of decision-makers, combined with PT is developed. Finally, the proposed framework solves a RES selection problem in northwest of China. The result shows solar energy is the best choice, followed by wind, hydro and biomass energy. Sensitivity analysis is conducted to explore the effects of the parameters on the results. The advantages of the proposed method are verified through a comparative analysis.

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Abbreviations

\(\rho\), \(\gamma\), \(\kappa\) :

Parameters in prospect theory

\(f\) :

Linguistic scale function

\(d_{g} \left( {p_{1} ,p_{2} } \right)\) :

Distance between picture linguistic fuzzy numbers

\(D = \left( {\delta_{ij} } \right)_{m \times n}\) :

Initial evaluation matrix

\(E_{ij} = \left( {e_{ij} } \right)_{m \times n}\) :

Normalized evaluation matrix

\(Dev_{j}\) :

Unweighted deviation of alternatives under criteria \(C_{j}\)

\(p_{j} \left( {A_{i} ,A_{h} } \right)\) :

The degree of alternative \(A_{i}\) is superior to others under criteria \(C_{j}\)

\(s\), \(t\) :

Indifference threshold in the preference function

PT:

Prospect theory

DM:

Decision maker

PLFSs:

Picture linguistic fuzzy sets

E-MDM:

Extended maximizing deviation method

RES:

Renewable energy source

\(S = \left\{ {\left. {s_{i} } \right|i = 0,2, \ldots ,2t} \right\}\) :

Linguistic term set

\(A_{m} = \left\{ {A_{1} ,A_{2} , \ldots ,A_{m} } \right\}\) :

Renewable energy source alternatives

\(C_{n} = \left\{ {C_{1} ,C_{2} , \ldots ,C_{n} } \right\}\) :

Evaluation criteria

\(\omega_{j} {\kern 1pt} {\kern 1pt} {\kern 1pt} {\kern 1pt}\) :

Weight of criteria

\(R = \left( {r_{j} } \right)_{n}\) :

Reference point alternative

\(V\) :

Perceptual distance

\(P\left( {A_{i} ,A_{h} } \right)\) :

Alternative \(A_{i}\) is superior to \(A_{h}\) under all criteria

\(x\),\(y\) :

Parameters in Heronian mean operator

\(B_{k} = \left\{ {B_{1} ,B_{2} , \ldots ,B_{k} } \right\}\) :

Evaluation criteria of experts

PLFNs:

Picture linguistic fuzzy numbers

PROMETHEE:

Preference ranking organization method for enrichment evaluations

PLFWHD:

Picture linguistic fuzzy weighed Heronian distance

Ref.:

Reference

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Acknowledgement

The authors are very grateful to the anonymous reviewers for their valuable comments and suggestions to help improve the overall quality of this paper. This work was supported by the National Natural Science Foundation of China (No. 71871228).

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Authors and Affiliations

  1. School of Business, Central South University, Changsha, 410083, People’s Republic of China

    Ting Chen, Yi-ting Wang & Jian-qiang Wang

  2. School of Business, Hunan University, Changsha, 410082, People’s Republic of China

    Lin Li

  3. Hunan Engineering Research Center for Intelligent Decision Making and Big Data on Industrial Development, Hunan University of Science and Technology, Xiangtan, 411201, China

    Jian-qiang Wang & Peng-Fei Cheng

  4. School of Business, Hunan University of Science and Technology, Xiangtan, 411201, China

    Peng-Fei Cheng

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  1. Ting Chen
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Correspondence to Peng-Fei Cheng.

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Chen, T., Wang, Yt., Wang, Jq. et al. Multistage Decision Framework for the Selection of Renewable Energy Sources Based on Prospect Theory and PROMETHEE. Int. J. Fuzzy Syst. 22, 1535–1551 (2020). https://doi.org/10.1007/s40815-020-00858-1

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