Skip to main content

Advertisement

SpringerLink
Log in

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

  • Published:
International Journal of Fuzzy Systems Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

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

References

  1. Ahmad, S., Nadeem, A., Akhanova, G., Houghton, T., Muhammad-Sukki, F.: Multi-criteria evaluation of renewable and nuclear resources for electricity generation in Kazakhstan. Energy 141, 1880–1891 (2017). https://doi.org/10.1016/j.energy.2017.11.102

    Article  Google Scholar 

  2. Ahmad, S., Tahar, R.M.: Selection of renewable energy sources for sustainable development of electricity generation system using analytic hierarchy process: a case of Malaysia. Renew. Energy 63, 458–466 (2014). https://doi.org/10.1016/j.renene.2013.10.001

    Article  Google Scholar 

  3. Al Garni, H., Kassem, A., Awasthi, A., Komljenovic, D., Al-Haddad, K.: A multicriteria decision making approach for evaluating renewable power generation sources in Saudi Arabia. Sustain. Energy Technol. Assess. 16, 137–150 (2016). https://doi.org/10.1016/j.seta.2016.05.006

    Article  Google Scholar 

  4. Amer, M., Daim, T.U.: Selection of renewable energy technologies for a developing county: a case of Pakistan. Energy Sustain. Dev. 15(4), 420–435 (2011). https://doi.org/10.1016/j.esd.2011.09.001

    Article  Google Scholar 

  5. Andreopoulou, Z., Koliouska, C., Galariotis, E., Zopounidis, C.: Renewable energy sources: using PROMETHEE II for ranking websites to support market opportunities. Technol. Forecast. Soc. Chang. 131, 31–37 (2018). https://doi.org/10.1016/j.techfore.2017.06.007

    Article  Google Scholar 

  6. Aydin, N.Y., Kentel, E., Sebnem Duzgun, H.: GIS-based site selection methodology for hybrid renewable energy systems: a case study from western Turkey. Energy Convers. Manage. 70, 90–106 (2013). https://doi.org/10.1016/j.enconman.2013.02.004

    Article  Google Scholar 

  7. Brans, J.P., Vincke, P.: Note—A preference ranking organisation method. Manage. Sci. 31(6), 647–656 (1985). https://doi.org/10.1287/mnsc.31.6.647

    Article  MATH  Google Scholar 

  8. Büyüközkan, G., Güleryüz, S.: Evaluation of Renewable Energy Resources in Turkey using an integrated MCDM approach with linguistic interval fuzzy preference relations. Energy 123, 149–163 (2017). https://doi.org/10.1016/j.energy.2017.01.137

    Article  Google Scholar 

  9. Büyüközkan, G., Karabulut, Y.: Energy project performance evaluation with sustainability perspective. Energy 119, 549–560 (2017). https://doi.org/10.1016/j.energy.2016.12.087

    Article  Google Scholar 

  10. Büyüközkan, G., Karabulut, Y., Güler, M.: Strategic renewable energy source selection for turkey with hesitant fuzzy MCDM method. In: Kahraman, C., Kayakutlu, G. (eds.) Energy management—collective and computational intelligence with theory and applications, pp. 229–250. Springer International Publishing, Cham (2018)

    Chapter  Google Scholar 

  11. Çelikbilek, Y., Tüysüz, F.: An integrated grey based multi-criteria decision making approach for the evaluation of renewable energy sources. Energy 115, 1246–1258 (2016). https://doi.org/10.1016/j.energy.2016.09.091

    Article  Google Scholar 

  12. Çolak, M., Kaya, İ.: Prioritization of renewable energy alternatives by using an integrated fuzzy MCDM model: a real case application for Turkey. Renew. Sustain. Energy Rev. 80, 840–853 (2017). https://doi.org/10.1016/j.rser.2017.05.194

    Article  Google Scholar 

  13. Haddad, B., Liazid, A., Ferreira, P.: A multi-criteria approach to rank renewables for the Algerian electricity system. Renew. Energy 107, 462–472 (2017). https://doi.org/10.1016/j.renene.2017.01.035

    Article  Google Scholar 

  14. Hu, X., Wang, H., Tang, X.: Cyber-physical control for energy-saving vehicle following with connectivity. IEEE Trans. Industr. Electron. 64(11), 8578–8587 (2017). https://doi.org/10.1109/TIE.2017.2703673

    Article  Google Scholar 

  15. Jian, X., Jin, F.: CNREC: China renewable energy outlook 2018. Int. Financ. 2, 11–14 (2019)

    Google Scholar 

  16. Kahneman, D., Tversky, A.: Prospect theory: an analysis of decision under risk. Econometrica 47(2), 263–291 (1979). https://doi.org/10.1142/9789814417358_0006

    Article  MathSciNet  MATH  Google Scholar 

  17. Li, Y.Y., Zhang, H.Y., Wang, J.Q.: Linguistic neutrosophic sets and its application to multi-criteria decision-making problems. Int. J. Uncertain. Quantif. 7(2), 135–154 (2017). https://doi.org/10.1615/Int.J.UncertaintyQuantification.2017019627

    Article  Google Scholar 

  18. Liang, R.X., Wang, J.Q., Zhang, H.Y.: Projection-based PROMETHEE methods based on hesitant fuzzy linguistic term sets. Int. J. Fuzzy Syst. 20(7), 2161–2174 (2018). https://doi.org/10.1007/s00521-016-2672-2

    Article  Google Scholar 

  19. Lin, S., Li, C., Xu, F., Liu, D., Liu, J.: Risk identification and analysis for new energy power system in China based on D numbers and decision-making trial and evaluation laboratory (DEMATEL). J. Clean. Prod. 180, 81–96 (2018). https://doi.org/10.1016/j.jclepro.2018.01.153

    Article  Google Scholar 

  20. Liu, G.: Development of a general sustainability indicator for renewable energy systems: a review. Renew. Sustain. Energy Rev. 31, 611–621 (2014). https://doi.org/10.1016/j.rser.2013.12.038

    Article  Google Scholar 

  21. Liu, P., Cheng, S., Zhang, Y.: An extended multi-criteria group decision-making PROMETHEE method based on probability multi-valued neutrosophic sets. Int. J. Fuzzy Syst. 21(2), 388–406 (2019)

    Article  Google Scholar 

  22. Liu, Y., Wang, X., Wang, J., Li, L., Cheng, P.: Cloud model-based PROMETHEE method under 2D uncertain linguistic environment. J. Intell. Fuzzy Syst. (2020). https://doi.org/10.3233/JIFS-191546

    Article  Google Scholar 

  23. Malkawi, S., Al-Nimr, M.D., Azizi, D.: A multi-criteria optimization analysis for Jordan’s energy mix. Energy 127, 680–696 (2017). https://doi.org/10.1016/j.energy.2017.04.015

    Article  Google Scholar 

  24. Nie, R.X., Wang, J.Q.: Prospect theory-based consistency recovery strategies with multiplicative probabilistic linguistic preference relations in managing group decision making. Arab. J. Sci. Eng. 45(3), 2113–2130 (2020). https://doi.org/10.1007/s13369-019-04053-9

    Article  Google Scholar 

  25. Peng, J.J., Tian, C., Zhang, W.Y., Zhang, S., Wang, J.Q.: An integrated multi-criteria decision-making framework for sustainable supplier selection under picture fuzzy environment. Technol. Econ. Devel. Econ. (2020). https://doi.org/10.3846/tede.2020.12110

    Article  Google Scholar 

  26. Phong, P.H., Cuong, B.C.: Multi-criteria group decision making with picture linguistic numbers. J. Sci. Comp. Sci. Com. Eng. 33(3), 39–52 (2016). http://repository.vnu.edu.vn/handle/VNU_123/56914

  27. Pinna-Hernández, M.G., Martínez-Soler, I., Díaz Villanueva, M.J., Acien Fernández, F.G., López, J.L.C.: Selection of biomass supply for a gasification process in a solar thermal hybrid plant for the production of electricity. Ind. Crops Prod. 137, 339–346 (2019). https://doi.org/10.1016/j.indcrop.2019.04.060

    Article  Google Scholar 

  28. Qiao, D., Shen, K., Wang, J., Wang, T.: Multi-criteria PROMETHEE method based on possibility degree with Z-numbers under uncertain linguistic environment. J. Ambient Intell. Human. Comput. 11(5), 2187–2201 (2020). https://doi.org/10.1007/s12652-019-01251-z

    Article  Google Scholar 

  29. Ren, J., Lützen, M.: Selection of sustainable alternative energy source for shipping: multi-criteria decision making under incomplete information. Renew. Sustain. Energy Rev. 74, 1003–1019 (2017). https://doi.org/10.1016/j.rser.2017.03.057

    Article  Google Scholar 

  30. San Cristóbal, J.R.: Multi-criteria decision-making in the selection of a renewable energy project in spain: the VIKOR method. Renew. Energy 36(2), 498–502 (2011). https://doi.org/10.1016/j.renene.2010.07.031

    Article  Google Scholar 

  31. Şengül, Ü., Eren, M., Eslamian Shiraz, S., Gezder, V., Şengül, A.B.: Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey. Renew. Energy 75, 617–625 (2015). https://doi.org/10.1016/j.renene.2014.10.045

    Article  Google Scholar 

  32. Shen, K., Li, L., Wang, J.: Circular economy model for recycling waste resources under government participation: a case study in industrial waste water circulation in China. Technol. Econ. Dev. Econ. 26(1), 21–47 (2020)

    Article  Google Scholar 

  33. Shen, K.W., Wang, X.K., Qiao, D., Wang, J.Q.: Extended Z-MABAC method based on regret theory and directed distance for regional circular economy development program selection with Z-information. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2923948

    Article  Google Scholar 

  34. Tian, C., Peng, J., Zhang, W., Zhang, S., Wang, J.: Tourism environmental impact assessment based on improved AHP and picture fuzzy PROMETHEE II methods. Technol. Econ. Dev. Econ. 26(2), 355–378 (2020). https://doi.org/10.3846/tede.2019.11413

    Article  Google Scholar 

  35. Tian, Z.P., Nie, R.X., Wang, J.Q., Luo, H.Y., Li, L.: A prospect theory-based QUALIFLEX for uncertain linguistic Z-number multi-criteria decision-making with unknown weight information. J. Intell. Fuzzy Syst. 38(2), 1775–1787 (2020). https://doi.org/10.3233/JIFS-190065

    Article  Google Scholar 

  36. Tian, Z.P., Wang, J., Wang, J.Q., Zhang, H.Y.: Simplified neutrosophic linguistic multi-criteria group decision-making approach to green product development. Group Decis. Negot. 26(3), 597–627 (2017). https://doi.org/10.1007/s10726-016-9479-5

    Article  Google Scholar 

  37. Troldborg, M., Heslop, S., Hough, R.L.: Assessing the sustainability of renewable energy technologies using multi-criteria analysis: suitability of approach for national-scale assessments and associated uncertainties. Renew. Sustain. Energy Rev. 39, 1173–1184 (2014). https://doi.org/10.1016/j.rser.2014.07.160

    Article  Google Scholar 

  38. Wang, C.C., Davidson, F., Trivedi, S.: Moving space-charge field effects in photoconductive semiconductors with interband optical excitation of free charge carriers. J. Opt. Soc. Am. B 14(1), 21–26 (1997). https://doi.org/10.1364/JOSAB.14.000021

    Article  Google Scholar 

  39. Wang, L., Wang, X.K., Peng, J.J., Wang, J.Q.: The differences in hotel selection among various types of travellers: a comparative analysis with a useful bounded rationality behavioural decision support model. Tour. Manage. 76, 103961 (2020). https://doi.org/10.1016/j.tourman.2019.103961

    Article  Google Scholar 

  40. Wang, L., Zhang, H., Wang, J.Q., Wu, G.F.: Picture fuzzy multi-criteria group decision making method to hotel building energy efficiency retrofit project selection. Oper. Res. 54(1), 211–229 (2020). https://doi.org/10.1051/ro/2019004

    Article  MathSciNet  MATH  Google Scholar 

  41. Wang, L., Zhang, H.Y., Wang, J.Q., Li, L.: Picture fuzzy normalized projection-based VIKOR method for the risk evaluation of construction project. Appl. Soft Comput. 64, 216–226 (2018)

    Article  Google Scholar 

  42. Wang, Y., Liang, Z., Wu, S., Han, Z., Ren, X.: Idiopathic ventricular arrhythmias originating from the right coronary sinus: prevalence, electrocardiographic and electrophysiological characteristics, and catheter ablation. Heart Rhythm 15(1), 81–89 (2018). https://doi.org/10.1016/j.hrthm.2017.09.008

    Article  Google Scholar 

  43. Xiao, F., Wang, J.: Multistage decision support framework for sites selection of solar power plants with probabilistic linguistic information. J. Clean. Prod. 230, 1396–1409 (2019). https://doi.org/10.1016/j.jclepro.2019.05.138

    Article  Google Scholar 

  44. Xu, J., Wang, X.: Self-healing of concrete cracks by use of bacteria-containing low alkali cementitious material. Constr. Build. Mater. 167, 1–14 (2018). https://doi.org/10.1016/j.conbuildmat.2018.02.020

    Article  Google Scholar 

  45. Ye, X.H.: China renewable energy development report 2017. Water Power 44(12), 23 (2018)

    Google Scholar 

  46. Yu, H., Liu, P., Jin, F.: Research on the stochastic hybrid multi-attribute decision making method based on prospect theory. Scientia Iranica. Transaction E, Industrial Engineering 21(3), 1105–1119 (2014)

    Google Scholar 

  47. Yuan, J., Li, C., Li, W., Liu, D., Li, X.: Linguistic hesitant fuzzy multi-criterion decision-making for renewable energy: a case study in Jilin. J. Clean. Prod. 172, 3201–3214 (2018). https://doi.org/10.1016/j.jclepro.2017.11.038

    Article  Google Scholar 

  48. Zeng, M., Liu, X.M., Li, Y.L., Peng, L.L.: Review of renewable energy investment and financing in China: status, mode, issues and countermeasures. Renew. Sustain. Energy Rev. 31, 23–37 (2014). https://doi.org/10.1016/j.rser.2013.11.026

    Article  Google Scholar 

  49. Zhang, L., Xin, H., Yong, H., Kan, Z.: Renewable energy project performance evaluation using a hybrid multi-criteria decision-making approach: case study in Fujian, China. J. Clean. Prod. 206, 1123–1137 (2019). https://doi.org/10.1016/j.jclepro.2018.09.059

    Article  Google Scholar 

  50. Zhong, L., Yao, L.: An ELECTRE I-based multi-criteria group decision making method with interval type-2 fuzzy numbers and its application to supplier selection. Appl. Soft Comput. 57, 556–576 (2017). https://doi.org/10.1016/j.asoc.2017.04.001

    Article  Google Scholar 

  51. Zhou, H., Wang, J.Q., Zhang, H.Y.: Stochastic multi-criteria decision-making approach based on SMAA-ELECTRE with extended grey numbers. Int. Trans. Operat. Res. 26(5), 2032–2052 (2019). https://doi.org/10.1111/itor.12380

Download references

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).

Author information

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

Authors
  1. Ting Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yi-ting Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jian-qiang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lin Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Peng-Fei Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peng-Fei Cheng.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-020-00858-1

Keywords

Search

Navigation