A Bibliometric Review on Decision Approaches for Clean Energy Systems under Uncertainty
Abstract
:1. Introduction
- Fuzzy sets are key concepts that are used for modeling uncertainty in the decision process associated with CES.
- Most of the literature studies obtain data as rating information in the Likert-scale form and transform them into fuzzy values to generate decisions.
- The criteria for such applications are competing and conflicting with one another, and the estimation of their relative importance is considered a crucial stage in the existing framework.
- Utility function-based formulation and distance measure-based formulation are popular in ranking CESs and their associated options.
- Earlier literature reviews have also claimed that the assessment of CESs using multi-criteria decision making (MCDM) will grow due to the nature of the problem and the efficacy of the method.
- Which countries prominently contributed to CES-related research based on the data collection by authors?
- Who are the prominent first authors in the CES assessment field based on the collected articles from 2018 to 2021?
- Which publisher and journal(s) dominate and attract articles in the theme of the review?
- What are the popular decision approaches used by researchers to assess CESs rationally?
- What fuzzy sets are prominently used by researchers for CES assessment?
- What are commonly adopted metrics to evaluate the superiority of the proposed decision framework in the current field of study?
- What are the prevalent application areas addressed by researchers in the CES field and what are the future challenges, and how does the future research intuitively look for the current field of study?
2. Decision Approaches and Fuzzy Sets for CES
2.1. Decision-Making Methods
2.2. Fuzzy Sets
3. Review Model
4. Results and Discussion
4.1. Response to RQs
4.2. Challenges in CES Evaluation for Future Research
- Another notable inference is that the authors commonly adopt AHP, VIKOR, and TOPSIS under fuzzy contexts (from Table 2) to gain rational decisions on the CES field. Variants of AHP are also commonly adopted. Researchers recently adopted integrated schemes where fuzzy set ideas are integrated with machine learning methods, which gained a lot of attention in the CES field. The net contribution from the review process is observed to be close to 50%.
- Furthermore, it can be inferred that the triangular fuzzy number is a popular fuzzy variant adopted by researchers as preference information in the CES field. The orthopair variants constitute around 32%, indicating the popularity of numeric decision making in the CES domain.
- Contributions from China and India to the field of CES are around 44%, with a prime focus on integrated decision approaches under the fuzzy context (from Table 4). The selection of apt energy sources for the demand satisfaction and location identification of plant construction are interesting applications that are explored by the countries’ researchers.
- Elsevier has dominated publication in the CES field, with popular journals, such as the Journal of Cleaner Production, Energy, and Renewable and Sustainable Reviews, that attract readership in the CES field (from Table 5). These journals follow a rigorous review process to ensure quality research is given to their readers.
- Certain research has started with linguistic decision models for the CES field, which could be further enhanced by bringing sophisticated linguistic models for data acquisition from agents involved in the CES domain.
- Human intervention causes biases and inaccuracies in the decision process. Therefore, models must be developed with less human intervention and an acceptable level of complexity.
- Research relating to the integration of machine learning concepts with decision models has begun in the CES domain. Further exploration is required to develop approaches to solve large-scale decision problems better, which is lacking at the present stage.
- Finally, researchers must work on creating usable products that aid policymakers in making choices in critical situations.
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Abbreviation | Expansion |
---|---|
AHP | Analytical Hierarchy Process |
ANP | Analytic Network Process |
PSO | Particle Swarm Optimization |
MOO | Multi-Objective Optimization |
VIKOR | VIsekriterijumska Optimizacija I Kompromisno Resenje |
WSM | Weighted Sum Method |
TOPSIS | Technique for Order of Preference by Similarity to Ideal Solution |
MOPSO | Multi-Objective Particle Swarm Optimization |
MAUT | Multi-Attribute Utility Theory |
SVR | Support Vector Regression |
MLR | Multiple Linear Regression |
GA | Genetic Algorithm |
RF | Random Forest |
WASPAS | Weighted Aggregated Sum Product Assessment |
INRM | Influential Network Relationship Map |
MAGDM | Multi-Attribute Group Decision Making |
MCGDM | Multi-Criteria Group Decision Making |
MODA | Multi-Objective Decision Approaches |
MGU | Maximum Group Utility |
LSTM-CNN | Long Short Term Memory—Convolutional Neural Network |
ARAS | Additive Ratio Assessment |
SWARA | Stepwise Weight Assessment Ratio Analysis |
CRITIC | Criteria Index Correlation |
LBWA | Level Based Weight Assessment |
IDOCRIW | Integrated Determination of Objective Criteria Weights |
CODAS | Combinative Distance-based Assessment |
EDAS | Evaluation Based on Distance from Average Solution |
MOOSRA | Multi-Objective Optimization based on Simple Ratio Analysis |
MOGA | Multi-Objective Genetic Algorithm |
NSGA—II | Nondominated Sorting Genetic Algorithm II |
MPC | Model Predictive Control |
MULTIMOORA | Multiple Objective Optimization based on Ratio Analysis |
DEMATEL | Decision-Making Trail and Evaluation Laboratory |
PROMETHEE | Preference Ranking Organization Method for Enrichment of Evaluations |
MARCOS | Measurement Alternatives and Ranking according to Copromise Solution |
IDM | Investment Decision Making |
MEE | Matter Element Extension |
ECP | Expected Constraint Programming |
SAW | Simple Additive Weighting |
FA | Firefly Algorithm |
EVAMIX | Evaluation of Mixed |
DDSM | Data-Driven Screening Model |
ELECTRE | Elimination Et Choix Traduisant la Realité (ELimination Et Choice Translating Reality) |
ANN | Artificial Neural Network |
MPPT | Maximum Power Point Tracking |
SA | Simulated Annealing |
BWM | Best-Worst Method |
COPRAS | Complex Proportional Assessment |
IRS | Ideal Referential Solution |
GRA | Grey Relational Analysis |
SW | Sum Weighted |
FSM | Fuzzy Satisfaction Method |
HFL | Hesitant Fuzzy Linguistic |
IVF | Interval-Valued Fuzzy |
TRI-FUZZY NUMBER | Triangular Fuzzy Number |
TRAP-FUZZY NUMBER | Trapezoidal Fuzzy Number |
PYTH-FUZZY NUMBER | Pythagorean Fuzzy Number |
ANFIS | Adaptive Neural Fuzzy Inference System |
I2TLIFN | Interval 2 Tuple Linguistic Fuzzy Number |
SFAHNP | Stochastic Fuzzy Analytic Hierarchical Network Process |
FUZZY-MAPM | Fuzzy Multi-Attribute Preference Model |
FUZZY MOD | Fuzzy Multi-Objective Decision |
FEA | Fuzzy Expert Approach |
ICFHHA | Intuitionistic Cubic Fuzzy Hamacher Hybrid Averaging |
ICFHOWA | Intuitionistic Cubic Fuzzy Hamacher Weighted Averaging |
ICFS | Intuitionistic Cubic Fuzzy Set |
LINEAR PROG | Linear Programming |
TIFH | Trapezoidal Intuitionistic Fuzzy Number |
FUCOM | Full Consistency Method |
DEA | Data Envelopment Analysis |
IQ-ROFPWMM | Interval Q-Rung Orthopair Weighted Power Muirhead Mean |
A-SVN-DM | Aggregated Single-Valued Neutrosophic Decision Matrix |
FAHP | Fuzzy AHP |
CoCoSo | Combined Compromise Solution |
CM | Compromise Measure (CM) |
DEs | Decision experts |
EWP | Exponentially Weighted Product |
FS | Fuzzy Set |
GHG | Greenhouse Gas |
GUM | Group Utility Measure |
IFS | Intuitionistic Fuzzy Set |
IRM | Individual Regret Measure |
LVs | Linguistic Values |
MCDM | Multi-criteria Decision Making |
NS | Neutrosophic Set |
RES | Renewable Energy Source |
SVNS | Single-Valued Neutrosophic Set |
SVN | Single-Valued Neutrosophic |
SVN-SWARA-CoCoSo | Single-Valued Neutrosophic-SWARA-CoCoSo |
SVN-TOPSIS | Single-Valued Neutrosophic TOPSIS |
SVN-VIKOR | Single-Valued Neutrosophic VIKOR |
SVN-WASPAS | Single-Valued Neutrosophic WASPAS |
SAW | Simple Additive Weighting |
WEEE | Waste Electrical and Electronic Equipment |
WSM | Weighted Sum Model |
WPM | Weighted Product Model |
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Wu et al. [45] | 2018 | ✓ | ||||||||
Wang et al. [46] | 2018 | ✓ | ✓ | |||||||
Büyüközkan et al. [47] | 2018 | ✓ | 65 | |||||||
Promentilla et al. [48] | 2018 | ✓ | 66 | |||||||
Lee et al. [49] | 2018 | ✓ | ✓ | ✓ | 54 | |||||
Ghimire & Kim [50] | 2018 | ✓ | ||||||||
Chatterjee & Kar [51] | 2018 | ✓ | ||||||||
Chen & Ren [52] | 2018 | ✓ | ✓ | |||||||
Boran [53] | 2018 | ✓ | ||||||||
Simsek et al. [54] | 2018 | 10 | ||||||||
Sehatpour et al. [55] | 2018 | 17 | ||||||||
Li et al. [56] | 2018 | 30 | ||||||||
Alizadeh et al. [57] | 2018 | ✓ | ||||||||
Liu et al. [58] | 2019 | ✓ | 9 | |||||||
Cerón et al. [59] | 2019 | 20 | ||||||||
Tarybakhsh et al. [60] | 2019 | 11, 53, 67 | ||||||||
Mostafaeipour & Sadeghi-Sedeh [61] | 2019 | ✓ | ✓ | ✓ | 48, 55 | |||||
Deo et al. [62] | 2019 | 12, 14 17, 18 | ||||||||
Kumar et al. [63] | 2019 | |||||||||
Essien et al. [64] | 2019 | |||||||||
Rani et al. [65] | 2019 | ✓ | ✓ | 45 | ||||||
Karunathilake et al. [66] | 2019 | ✓ | ✓ | |||||||
Krishankumar et al. [67] | 2019 | 65 | ||||||||
Krishankumar et al. [68] | 2020 | ✓ | ||||||||
Rani et al. [69] | 2020 | ✓ | ||||||||
Yousef et al. [70] | 2020 | ✓ | 56 | |||||||
Asif et al. [71] | 2020 | 57 | ||||||||
Muneeza et al. [72] | 2020 | ✓ | ✓ | ✓ | 22 | |||||
Wu et al. [73] | 2020 | 23 | ||||||||
Okokpujie et al. [74] | 2020 | ✓ | ✓ | |||||||
Guðlaugsson et al. [75] | 2020 | |||||||||
Luo et al. [76] | 2020 | ✓ | ✓ | 61 | ||||||
Papanikolaou et al. [77] | 2020 | ✓ | ||||||||
Wang et al. [78] | 2020 | ✓ | ||||||||
Kamari et al. [79] | 2020 | ✓ | 40, 65 | |||||||
Alkan & Albayrak [80] | 2020 | |||||||||
Song et al. [81] | 2020 | |||||||||
Hu et al. [82] | 2020 | ✓ | ||||||||
Karaşan et al. [83] | 2020 | ✓ | ||||||||
Ikram et al. [84] | 2020 | ✓ | ✓ | ✓ | ||||||
Guleria & Bajaj [85] | 2020 | ✓ | ✓ | ✓ | ||||||
Ahmadi et al. [86] | 2020 | ✓ | ✓ | 25 | ||||||
Li et al. [87] | 2020 | 26 | ||||||||
Arriola et al. [88] | 2020 | ✓ | ✓ | 13, 17, 40, 59 | ||||||
Albawab et al. [89] | 2020 | 27, 28 | ||||||||
Wang et al. [90] | 2020 | ✓ | ✓ | 29 | ||||||
Deveci et al. [91] | 2020 | ✓ | 19, 31, 61 | |||||||
Aryanfar et al. [92] | 2020 | ✓ | 41 | |||||||
Rivera-Niquepa et al. [93] | 2020 | 32 | ||||||||
Ali et al. [94] | 2020 | 16, 33, 34, 35, 36 | ||||||||
Afzal & Ramis [95] | 2020 | ✓ | ✓ | 13, 37, 38, 39 | ||||||
Xu et al. [96] | 2020 | ✓ | ✓ | 41 | ||||||
Wu et al. [97] | 2020 | 41, 55 | ||||||||
Mangla et al. [98] | 2020 | ✓ | ✓ | 41 | ||||||
Mokarram et al. [99] | 2020 | ✓ | ✓ | |||||||
Moradi et al. [100] | 2020 | ✓ | ✓ | |||||||
Çolak & Kaya [101] | 2020 | ✓ | ✓ | ✓ | ✓ | |||||
Adedeji et al. [102] | 2020 | |||||||||
Geng et al. [103] | 2020 | |||||||||
Alao et al. [104] | 2020 | ✓ | ||||||||
Pamucar et al. [105] | 2020 | 43, 61 | ||||||||
Wu et al. [106] | 2020 | 23 | ||||||||
Wu et al. [107] | 2020 | ✓ | 42 | |||||||
Cheng et al. [108] | 2020 | ✓ | 41 | |||||||
Tarife et al. [109] | 2020 | |||||||||
Feng [110] | 2021 | ✓ | ||||||||
Mrówczyńska et al. [111] | 2021 | ✓ | ||||||||
Kumar et al. [112] | 2021 | ✓ | ✓ | |||||||
Krishankumar et al. [113] | 2021 | 21, 55, 62 | ||||||||
Liu et al. [114] | 2021 | ✓ | ✓ | 46 | ||||||
Ahmad et al. [115] | 2021 | ✓ | ✓ | 23 | ||||||
Hashmi et al. [116] | 2021 | ✓ | 17, 47 | |||||||
Fetanat et al. [117] | 2021 | ✓ | 60 | |||||||
Wu et al. [118] | 2021 | ✓ | 41 | |||||||
Adedeji et al. [119] | 2021 | ✓ | 13 | |||||||
Malik & Yadav [120] | 2021 | 63 | ||||||||
Gulzar et al. [121] | 2021 | 13, 49 | ||||||||
Kotb et al. [122] | 2021 | ✓ | ✓ | |||||||
Lin et al. [123] | 2021 | |||||||||
Wang et al. [124] | 2021 | 50 | ||||||||
Wang et al. [125] | 2021 | ✓ | 40 | |||||||
Mei & Chen [126] | 2021 | 41 | ||||||||
Yang & Chang [127] | 2021 | 51 | ||||||||
Clauberg et al. [128] | 2021 | |||||||||
Yazır et al. [129] | 2021 | |||||||||
Sun & Yu [130] | 2021 | ✓ | ✓ | 15, 52 | ||||||
Huai et al. [131] | 2021 | 64 | ||||||||
Mostafaeipour et al. [132] | 2021 | 35, 61 | ||||||||
Balezentis et al. [133] | 2021 | 16, 61 | ||||||||
Ghouchani et al. [134] | 2021 | 19 | ||||||||
Ullah et al. [135] | 2021 | ✓ | ✓ | 35, 40 | ||||||
Cayir Ervural et al. [136] | 2021 | ✓ | ✓ | |||||||
Wang et al. [137] | 2021 | ✓ | 68 | |||||||
Liu et al. [138] | 2021 | ✓ | 41 | |||||||
Gökgöz & Yalçın [139] | 2021 | 10, 29, 64 | ||||||||
Ulutaş & Karaca. [140] | 2021 | 29, 65 | ||||||||
Malemnganbi & Shimray [141] | 2021 | ✓ | ||||||||
Ecer [142] | 2021 | 27, 43, 65 | ||||||||
Ramos-Escudero [143] | 2021 | ✓ | ||||||||
Gkeka-Serpetsidaki & Tsoutsos [144] | 2021 | ✓ | ||||||||
Kannan et al. [145] | 2021 | ✓ | 61, 64, 69 | |||||||
Abdul-Basset et al. [146] | 2021 | ✓ | 35 | |||||||
Xie et al. [147] | 2021 | 41 | ||||||||
Saraswat & Digalwar [148] | 2021 | ✓ | ✓ | |||||||
Pan & Wang [149] | 2021 | 58 | ||||||||
Karaaslan et al. [150] | 2021 | ✓ | 43 | |||||||
Dang et al. [151] | 2021 | ✓ | ||||||||
Qazi et al. [152] | 2021 | ✓ | ||||||||
Karatop et al. [153] | 2021 | ✓ | 35 | |||||||
Günen [154] | 2021 | ✓ | ||||||||
Akçay & Atak [155] | 2018 | ✓ | ✓ | |||||||
Dominguez et al. [156] | 2021 | 77 | ||||||||
Lin & Ren [157] | 2021 | |||||||||
Shorabeh et al. [158] | 2021 | ✓ | ✓ | |||||||
Lopes et al. [159] | 2021 | ✓ | ||||||||
Rahoma & Obeidat [160] | 2021 | |||||||||
Ajanaku et al. [161] | 2021 | ✓ | ||||||||
Asanza et al. [162] | 2021 | ✓ | ||||||||
Ulewicz et al. [163] | 2021 | ✓ | ✓ | |||||||
Crivellari et al. [164] | 2021 | 69 | ||||||||
Babatunde et al. [165] | 2021 | 35 | ||||||||
Prieto-Amparán et al. [166] | 2021 | ✓ | ||||||||
Tercan et al. [167] | 2021 | ✓ | ||||||||
Hwang et al. [168] | 2021 | |||||||||
Naegler et al. [169] | 2021 | ✓ | ||||||||
Sipa [170] | 2021 | 40 | ||||||||
Lucheroni et al. [171] | 2021 | 71 | ||||||||
Castangia et al. [172] | 2021 | 26 | ||||||||
Bertolino et al. [173] | 2021 | 72 | ||||||||
Derbeli et al. [174] | 2021 | 56 | ||||||||
Mohd et al. [175] | 2021 | 73 | ||||||||
Alam et al. [176] | 2021 | 74 | ||||||||
Alberizzi et al. [177] | 2021 | 20 | ||||||||
Martin-Hernandez et al. [178] | 2021 | 75 | ||||||||
Oregi et al. [179] | 2021 | 76 | ||||||||
1. AHP | 26. LSTM-CNN | 51. EVAMIX | ||||||||
2. ANP | 27. ARAS | 52. K-MEAN METHOD | ||||||||
3. PSO | 28. SWARA | 53. DDSM | ||||||||
4. MOO | 29. CRITIC | 54. ELECTRE | ||||||||
5. VIKOR | 30. AUGMENTED Є CONSTRAINT | 55. TODIM | ||||||||
6. WSM | 31. LBWA | 56. ANN | ||||||||
7. TOPSIS | 32. PARETO SET | 57. MPPT | ||||||||
8. ENTROPY METHOD | 33. IDOCRIW | 58. LSGDM | ||||||||
9. MOPSO | 34. CODAS | 59. SA | ||||||||
10. MAUT | 35. EDAS | 60. LINEAR ASSIGNMENT | ||||||||
11. SVR | 36. MOOSRA | 61. BWM | ||||||||
12. MLR | 37. MOGA | 62. GINI INDEX | ||||||||
13. GA | 38. NSGA—II | 63. FORECASTING | ||||||||
14. RF | 39. MPC | 64. GRA | ||||||||
15. NORMALIZATION METHOD | 40. MULTIMOORA | 65. COPRAS | ||||||||
16. WASPAS | 41. DEMATEL | 66. SFAHNP | ||||||||
17. GP | 42. PROMETHEE | 67. FINITE ELEMENT ANALYSIS | ||||||||
18. M5TREEMODEL | 43. MARCOS | 68. DEA | ||||||||
19. DELPHI METHOD | 44. IDM | 69. MONTE CARLO | ||||||||
20. MILM | 45. DIVERGE MEASURE | 70. LCP | ||||||||
21. MAGDM | 46. MEE | 71. Value at risk | ||||||||
22. MCGDM | 47. ECP | 72. Cumulative impact function; Evolutionary algorithm | ||||||||
23. PROMETHEE—II | 48. SAW | 73. BeWhere model 74. Technology acceptance model with theory of reason action | ||||||||
24. MINLP | 49. FA | 75. First principle/Superstructure model | ||||||||
25. GIS | 50. REGRET THEORY | 76. Life cycle assessment 77. Statistical analysis |
Method | Studies | Total | Percentage (%) |
---|---|---|---|
AHP | [45,46,47,48,50,61,66,74,75,76,80,81,87,88,89,95,98,107,108,109,110,111,118,121,141,144,147,148,150,153,154,155,161,162,163,166,167] | 38 | 30.4% |
TOPSIS | [46,49,52,58,61,68,69,72,74,76,77,82,85,88,90,96,104,108,112,115,130,135,136,137,152,155,158,159,163] | 31 | 24.8% |
VIKOR | [49,53,61,66,68,69,73,83,98,111,112,119,140,142,148] | 16 | 12.8% |
ANP | [51,52,57,72,76,86,95,96,97,98,107,132,155] | 14 | 11.2% |
Author | Year | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
---|---|---|---|---|---|---|---|---|---|
Büyüközkan et al. [47] | 2018 | ✓ | |||||||
Ghimire & Kim [50] | 2018 | ✓ | |||||||
Sehatpour et al. [55] | 2018 | ✓ | |||||||
Tarybakhsh et al. [60] | 2019 | ✓ | |||||||
Deo et al. [62] | 2019 | ✓ | |||||||
Kumar et al. [63] | 2019 | ✓ | |||||||
Essien et al. [64] | 2019 | ✓ | |||||||
Rani et al. [65] | 2019 | ✓ | |||||||
Karunathilake et al. [66] | 2019 | ✓ | |||||||
Krishankumar et al. [67] | 2019 | ✓ | ✓ | ||||||
Krishankumar et al. [68] | 2020 | ✓ | |||||||
Rani et al. [69] | 2020 | ✓ | |||||||
Yousef et al. [70] | 2020 | ✓ | |||||||
Asif et al. [71] | 2020 | ✓ | |||||||
Wu et al. [73] | 2020 | ✓ | |||||||
Guðlaugsson et al. [75] | 2020 | ✓ | |||||||
Luo et al. [76] | 2020 | ✓ | |||||||
Kamari et al. [79] | 2020 | ✓ | |||||||
Alkan et al. [80] | 2020 | ✓ | |||||||
Hu et al. [82] | 2020 | ✓ | ✓ | ||||||
Karaşan et al. [83] | 2020 | ✓ | ✓ | ||||||
Guleria & Bajaj [85] | 2020 | ✓ | |||||||
Arriola et al. [88] | 2020 | ✓ | |||||||
Deveci et al. [91] | 2020 | ✓ | ✓ | ||||||
Aryanfar et al. [92] | 2020 | ✓ | |||||||
Xu et al. [96] | 2020 | ✓ | |||||||
Wu et al. [97] | 2020 | ✓ | |||||||
Çolak & Kaya [101] | 2020 | ✓ | ✓ | ||||||
Adedeji et al. [102] | 2020 | ✓ | |||||||
Geng et al. [103] | 2020 | ✓ | ✓ | ||||||
Pamucar et al. [105] | 2020 | ✓ | |||||||
Wu et al. [106] | 2020 | ✓ | |||||||
Cheng et al. [108] | 2020 | ✓ | ✓ | ||||||
Feng [110] | 2021 | ✓ | |||||||
Mrówczyńska et al. [111] | 2021 | ✓ | |||||||
Krishankumar et al. [113] | 2021 | ✓ | |||||||
Wu et al. [118] | 2021 | ✓ | |||||||
Adedeji et al. [119] | 2021 | ✓ | |||||||
Wang et al. [124] | 2021 | ✓ | |||||||
Wang et al. [125] | 2021 | ✓ | |||||||
Yang & Chang [127] | 2021 | ✓ | |||||||
Clauberg et al. [128] | 2021 | ✓ | |||||||
Yazır & Şahin [129] | 2021 | ✓ | |||||||
Sun & Yu [130] | 2021 | ✓ | |||||||
Mostafaeipour et al. [132] | 2021 | ✓ | |||||||
Wang et al. [137] | 2021 | ✓ | |||||||
Liu et al. [138] | 2021 | ✓ | |||||||
Abdul-Basset et al. [146] | 2021 | ✓ | |||||||
Xie et al. [147] | 2021 | ✓ | |||||||
Pan & Wang [149] | 2021 | ✓ | |||||||
Dang et al. [151] | 2021 | ✓ | |||||||
Karatop et al. [153] | 2021 | ✓ | |||||||
1. hesitant fuzzy set variants | |||||||||
2. intuitionistic fuzzy set variants | |||||||||
3. classical fuzzy set variants | |||||||||
4. linguistic term set variants | |||||||||
5. q-rung orthopair fuzzy set | |||||||||
6. neutrosophic fuzzy set variants | |||||||||
7. Pythagorean fuzzy set variants | |||||||||
8. interval fuzzy set variants |
Country | Papers | Percentage |
---|---|---|
China | 30 | 22.4% |
Turkey | 15 | 11.2% |
India | 14 | 10.5% |
Iran | 10 | 7.5% |
Pakistan | 4 | 3% |
Taiwan | 4 | 3% |
Brazil | 3 | 2.2% |
Nigeria | 3 | 2.2% |
Poland | 3 | 2.2% |
Australia | 2 | 1.5% |
Canada | 2 | 1.5% |
Colombia | 2 | 1.5% |
Egypt | 1 | 0.7% |
Germany | 1 | 0.7% |
Singapore | 2 | 1.5% |
South Africa | 2 | 1.5% |
United Arab Emirates | 2 | 1.5% |
United Kingdom | 2 | 1.5% |
USA | 3 | 2.2% |
Vietnam | 2 | 1.5% |
Japan | 2 | 1.5% |
Chile | 1 | |
Denmark | 1 | |
France | 1 | |
Greece | 1 | |
Hungary | 1 | |
Iceland | 1 | |
Italy | 5 | |
Jordan | 1 | |
Lithuanian | 1 | |
Malaysia | 3 | |
Mexico | 1 | |
Philippines | 1 | |
Serbia | 1 | |
Spain | 4 | |
Sri Lanka | 1 | |
Uzbekistan | 1 | |
South Korea | 1 | |
Total | 134 | 100% |
Author Names | Country (Affiliation) | Research Papers |
---|---|---|
Yunna Wu. | China | 4 |
Raghunathan Krishankumar | India | 3 |
Pratibha Rani | India | 2 |
Mahya Ghouchani | Iran | 2 |
Paul A. Adedeji | South Africa | 2 |
Publisher | Journal Name | Count of Paper | Percentage |
---|---|---|---|
Academic Press Inc. | Environmental Research | 1 | |
Journal of Environmental Management | 1 | ||
Design Engineering | Others | 1 | |
Elsevier | Applied Soft Computing | 1 | |
Combustion and Flame Computer and Chemical Engineering | 1 1 | ||
Computers & Industrial Engineering | 1 | ||
Energy | 5 | 3.7% | |
Energy Conversion and Management | 1 | 0.75% | |
Energy for Sustainable Development | 1 | 0.75% | |
Energy Policy | 2 | 1.5% | |
Energy Reports | 3 | 2.2% | |
Energy Strategy Reviews | 1 | 0.75% | |
Experts Systems with Applications Heliyon | 1 2 | 0.75% 1.5% | |
International Journal of Hydrogen Energy | 3 | 2.2% | |
International Journal of Production Economics | 1 | 0.75% | |
Journal of Air Transport Management | 1 | 0.75% | |
Journal of Cleaner Production | 17 | 12.7% | |
Journal of Energy Storage | 7 | 5.2% | |
Land Use Policy | 1 | ||
Ocean and Coastal Management | 1 | ||
Ocean Engineering | 1 | ||
Procedia Manufacturing | 1 | ||
Renewable and sustainable energy Reviews | 9 | 6.7% | |
Renewable Energy | 7 | 5.2% | |
Sustainable Cities and Society | 3 | 2.2% | |
Sustainable Energy Technologies and Assessments | 5 | 3.7% | |
Sustainable Operations and Computers | 1 | ||
Technological Forecasting & Social Change | 1 | ||
Technological Forecasting and Social Change | 1 | ||
Thermal Science and Engineering Progress | 1 | ||
IEEE | Environmental Science and Pollution Research | 1 | |
TRANSACTIONS ON ENGINEERING MANAGEMENT | 1 | ||
Others | 1 | ||
ICRERA | 1 | ||
John Wiley and Sons Ltd. | Business Strategy and the Environment | 1 | |
Canadian Journal of Chemical Engineering | 1 | ||
Energy Science and Engineering | 4 | 3% | |
Engineering Reports | 1 | 0.75% | |
International Journal of Energy Research | 6 | 4.5% | |
International Journal of Intelligent System | 1 | ||
International Transactions on Electrical Energy Systems | 1 | ||
Sustainable Development | 1 | ||
KeAi Publishing Communications Ltd. | Global Energy Interconnection | 1 | |
Korean Association of Shipping and Logistics, Inc. | Asian Journal of Shipping and Logistics | 1 | |
MDPI | Applied Sciences (Switzerland) | 1 | |
Energies | 3 | 2.2% | |
Land | 1 | 1.5% | |
Mathematics Sustainability | 1 5 | 3.7% | |
Springer | Archives of Computational Methods in Engineering | 1 | |
Energy Systems Evaluation | 1 | ||
Environmental Science and Pollution Research | 1 | ||
GeoJournal | 1 | ||
Renewable Energy | 1 | ||
Others | 1 | ||
Celal Bayar University Journal of Science | 1 | ||
Advances in Intelligent Systems and Computing Annals of Operations Research | 2(1 + 1) | ||
Taylor & Francis | ENERGY SOURCES | 1 | |
International Journal of Sustainable Energy | 1 | ||
Wiley-Blackwell Publishing Ltd | Food and Energy Security | 1 | |
Others | Low Carbon Energy Technologies in Sustainable Energy Systems | 1 | |
Renewable Energy Research and Application | 1 | ||
Technological and Economic Development of Economy | 1 | ||
Others | 1 | ||
Grand Total | 134 | 100% |
Analysis Type | Studies | Total | Percentage |
---|---|---|---|
Sensitivity analysis | [52,76,82,89,94,98,100,101,103,106,122,124,131,133,149,155,160,165,166] | 14 | 17.234% |
Comparative analysis | [47,49,58,72,76,99,101,103,105,106,113] | 12 | 14.815% |
Total | 26 | 32.098% |
Applications | Studies | Total | Percentage |
---|---|---|---|
Energy Facility Location | [45,46,72,73,76,85,86,91,100,102,103,107,110,119,127,128,129,137,139,140,147,148,151,152,159,163,169] | 27 | 21% |
Energy Source Selection | [47,49,59,66,113,126,133,149,156,160] | 10 | 8% |
Energy System Selection | [48,56,58,65,71,79,81,82,83,89,94,95,97,101,106,122,130,162] | 18 | 14% |
Decision Analysis | [75,97,99,111,117,135,153,155,157,165,167,169] | 12 | 9% |
Strategy Selection | [60,64,118,123,133] | 7 | 6% |
Sustainability Evaluation | [52,54,77,88,89,92,96,110,115,124,125,126,128,131,132,136,141,142,143,145,154,159,161,166] | 24 | 19% |
Forecasting | [62,87,102,119,120] | 5 | 4% |
Process Optimization | [63,70,93,121] | 4 | 3% |
Ranking | [80,89,105,130,138] | 5 | 4% |
Miscellaneous | [61,74,84,90,112,114,144,146,150,168,170,171,172,173,174] | 15 | 12% |
Renewable Energy | Studies | Total | Percentage |
---|---|---|---|
Wind Energy | [45,46,58,74,86,91,100,107,110,119,120,131,141,144,146] | 15 | 12% |
Solar Energy | [54,61,71,92,99,103,106,138,141,164] | 10 | 8% |
Hydrogen Energy | [85,97,105,106,126] | 5 | 4% |
Nuclear | [73,118,121] | 3 | 2% |
Hydro Energy | [72,128] | 2 | 2% |
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Pandey, A.K.; Krishankumar, R.; Pamucar, D.; Cavallaro, F.; Mardani, A.; Kar, S.; Ravichandran, K.S. A Bibliometric Review on Decision Approaches for Clean Energy Systems under Uncertainty. Energies 2021, 14, 6824. https://doi.org/10.3390/en14206824
Pandey AK, Krishankumar R, Pamucar D, Cavallaro F, Mardani A, Kar S, Ravichandran KS. A Bibliometric Review on Decision Approaches for Clean Energy Systems under Uncertainty. Energies. 2021; 14(20):6824. https://doi.org/10.3390/en14206824
Chicago/Turabian StylePandey, Alok K., R. Krishankumar, Dragan Pamucar, Fausto Cavallaro, Abbas Mardani, Samarjit Kar, and K. S. Ravichandran. 2021. "A Bibliometric Review on Decision Approaches for Clean Energy Systems under Uncertainty" Energies 14, no. 20: 6824. https://doi.org/10.3390/en14206824