Ahmad et al. (2021)Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021). Artificial intelligence in sustainable energy industry: status quo, challenges and opportunities. Journal of Cleaner Production, 289, 125834. http://dx.doi.org/10.1016/j.jclepro.2021.125834. http://dx.doi.org/10.1016/j.jclepro.2021...
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A baseline that allows researchers and readers to compare their AI efforts, new state-of-the-art applications and global roles in policymaking of energy industry |
AI techniques |
The energy industry, utilities, power system operators, and independent power producers may need to focus more on AI technologies if they want meaningful results to remain competitive. |
Ahmadi et al. (2022)Ahmadi, M., Soofiabadi, M., Nikpour, M., Naderi, H., Abdullah, L., & Arandian, B. (2022). Developing a deep neural network with fuzzy wavelets and integrating an inline PSO to predict energy consumption patterns in urban buildings. Mathematics, 10(8), 1270. http://dx.doi.org/10.3390/math10081270. http://dx.doi.org/10.3390/math10081270...
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Predicting energy consumption patterns in urban buildings |
Deep neural network with fuzzy wavelets |
This study shows that the presented method provides high-performance prediction at a lower level of complexity. |
Al-Barakati et al. (2022)Al-Barakati, A., Mishra, A. R., Mardani, A., & Rani, P. (2022). An extended interval-valued Pythagorean fuzzy WASPAS method based on new similarity measures to evaluate the renewable energy sources. Applied Soft Computing, 120, 108689. http://dx.doi.org/10.1016/j.asoc.2022.108689. http://dx.doi.org/10.1016/j.asoc.2022.10...
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Evaluating the renewable energy sources |
Extended interval-valued Pythagorean fuzzy WASPAS |
The evaluation results showed that the wind energy with a maximum assessment score degree using the proposed method was found the best option for selecting renewable energy sources over diverse criteria. |
Buțurache & Stancu (2022)Buțurache, A.-N., & Stancu, S. (2022). Building energy consumption prediction using neural-based models. International Journal of Energy Economics and Policy, 12(2), 30-38. http://dx.doi.org/10.32479/ijeep.12739. http://dx.doi.org/10.32479/ijeep.12739...
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Building energy consumption prediction |
Neural-based models |
Neural-based models possess the capability of learning and generalizing from different datasets having different patterns. |
Caiado et al. (2017)Caiado, R. G. G., Lima, G. B. A., Gavião, L. O., Quelhas, O. L. G., & Paschoalino, F. F. (2017). Sustainability analysis in electrical energy companies by similarity technique to ideal solution. IEEE Latin America Transactions, 15(4), 675-681. http://dx.doi.org/10.1109/TLA.2017.7896394. http://dx.doi.org/10.1109/TLA.2017.78963...
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Proposing a novel model for solving decision-making problems in the evaluation of electrical energy companies |
TOPSIS method |
Robust evaluation and ranking of the energy companies with respect to the observed aspects of sustainability. |
Chamandoust et al. (2020)Chamandoust, H., Derakhshan, G., & Bahramara, S. (2020). Multi-objective performance of smart hybrid energy system with multi-optimal participation of customers in day-ahead energy market. Energy and Building, 216, 109964. http://dx.doi.org/10.1016/j.enbuild.2020.109964. http://dx.doi.org/10.1016/j.enbuild.2020...
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Performance assessment of smart hybrid energy system (SHES) |
Shuffled frog leaping algorithm (SFLA) |
Optimal scheduling of SHES with acceptable levels of operation costs, emission pollution and customer satisfaction. |
Colla et al. (2020)Colla, M., Ioannou, A., & Falcone, G. (2020). Critical review of competitiveness indicators for energy projects. Renewable & Sustainable Energy Reviews, 125, 109794. http://dx.doi.org/10.1016/j.rser.2020.109794. http://dx.doi.org/10.1016/j.rser.2020.10...
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Critically review of multi-disciplinary KPIs, allowing a holistic comparison across different types of energy projects |
A structured evaluation framework based on the identified set of indicators |
Integrated framework and a fairer assessment of competing energy projects by relevant stakeholders. |
Daugavietis et al. (2022)Daugavietis, J. E., Soloha, R., Dace, E., & Ziemele, J. (2022). A comparison of multi-criteria decision analysis methods for sustainability assessment of district heating systems. Energies, 15(7), 2411. http://dx.doi.org/10.3390/en15072411. http://dx.doi.org/10.3390/en15072411...
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A Comparison of Multi-Criteria Decision Analysis Methods for sustainability assessment of District Heating systems |
WSM, TOPSIS, PROMETHEE, ELECTRE and DEA methods |
The results of sensitivity analysis along with literature investigation shows that all methods are suitable for sustainability analyses of District Heating systems while also having differences in the calculation process and in the interpretation of results. |
Ervural et al. (2018a)Ervural, B. C., Evren, R., & Delen, D. (2018a). A multi-objective decision-making approach for sustainable energy investment planning. Renewable Energy, 126, 387-402. http://dx.doi.org/10.1016/j.renene.2018.03.051. http://dx.doi.org/10.1016/j.renene.2018....
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Energy investment planning |
TOPSIS and AHP |
The renewable energy investment plan of a power company in Turkey is evaluated with a newly developed integral approach. |
Ervural et al. (2018b)Ervural, B. C., Zaim, S., Demireld, O. F., Aydin, Z., & Delen, D. (2018b). An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning. Renewable & Sustainable Energy Reviews, 82, 1538-1550. http://dx.doi.org/10.1016/j.rser.2017.06.095. http://dx.doi.org/10.1016/j.rser.2017.06...
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Energy planning |
ANP, fuzzy TOPSIS and SWOT analysis |
Integrated framework for the Turkey’s energy sector to prioritize alternative energy strategies. |
Kwakkel & Pruyt (2013)Kwakkel, J. H., & Pruyt, E. (2013). Exploratory modeling and analysis, an approach for model-based foresight under deep uncertainty. Technological Forecasting and Social Change, 80(3), 419-431. http://dx.doi.org/10.1016/j.techfore.2012.10.005. http://dx.doi.org/10.1016/j.techfore.201...
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An approach for model-based foresight under deep uncertainty |
Exploratory Modeling and Analysis |
Multiplicity assessment of deep uncertainties in the analysis of decision-making problems in the electricity sector. |
Panchal et al. (2022)Panchal, D., Chatterjee, P., Pamucar, D., & Yazdani, M. (2022). A novel fuzzy‐based structured framework for sustainable operation and environmental friendly production in coal‐fired power industry. International Journal of Intelligent Systems, 37(4), 2706-2738. http://dx.doi.org/10.1002/int.22507. http://dx.doi.org/10.1002/int.22507...
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A novel structured framework for analyzing sustainable operational performance‐related issues of ash handling unit (AHU) under vague/uncertain information |
Integrated fuzzy lambda-tau and fuzzy multicriteria decision‐making methods |
The current work discussed a framework for evaluating performance issues of the thermal power industry for sustainable and environmental friendly operation for emission control. |
Qi et al. (2020)Qi, W., Huang, Z., Dinçer, H., Korsakiene, R., & Yuksel, S. (2020). Corporate governance-based strategic approach to sustainability in energy industry of emerging economies with a novel interval-valued intuitionistic fuzzy hybrid decision making model. Sustainability, 12(8), 3307. http://dx.doi.org/10.3390/su12083307. http://dx.doi.org/10.3390/su12083307...
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Defining a set of criteria and dimensions for analyzing the corporate governance-based strategic |
IVIF DEMATEL; IVIF VIKOR |
Extending investigations on corporate governance and sustainable production in energy industry. |
Rigo et al. (2020)Rigo, P. D., Rediske, G., Rosa, C. B., Gastaldo, N. G., Michels, L., Neuenfeldt, A. L. Jr., & Siluk, J. C. M. (2020). Renewable energy problems: exploring the methods. Sustainability, 12(23), 10195.
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Systematic literature review of renewable energy problems associated with MCDM methods |
MCDM methods |
Improving their ability to choose the proper MCDM methods to solve energy problems. |
Rolnick et al. (2022)Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., Luccioni, A. S., Maharaj, T., Sherwin, E. D., Mukkavilli, S. K., Kording, K. P., Gomes, C. P., Ng, A. Y., Hassabis, D., Platt, J. C., Creutzig, F., Chayes, J., & Bengio, Y. (2022). Tackling climate change with machine learning. ACM Computing Surveys, 55(2), 42. http://dx.doi.org/10.1145/3485128. http://dx.doi.org/10.1145/3485128...
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How machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate |
Machine Learning techniques |
Climate change solution domains with selected areas of ML that are relevant. |
Sahabuddin & Khan (2021)Sahabuddin, M., & Khan, I. (2021). Multi-criteria decision analysis methods for energy sector’s sustainability assessment: robustness analysis through criteria weight change. Sustainable Energy Technologies and Assessments, 47, 101380. http://dx.doi.org/10.1016/j.seta.2021.101380. http://dx.doi.org/10.1016/j.seta.2021.10...
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Energy sector’s sustainability assessment |
Multi-criteria decision analysis methods |
The analysis revealed that COPRAS is the most robust MCDA method, followed by WPM. |
Tajbakhsh & Shamsi (2019)Tajbakhsh, A., & Shamsi, A. (2019). A facility location problem for sustainability-conscious power generation decision makers. Journal of Environmental Management, 230, 319-334. http://dx.doi.org/10.1016/j.jenvman.2018.09.066. PMid:30293017. http://dx.doi.org/10.1016/j.jenvman.2018...
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Analyzing a comprehensive objective function in the facility location context in the presence of variable costs, fixed costs, and sustainability consideration |
Double bootstrap data envelopment analysis |
The proposed approach substantially diminishes greenhouse gas emissions at the cost of slight increases in total expense. |
Vargas-Solar et al. (2022)Vargas-Solar, G., Khalil, M., Espinosa-Oviedo, J. A., & Zechinelli-Martini, J.-L. (2022). GREENHOME: a household energy consumption and CO2 footprint metering environment. ACM Transactions on Internet Technology, 22(3), 72. http://dx.doi.org/10.1145/3505264. http://dx.doi.org/10.1145/3505264...
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Providing data analytical tools for metering household energy consumption and CO2 footprint under different perspectives |
GREENHOME environment toolkit |
The article reports on experiments conducted for modelling and forecasting energy consumption and CO2 footprint in the context of the Triple-A European project. |
Wang et al. (2021)Wang, Y., Li, S., Wu, X., Zhang, Y., Li, B., & Gao, L. (2021). Using sustainable performance prediction in data-scarce scenarios: a study of park-level integrated microgrid projects in Tianjin, China. Journal of Cleaner Production, 304, 127042. http://dx.doi.org/10.1016/j.jclepro.2021.127042. http://dx.doi.org/10.1016/j.jclepro.2021...
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Using sustainable performance prediction in data-scarce scenarios |
Integrated energy efficiency system |
Strengthening the real-time control of integrated energy projects and for effectively promoting the sustainable development of the integrated energy industry. |
Wanke et al. (2020)Wanke, P., Tan, Y., Antunes, J., & Hadi-Vencheh, A. (2020). Business environment drivers and technical efficiency in the Chinese energy industry: a robust Bayesian stochastic frontier analysis. Computers & Industrial Engineering, 144, 106487. http://dx.doi.org/10.1016/j.cie.2020.106487. http://dx.doi.org/10.1016/j.cie.2020.106...
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Improving the technical efficiency of the energy industry in China |
Bayesian stochastic frontier analysis |
Increases in the efficiency of the Chinese energy industry can be achieved by increasing the level of inventories and fixed assets. |
Zhou et al. (2019)Zhou, P., Zhou, P., Yüksel, S., Dinçer, H., & Uluer, G. S. (2019). Balanced scorecard-based evaluation of sustainable energy investment projects with IT2 fuzzy hybrid decision making approach. Energies, 13(1), 82. http://dx.doi.org/10.3390/en13010082. http://dx.doi.org/10.3390/en13010082...
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Evaluation of sustainable energy investment projects |
Balanced Scorecard, IT2 Fuzzy DEMATEL, IT2 Fuzzy QUALIFLEX |
Which issues are effective in financial institutions' lending process of large-scale energy projects. |