REVIEW PAPER
A comprehensive review on applications of multicriteria decision-making methods in power and energy systems
Shabbir S. Bohra,
Amjad Anvari-Moghaddam,
Corresponding Author
Shabbir S. Bohra
Department of Electrical Engineering, Sarvajanik College of Engineering & Technology, Surat, India
Correspondence
Shabbir S. Bohra, Department of Electrical Engineering, Sarvajanik College of Engineering & Technology, Surat-395001, India.
Email: [email protected]
Search for more papers by this authorAmjad Anvari-Moghaddam
Department of Energy Technology, Aalborg University, Aalborg, Denmark
Search for more papers by this authorShabbir S. Bohra,
Amjad Anvari-Moghaddam,
Corresponding Author
Shabbir S. Bohra
Department of Electrical Engineering, Sarvajanik College of Engineering & Technology, Surat, India
Correspondence
Shabbir S. Bohra, Department of Electrical Engineering, Sarvajanik College of Engineering & Technology, Surat-395001, India.
Email: [email protected]
Search for more papers by this authorAmjad Anvari-Moghaddam
Department of Energy Technology, Aalborg University, Aalborg, Denmark
Search for more papers by this authorSummary
Energy has been considered as one of the essential needs of mankind along with air, water, and food and witnessed evolution of civilization since evidence of human life. Managing energy resources is one of the challenging problems being capital intensive. Addressing this involves critical thinking and decision making with all possible aspects, technically known as set of primary and secondary criteria. There exist a number of literature sources addressing applications of multicriteria decision-making (MCDM) in different energy-related areas. Some are focusing on energy policy making, few are explaining site selection of solar PV, wind farm, and hydro power plants, and a few are describing applications in load management. Moreover, a few literature in this field elaborates various MCDM methods and their applications. In this article, an extensive and exhaustive study is carried out incorporating almost all possible applications of MCDM in renewable energy area. Various energy-intensive applications are mapped with MCDM methods along with governing sensitive parameters. Hence, this study facilitates practicing engineers, decision-makers, academician, and researchers to identify areas and MCDM techniques researched over the past decade in energy sector for planning, managing, selecting renewable resources, etc.
REFERENCES
- 1Ritchie H, Roser M. [Online]. February 2020. https://ourworldindata.org/energy.
- 2 United Nations. Department of Economic and Social Affairs: Sustainable Development. 2021. [Online]. https://sdgs.un.org/goals/goal7. Accessed September 2021.
- 3 2019 Tracking SDG 7 The Energy Progress Report. Washington, DC; 2019.
- 4April 2020. [Online]. https://www.c2es.org/content/renewable-energy/.
- 52020. [Online]. trackingsdg7.esmap.org.
- 62020. [Online]. ww.iea.org.
- 7Green thinking: pioneers in clean energy. 2020. [Online]. https://denmark.dk/innovation-and-design/clean-energy. Accessed April 2020.
- 8Gronholt-Pedersen J. Discover Thomson Reuters. Reuteres. January 2020. [Online]. https://www.reuters.com/article/us-climate-change-denmark-windpower-idUSKBN1Z10KE. Accessed June 2020.
- 9Green Transition. ENERGINET [Online]. https://en.energinet.dk/Green-Transition/Renewable-energy-in-the-energy-system. Accessed May 2020.
- 10January 2020. [Online]. https://gulfgasandpower.uk/blog/top-renewable-energy-generating-countries-in-the-world.
- 11Zeleny M. Multiple criteria decision making: eight concepts of optimality. In: J Clímaco, ed. Multicriteria Analysis. Berlin, Heidelberg: Springer; 1997.
10.1007/978-3-642-60667-0_19 Google Scholar
- 12Zavadskas EK, Kaklauskas A, Sarka V. The new method of multicriteria complex proportional assessment of projects. Technol Econ Dev Econ. 1994; 1(3): 131-139.
- 13Velasquez M, Hester PT. An analysis of multi-criteria decision making methods. Int J Oper Res. 2013; 10(2): 56-66.
- 14Yazdani-Chamzini A, Fouladgar MM, Zavadskas EK, Moini SHH. Selecting the optimal renewable energy using multi criteria decision making. J Bus Econ Manage. 2014; 14: 957-978.
- 15Wang J-J, Jing Y-Y, Zhang C-F, Zhao J-H. Review on multi-criteria decision analysis aid in sustainable energy decision making. Renew Sustain Energy Rev. 2009; 13(9): 2263-2278.
- 16Koksalan M, Wallenius J, Zionts S. Multiple Criteria Decision Making: from Early History to the 21st Century. Singapore: World Scientific Publishing Co. Pte. Ltd.; 2011.
10.1142/8042 Google Scholar
- 17Ozernoy VM. Choosing the “best” multiple criterlv decision-making method. INFOR: Inf Syst Oper Res. 1992; 30(2): 159-171.
- 18 A Anvari-Moghaddam, B Mohammadi-ivatloo, S Asadi, K Larsen, M Shaidehpour, eds. Sustainable Energy Systems Planning, Integration, and Management. Basel, Switzerland: MDPI; 2020.
- 19Köksalan M, Wallenius J, Zionts S. An early history of multiple criteria decision making. J Multi-Crit Decis Anal. 2013; 20: 87-94.
10.1002/mcda.1481 Google Scholar
- 20Dyer JS, Fishburn PC, Steuer RE, Wallenius J, Zionts S. Multiple criteria decision making, multiattribute utility theory: the next ten years. Manage Sci. 1992; 38(5): 645-654.
- 21Tzeng G-H, Huang J-J. Multiple Attribute Decision Making: Methods and Applications. Berlin, Heidelberg: CRC Press, Taylor and Francis Group; 2011.
10.1201/b11032 Google Scholar
- 22Alinezhad A, Khalili J. In: CC Price, ed. New Methods and Applications in Multiple Attribute Decision Making (MADM). International Series in Operations Reserch & Management Science. Switzerland: Springer; 2019.
10.1007/978-3-030-15009-9 Google Scholar
- 23Taylan O, Alamoudi R, Kabli M, AlJifri A, Ramzi F, Herrera-Viedma E. Assessment of energy systems using extended fuzzy AHP, fuzzy VIKOR, and TOPSIS approaches to manage non-cooperative opinions. Sustainability. 2020; 12:2745.
- 24Shao M, Han Z, Sun J, Xiao C, Zhang S, Zhao Y. A review of multi-criteria decision making applications for renewable energy site selection. Renew Energy. 2020; 157: 377-403.
- 25Kamari ML, Isvand H, Nazari MA. Applications of multi-criteria decision-making (MCDM) methods in renewable energy development: a review. Renew Energy Res Appl. 2020; 1(1): 47-54.
- 26Hwang CL, Yoon K. Multiple Attribute Decision Making: Methods and Applications, Lecture Notes in Economics and Mathematical Systems. New York: Springer-Verlag; 1981: 186.
- 27Ilbahara E, Cebia S, Kahraman C. A state-of-the-art review on multi-attribute renewable energy decision making. Energy Strat Rev. 2019; 25: 18-33.
- 28Vassoney E, Mammolit IMA, Desiderio E, Negro G, Pilloni M, Comoglio C. Comparing multi-criteria decision-making methods for the assessment of flow release scenarios from small hydropower plants in the alpine area. Front Environ Sci. 2021; 9: 1-20.
- 29Chen S-J, Hwang C-L. Fuzzy Multiple Attribute Decision Making:Methods and Applications Series: Lecture Notes in Economics and Mathematical Systems. Vol 375. Berlin, Heidelberg: Springer-Verlag; 1992.
- 30Kaya İ, Kahraman C. Evaluation of green and renewable energy system alternatives using a multiple attribute utility model: the case of Turkey. Soft Computing in Green and Renewable Energy Systems. Studies in Fuzziness and Soft Computing. Vol 269; Berlin, Heidelberg: Springer; 2011: 157-182.
10.1007/978-3-642-22176-7_6 Google Scholar
- 31Bhushan N, Rai K. Strategic Decision Making: Applying the Analytic Hierarchy Process. Verlag London: Springer-Verlag London; 2004.
10.1007/b97668 Google Scholar
- 32Dubois D, Prade H. Fuzzy Sets and Systems:Theory and Applications. New York: Academic Press; 1980.
- 33Saaty TL. The Analytic Hierarchy Process. New York: McGraw Hill International; 1980.
- 34Alonso JA, Lamata MT. Consistency in the analytic hierarchy process: a new approach. Int J Uncertainty Fuzziness Knowl-Based Syst. 2006; 14(4): 445-459.
- 35Saaty RW. The analytic hierarchry process-whats it is and how it is used. Math Modell. 1987; 9(3-5): 161-176.
- 36Kabir ABMZ, Shihan SMA. Selection of renewable energy sources using analytic hierarchy process. Paper presented at: Proceedings of the International Symposium on Analytic Hierarchy Process (ISAHP); August 7-9, 2003; Bali, Indonesia.
- 37Yi SK, Sin HY, Heo E. Selecting sustainable renewable energy source for energy assistance to North Korea. Renew Sustain Energy Rev. 2011; 15: 554-563.
- 38Abdullah L, Najib L. Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia. Int J Sustain Energy. 2016; 35: 360-377.
- 39Claudia R, Martinez M, Pena R. Scenarios for a hierarchical assessment of the global sustainability of electric power plants in Mexico. Renew Sustain Energy Rev. 2014; 33: 154-160.
- 40Talinli I, Topuz E, Akbay MU. Comparative analysis for energy production processes (EPPs): sustainable energy futures for Turkey. Energy Policy. 2010; 38: 4479-4488.
- 41Saaty TL, Vargas LG. Decision Making with the Analytic Network Process. Pittsburgh, PA: Spinger Science; 2005.
- 42Saaty TL. How to make a decision: the analytic hierarchy process. Interfaces. 1994; 24: 19-43.
- 43MacCrimmon KR. Decision making among multiple-attribute alternatives: a survey and consolidated approach. RAND Memorandum. Vols. RM-4823-ARPA; 1968.
- 44Bellman RE, Zadeh LA. Decision-making in a fuzzy environment. Manage Sci. 1970; 17(4): B141-B273.
- 45Çolak 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. 2017; 80C: 840-853.
- 46Erol İ, Sencer S, Özmen A, Searcy C. Fuzzy MCDM framework for locating a nuclear power plant in Turkey. Energy Policy. 2013; 67: 186-197.
- 47Grandhi S, Wibowo S. Application of fuzzy MCDM approach for evaluating and selecting solar energy suppliers. Paper presented at: 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD); July 29-31, 2017; Guilin, China.
- 48Asemi A, Baba M, Asemi A, Abdullah R, Idris N. Fuzzy multi criteria decision making applications: a review study. Paper presented at: 3rd International Conference on Computer Engineering & Mathematical Sciences (ICCEMS 2014); 2014; Langkawi, Malaysia.
- 49Stojcic M, Zavadskas EK, Pamucar D, Stevic Ž, Mardani A. Application of MCDM methods in sustainability engineering: a literature review 2008–2018. Symmetry. 2019; 11:350.
- 50Doukas H, Karakosta C, Psarras J. A linguistic TOPSIS model to evaluate the sustainability of renewable energy options. Int J Global Energy Issues. 2009; 32(1-2): 102-118.
10.1504/IJGEI.2009.027976 Google Scholar
- 51Chen C. Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Set Syst. 2000; 114: 1-9.
- 52Opricovic S. Multicriteria Optimization of Civil Engineering Systems [thesis]. Belgrade; 1998.
- 53Opricovic S, Tzeng G. Extended vikor method in comparison with outranking methods. Eur J Oper Res. 2007; 178(2): 514-529.
- 54Quijano H, Botero B, Dominguez B. MODERGIS application: integrated simulation platform to promote and develop renewable sustainable energy plans, Colombian case study. Renew Sustain Energy Rev. 2012; 16: 5176-5187.
- 55Kaya T, Kahraman C. Multicriteria renewable energy planning using an integrated fuzzy VIKOR and AHP methodology: the case of Istanbul. Energy. 2010; 35: 2517-2527.
- 56Cristóbal JRS. Multi-criteria decision-making in the selection of a renewable energy project in Spain: the Vikor method. Renew Energy. 2011; 36: 498-502.
- 57Wu Y, Zhang B, Xu C, Li L. Site selection decision framework using fuzzy ANP-VIKOR for large commercial rooftop PV system based on sustainability perspective. Sustain Cities Soc. 2018; 40: 454-470.
- 58Roy B. Classement et choix en présence de points de vue multiples (la méthode ELECTRE). La Revue d'Informatique et de Recherche Opérationelle (RIRO). 1968; 8: 57-75.
- 59Beccali M, Cellura M, Mistretta M. Decision-making in energy planning. Application of the Electre method at regional level for the diffusion of renewable energy technology. Renew Energy. 2003; 28(13): 2063-2087.
- 60Saracoglu BO. An experimental research study on the solution of a private small hydropower plant investments selection problem by ELECTRE III/IV, Shannon's entropy, and Saaty's subjective criteria weighting. Adv Decis Sci. 2015; 2015: 1-20.
10.1155/2015/548460 Google Scholar
- 61Brans J, Vincke P, Mareschal B. How to select and how to rank projects: the Promethee method. Eur J Oper Res. 1986; 24(2): 228-238.
- 62Cavallaro F, Molise UO. An Integrated Multi-Criteria System to Assess Sustainable Energy Options: An Application of the Promethee Method; 2005.
- 63Oberschmidt J, Geldermann J, Ludwig J, Schmehl M. Modified PROMETHEE approach for assessing energy technologies. Int J Energy Sector Manage. 2010; 4(2): 183-212.
10.1108/17506221011058696 Google Scholar
- 64Sola AVH, Mota CMM, Kovaleski JL. A model for improving energy efficiency in industrial motor system using multicriteria anglysis. Energy Policy. 2011; 39(6): 3645-3654.
- 65Virtanen M. Choosing the Optimal Energy System for Buildings and Districts. Research s in energy and eco-efficient built enviroment. Espoo, Finland: VTT Technical Research Centre of Finland. 2012; 49-51.
- 66Ren H, Gao W, Zhou W, Nakagami K. Multi-criteria evaluation for the optimal adoption of distributed residential energy systems in Japan. Energy Policy. 2009; 37(12): 5484-5493.
- 67Debbarma B, Chakraborti P, Bose PK, Deb M, Banerjee R. Exploration of PROMETHEE II and VIKOR methodology in a MCDM approach for ascertaining the optimal performance-emission trade-off vantage in a hydrogen-biohol dual fuel endeavour. Fuel. 2017; 210: 922-935.
- 68Deng JL. Spread of grey relational space. J Grey Syst. 1995; 7(3): 96-100.
- 69Deng JL. Introduction to grey system theory. J Grey Syst. 1989; 1(1): 1-24.
- 70Tzeng G, Tasur S. The multiple criteria evaluation of grey relation model. J Grey Syst. 1994; 6(2): 87-108.
- 71Celikbilek Y, Tuysuz F. An integrated grey based multi-criteria decision making approach for the evaluation of renewable energy sources. Energy. 2016; 115: 1246-1258.
- 72Chen M-F, Tzeng G-H. Combining grey relation and TOPSIS concepts for selecting an expatriate host country. Math Comput Modell. 2004; 40: 1473-1490.
- 73Stefano NM, Filho NC, Garcia LVL, da Rocha RUG. COPRAS (Complex Proportional Assessment): state of the art research and its applications. IEEE Latin America Trans. 2015; 13(12): 3899-3906.
- 74Li Y, Shao S, Zhang F. An analysis of the multi-criteria decision-making problem for distributed energy systems. Energies. 2018; 11:2453.
- 75Chatterjee N, Bose GK. A COPRAS-F base multi-criteria group decision making approach for site selection of wind farm. Decis Sci Lett. 2012; 2(2): 1-10.
- 76Dhiman HS, Deb D. Fuzzy TOPSIS and fuzzy COPRAS based multi-criteria decision making for hybrid wind farms. Energy. 2020; 202:117755.
- 77Pradhan S, Ghose D, Shabbiruddin. Analysis and evaluation of power plants: a case study. Advances in Communication, Devices and Networking, ICCDN 2019, Lecture Notes in Electrical Engineering. Vol 662. Singapore: Springer; 2020.
10.1007/978-981-15-4932-8_4 Google Scholar
- 78Sims JR, Zhenyuan W. Fuzzy measures and fuzzy integrals: an overview. Int J Gen Syst. 1990; 17(2-3): 157-189.
- 79Ralescu D, Adams G. The fuzzy integral. J Math Anal Appl. 1980; 75(2): 562-570.
- 80Murofushi T, Sugeno M. An interpretation of fuzzy measures and the Choquet integral as an integral with respect to a fuzzy measure. Fuzzy Set Syst. 1989; 29(2): 201-227.
- 81Heo E, Kim J, Boo KJ. Analysis of the assessment factors for renewable energy dissemination program evaluation using fuzzy AHP. Renew Sustain Energy Rev. 2010; 14(8): 2214-2220.
- 82Kahraman C, Cebi S, Kaya I. Selection among renewable energy alternatives using fuzzy axiomatic design: the case of Turkey. J Univ Comput Sci. 2010; 16(1): 82-102.
- 83Lee SK, Mogi G, Lee SK, Kim JW. Prioritizing the weights of hydrogen energy technologies in the sector of the hydrogen economy by using a fuzzy AHP approach. Int J Hydrogen Energy. 2011; 36(2): 1897-1902.
- 84Wang C-N, Chen Y-T. Evaluation of wave energy location by using an integrated MCDM approach. Energies. 2021; 14:1840.
- 85Perera A, Attalage R, Perera K, Dassanayake V. A hybrid tool to combine multi-objective optimization and multi-criterion decision making in designing standalone hybrid energy systems. Appl Energy. 2013; 107: 412-425.
- 86Balezentiene L, Streimikiene D, Balezentis T. Fuzzy decision support methodology for sustainable energy crop selection. Renew Sustain Energy Rev. 2013; 17(1): 83-93.
- 87Kaya İ, Çolak M, Terzi F. Use of MCDM techniques for energy policy and decision-making problems: a review. Int J Energy Res. 2018; 42: 1-29.
- 88Kumar A, Sah B, Singh AR, et al. A review of multi criteria decision making (MCDM) towards sustainable renewable energy developement. Renew Sustain Energy Rev. 2017; 69: 596-609.
- 89Evans A, Strezov V, Evans TJ. Assessment of sustainability indicators for renewable energy technologies. Renew Sustain Energy Rev. 2009; 13(5): 1082-1088.
- 90Jamal T, Urmee T, Shafiullah G, Shahnia F. Using experts' opinion and multi-criteria decision analysis to determine the weighing of crieria emplyed in planning remote area microgrids. Paper presented at: 2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE); October 24-26, 2018; Phuket, Thailand.
- 91Alizadeh R, Soltanisehat L, Lund PD, Zamanisabzi H. Improving renewable energy policy planning and decision-making through a hybrid MCDM method. Energy Policy. 2019; 137:111174.
- 92Lee H-C, Chang C-T. Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan. Renew Sustain Energy Rev. 2018; 92: 883-896.
- 93Bohra SS, Anvari-Moghaddam A, Mohammadi-Ivatloo B. AHP-assisted multi-criteria decision-making model for planning of microgrids. Paper presented at: IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society; October 14-17, 2019; Lisbon, Portugal.
- 94Contreras SF, Cortes CA, Myrzik JMA. Optimal microgrid planning for enhancing ancillary service provision. J Mod Power Syst Clean Energy. 2019; 7(4): 862-875.
- 95Li C, Cao Y, Cao C, Kuang Y, Zeng L, Fang B. A review of islanding detection methods for microgrid. Renew Sustain Energy Rev. 2014; 35: 211-220.
- 96Diakoulaki D, Antunes CH, Gomes Martins A. MCDA and energy planning. Multiple Criteria Decision Analysis: State of the Art Surveys. International Series in Operations Research & Management Science. (Vol 78). New York, NY: Springer; 2005.
- 97Løken E. Use of multicriteria decision analysis methods for energy planning problems. Renew Sustain Energy Rev. 2007; 11(7): 1584-1595.
- 98Narayan A. A Framework for Microgrid Planning Using Multidisciplinary Design Optimization [thesis]. Ontario, Canada: University of Waterloo; 2015.
- 99Abotah R, Daim T. Towards building a multi perspective policy development framework for transition into renewable energy. Sustain Energy Technol Assess. 2017; 67-88: 21-88.
- 100Chou S-Y, Loc PX, Nguyen T-A-T. Interval valued neutrosophic sets to develop multi-criteria decision making approach for renewable energy selection. Paper presented at: Transdisciplinary Engineering for Complex Socio-Technical Systems (TE2019); 2020; Tokyo, Japan.
- 101Pavan Kumar YBR. Renewable energy based microgrid system sizing and energy management for green buildings. J Mod Power Syst Clean Energy. 2015; 3: 1-13.
- 102Rocha P, Siddiqui A, Stadler M. Improving energy efficiency via smart building energy management systems: a comparison with policy measures. Energy Build. 2015; 88: 203-213.
- 103Zhou L, Li J, Li F, Meng Q, Li J, Xu X. Energy consumption model and energy efficiency of machine tools: a comprehensive literature review. J Clean Prod. 2016; 116: 3721-3734.
- 104Ferreira CC, Vieira E, Gouvea da Gosta SE, Loures ER, de Lima EP. Application of MCDM method for technologies selection to support energy management. Paper presented at: 25th International Conference on Production Research Manufacturing Innovation: Cyber Physical Manufacturing; August 9-14, 2019; Chicago, IL.
- 105Ward E, Hutton BF. SMARTS and SMARTER: improved simple methods for multiattribute utility measurement. Organ Behav Hum Decis Process. 1994; 60(3): 306-325.
- 106Espie P, Ault G, Burt GM, McDonald JR. Multiple criteria decision making techniques applied to electricity distribution system planning. IEE Proc-Gener Transm Distrib. 2003; 150(5): 527.
- 107Rojas-Zerpa J, Yusta J. Application of multicriteria decision methods for electric supply planning in rural and remote areas. Renew Sustain Energy Rev. 2015; 52: 557-571.
- 108Banerjee S, Majumder M. Application of AHP for selection of source for microgrid system. Paper presented at: International Conference on Energy Efficient Technologies for Sustainability (ICEETS); April 2016; Nagercoil, India.
- 109Zhao H, Guo S, Zhao H. Selecting the optimal micro-grid planning program using a novel multi-criteria decision making. Energies. 2018; 11:1840.
- 110Datta A, Saha D, Ray A, Das P. Anti-islanding selection for grid-connected solar photovoltaic system applications: a MCDM based distance approach. Sol Energy. 2014; 110: 519-532.
- 111 HOMER. [Online]. https://www.homerenergy.com/company/index.html.
- 112Ghasemkhani A, Setareh M, Anvari-Moghaddam A, Parvizimosaed M, Rahimi-kian A. Multi-attribute distributed generation planning in a micro-grid considering uncertainty conditions. Paper presented at: 21st Iranian Conference on Electrical Engineering (ICEE'13); Mashhad, Iran.
- 113Wimmler C, Hejazi G, de Oliveira Fernandes E, Moreira C, Connors S. Multi-criteria decision support methods for renewable energy systems on islands. J Clean Energy Technol. 2015; 3(3): 185-195.
10.7763/JOCET.2015.V3.193 Google Scholar
- 114 Photovoltaics Report. Prepared by Fraunhofer Institute for Solar Energy Systems, ISE with support of PSE Projects GmbH, Freiburg, Germany; 2020.
- 115The world's biggest solar power plants. Power Technology. January 10, 2020. [Online]. https://www.power-technology.com/features/the-worlds-biggest-solar-power-plants/. Accessed July 2020.
- 116Tahri M, Hakdaoui M, Maanan M. The evaluation of solar farm locations applying Geographic Information System and Multi-Criteria Decision-Making methods: case study in southern Morocco. Renew Sustain Energy Rev. 2015; 51C: 1354-1362.
- 117Al Garni HZ, Awasthi A. Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia. Appl Energy. 2017; 206: 1225-1240.
- 118Ozdemir S, Sahin G. Multi-criteria decision-making in the location selection for a solar PV power plant using AHP. Measurement. 2018; 129: 218-226.
- 119Algarín CR, Llanos AP, Castro AO. An analytic hierarchy process based approach for evaluating renewable energy sources. Int J Energy Econ Policy. 2017; 7(4): 38-47.
- 120Sindhu S, Nehra V, Luthra S. Investigation of feasibility study of solar farms deployment using hybrid AHP-TOPSIS analysis: case study of India. Renew Sustain Energy Rev. 2017; 73: 496-511.
- 121Solangi YA, Ali Shah SA, Zameer H, Ikram M, Saracoglu BO. Assessing the solar PV power project site selection in Pakistan: based on AHP-fuzzy VIKOR approach. Environ Sci Pollut Res. 2019; 26: 30286-30302.
- 122Tunc A, Tuncay G, Alacakanat Z, Sevimli FS. GIS based solar power plants site selection using analytic hierarchy process (AHP) in Istanbul, Turkey. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 2019; XLII-2/W13: 1353-1360.
10.5194/isprs-archives-XLII-2-W13-1353-2019 Google Scholar
- 123Sánchez-Lozano JM, Teruel-Solano J, Soto-Elvira PL, García-Cascales M. Geographical Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms locations: case study in south-eastern Spain. Renew Sustain Energy Rev. 2013; 24: 544-556.
- 124Merrouni AA, Elalaoui FE, Ghennioui A, Mezrhab A. A GIS-AHP combination for the sites assessment of large-scale CSP plants with dry and wet cooling systems. Case study: Eastern Morocco. Sol Energy. 2018; 166: 2-12.
- 125Aragonés-Beltrán P, Chaparro-González F, Pastor-Ferrando JP, Rodríguez-Pozo F. An ANP-based approach for the selection of photovoltaic solar power plant. Renew Sustain Energy Rev. 2010; 14: 249-264.
- 126Chen C-R, Huang C-C, Tsuei H-J. A hybrid MCDM model for improving GIS-based solar farms site selection. Int J Photoenergy. 2014; 2014: 1-9.
- 127Sánchez-Lozano JM, Antunes CH, García-Cascales MS, Dias LC. GIS-based photovoltaic solar farms site selection using ELECTRE-TRI: evaluating the case for Torre Pacheco, Murcia, Southeast of Spain. Renew Energy. 2014; 66: 478-494.
- 128Wu Y, Zhang B, Wu C, Zhang T, Liu F. Optimal site selection for parabolic trough concentrating solar power plant using extended PROMETHEE method: a case in China. Renew Energy. 2019; 143: 1910-1927.
- 129Uyan M. GIS-based solar farms site selection using analytic hierarchy process (AHP) in Karapinar region, Konya/Turkey. Renew Sustain Energy Rev. 2013; 28: 11-17.
- 130Akkas OP, Erten Y, Cam E, Inanc N. Optimal site selection for a solar power plant in the Central Anatolian Region of Turkey. Int J Photoenergy. 2017; 2017: 13.
- 131Sánchez-Lozano JM, García-Cascales MS, Lamata ML. Comparative TOPSIS-ELECTRE TRI methods for optimal sites for photovoltaic solar farms. Case study in Spain. J Clean Prod. 2016; 127: 387-398.
- 132Hashemizadeh A, Ju Y, Dong P. A combined geographical information system and Best–Worst Method approach for site selection for photovoltaic power plant projects. Int J Environ Sci Technol. 2020; 17: 2027-2042.
- 133Feng J, Li M, Li Y. Study of decision framework of shopping mall photovoltaic plan selection based on DEMATEL and ELECTRE III with symmetry under neutrosophic set environment. Symmetry. 2018; 10:150.
- 134February 2020. [Online]. https://solarpaces.nrel.gov/.
- 135February 2020. [Online]. https://www.energy.gov/eere/solar/parabolic-trough.
- 136Tegou LI, Polatidis H, Haralambopoulos DA. Environmental management framework for wind farm siting: methodology and case study. J Environ Manage. 2010; 91: 2134-2147.
- 137Lee AH, Chen HH, Kang H-Y. Multi-criteria decision making on strategic selection of wind farms. Renew Energy. 2009; 34: 120-126.
- 138Moradi SYH, Noorollahi Y, Rosso D. Multi-criteria decision support system for wind farm site selection and sensitivity analysis: case study of Alborz Province, Iran. Energy Strat Rev. 2020; 29:100478.
- 139Rezaian S, Jozi SA. Application of multi criteria decision-making technique in site selection of wind farm- a case study of northwestern Iran. J Indian Soc Remote Sens. 2016; 44: 803-809.
- 140Szurek M, Blachowski J, Nowacka A. GIS-based method for wind farm location multi-criteria analysis. Min. Sci. 2014; 21: 65-81.
- 141Sánchez-Lozano J, García-Cascales M, Lamata M. GIS-based onshore wind farm site selection using Fuzzy Multi-Criteria Decision Making methods. Evaluating the case of Southeastern Spain. Appl Energy. 2016; 171: 86-102.
- 142Ayodele T, Ogunjuyigbe A, Odigie O, Munda J. A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process: the case study of Nigeria. Appl Energy. 2018; 228: 1853-1869.
- 143Ajanaku BA, Strager MP, Collins AR. GIS-based multi-criteria decision analysis of utility-scale wind farm site suitability in West Virginia. GeoJournal. 2021; 1-23.
- 144Kumar I, Sinha K. Regional land suitability framework for utility-scale wind farm development. J Infrastruct Syst. 2016; 22(3):04016018.
- 145Noorollahi Y, Yousefi H, Mohammadi M. Multi-criteria decision support system for wind farm site selection. Sustainable Energy Technol Assess. 2016; 13: 38-50.
- 146Chamanehpour E, Ahmadizadeh, Akbarpour. Site selection of wind power plant using multi-criteria decision-making methods in GIS: a case study. Comput Ecol Softw. 2017; 7(2): 49-64.
- 147Ur Rehman A, Abidi MH, Umer U, Usmani YS. Multi-criteria decision-making approach for selecting wind energy power plant locations. Sustainability. 2019; 11:6112.
- 148Al-Awami A, Sortomme E, El-Sharkawi M. Optimizing economic/environmental dispatch with wind and thermal units. Paper presented at: Proceedings of the 2009 IEEE Power & Energy Society General Meeting; July 26-30, 2009; Calgary, Canada:26-30.
- 149Strazzera E, Mura M, Contu D. Combining choice experiments with psychometric scales to assess the social acceptability of wind energy projects: a latent class approach. Energy Policy. 2012; 48: 334-347.
- 150Heydarian-Forushani E, Golshan M, Moghaddam M, Shafie-khah M, Catalão J. Robust scheduling of variable wind generation by coordination of bulk energy storages and demand response. Energy Convers Manage. 2015; 106: 941-950.
- 151Alsyouf I. Wind energy system reliability and maintainability, and operation and maintenance strategies. In: JD Sørensen, JN Sørensen, eds. Wind Energy Systems. Woodhead Publishing Series in Energy. Sawston, UK: Woodhead Publishing; 2011: 303-328.
10.1533/9780857090638.3.303 Google Scholar
- 152Talinli I, Topuz E, Aydin E, Kabakcı S. A holistic approach for wind farm site selection by FAHP. Wind farm: technical regulations, potential estimation and siting assessment. Wind Farm - Technical Regulations, Potential Estimation and Siting Assessment. Croatia: InTech; 2011: 213-234.
10.5772/17311 Google Scholar
- 153Muhsen DH, Al-Nidawi YM, Khatib T, Haider HT. Domestic load management based on integration of MODE and AHP-TOPSIS decision making methods. Sustain Cities Soc. 2019; 50:101651.
- 154Bassamzadeha N, Ghanem R, Lu S, Kazemitabard SJ. Robust scheduling of smart appliances with uncertain electricity prices in a heterogeneous population. Energy Build. 2014; 84: 537-547.
- 155Dong J, Huo H, Guo S. Demand side management performance evaluation for commercial enterprises. Sustainability. 2016; 8(10):1041.
- 156Vashishtha S, Ramachandran M. Multicriteria evaluation of demand side management (DSM) implementation strategies in the Indian power sector. Energy. 2006; 31: 2210-2225.
- 157Siksnelyte-Butkiene I, Kazimieras Zavadskas E, Streimikiene D. Multi-criteria decision-making (MCDM) for the Assessment of renewable energy technologies in a household: a review. Energies. 2020; 13:1164.
- 158Karabiber A. Controllable AC/DC integration for power quality improvement in microgrids. Adv Electr Comput Eng. 2019; 19(2): 97-104.
- 159Lopes JAP, Moreira CL, Madureira AG. Defining control strategies for MicroGrids islanded operation. IEEE Trans Power Syst. 2006; 21(2): 916-924.
- 160Moran B. Microgrid load management and control strategies. Paper presented at: 2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D); May 3-5, 2016; Dallas, TX:1-4.
- 161Baumann M, Weil M, Peters JF, Chibeles-Martins N, Moniz AB. A review of multi-criteria decision making approaches for evaluating energy storage systems for grid applications. Renew Sustain Energy Rev. 2019; 107: 516-534.
- 162Li N, Zhang H, Zhang X, Ma X, Guo S. How to select the optimal electrochemical energy storage planning program? a hybrid MCDM method. Energies. 2020; 13(4): 1-20.
- 163Zhao H, Guo S, Zhao H. Comprehensive assessment for battery energy storage systems based on fuzzy-MCDM considering risk preferences. Energy. 2018; 168: 450-461.
- 164Barin A, Canha LN, Abaide ADR, Magnago KF. Selection of storage energy technologies in a power quality scenario—the AHP and the fuzzy logic. Paper presented at: 2009 35th Annual Conference of IEEE Industrial Electronics (IECON'09); November 3-5, 2009; Porto, Portugal.
- 165Chang D-Y. Applications of the extent analysis method on fuzzy AHP. Eur J Oper Res. 1996; 95(3): 649-655.
- 166Tao L, Qi L, Dong Y, Lv S. Fuzzy TOPSIS approach based on axiomatic fuzzy set for assessing thermal-energy storage in concentrated solar power (CSP) systems. Paper presented at: 2017 International Conference on Network and Information Systems for Computers (ICNISC); April 14-16, 2017; Shanghai, China.
