IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v218y2023ics0960148123012077.html
   My bibliography  Save this article

Sustainable renewable energy system selection for self-sufficient households using integrated fermatean neutrosophic fuzzy stratified AHP-MARCOS approach

Author

Listed:
  • Manirathinam, Thangaraj
  • Narayanamoorthy, Samayan
  • Geetha, Selvaraj
  • Othman, Mohd Fairuz Iskandar
  • Alotaibi, Badr Saad
  • Ahmadian, Ali
  • Kang, Daekook

Abstract

Future focus ought to be on developing sustainable cities by cutting down on energy waste, and constructing environments that are carbon neutral. To achieve this objective, it is necessary to develop smart homes with self-sufficient power generation, storage, and consumption based on distributed renewable energy resources with good infrastructure. This energy system should be environmentally, technically, commercially, and socially sustainable. However, none of the alternative energy sources can completely meet these demands, even though wind and solar energy are often the most practical forms of renewable energy. Currently, many studies focused on fusing these two to benefit from their complimentary characteristics. Deploying optimal system of renewable energy on each house is very difficult due to various socio-economical barriers in selection and implementation of such technology leads to formulate respective decision-making problems. The fermatean neutrosophic fuzzy preferences handles problems uncertainty and the stratified target concept approves its ranking sustainability. Since, eight plausible targets were identified for ideal criteria weights which determined hybrid electric system as the best choice out of four possible options for future smart houses. The economical benefits of hybrid system is convincing enough to be taken into account for increased power generating capacity in developing nations. Furthermore, the proposed hybrid fuzzy decision-making technique is quite encouraging for governing authorities or specialists to make forward-thinking judgments on numerous real-world challenges due to its outcome sustainability, accuracy, and consistency.

Suggested Citation

  • Manirathinam, Thangaraj & Narayanamoorthy, Samayan & Geetha, Selvaraj & Othman, Mohd Fairuz Iskandar & Alotaibi, Badr Saad & Ahmadian, Ali & Kang, Daekook, 2023. "Sustainable renewable energy system selection for self-sufficient households using integrated fermatean neutrosophic fuzzy stratified AHP-MARCOS approach," Renewable Energy, Elsevier, vol. 218(C).
    • Handle: RePEc:eee:renene:v:218:y:2023:i:c:s0960148123012077
    DOI: 10.1016/j.renene.2023.119292
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148123012077
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2023.119292?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Elkadeem, M.R. & Younes, Ali & Sharshir, Swellam W. & Campana, Pietro Elia & Wang, Shaorong, 2021. "Sustainable siting and design optimization of hybrid renewable energy system: A geospatial multi-criteria analysis," Applied Energy, Elsevier, vol. 295(C).
    2. Kumar, Abhishek & Sah, Bikash & Singh, Arvind R. & Deng, Yan & He, Xiangning & Kumar, Praveen & Bansal, R.C., 2017. "A review of multi criteria decision making (MCDM) towards sustainable renewable energy development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 596-609.
    3. Khan, Khalid & Su, Chi Wei & Rehman, Ashfaq U. & Ullah, Rahman, 2022. "Is technological innovation a driver of renewable energy?," Technology in Society, Elsevier, vol. 70(C).
    4. Salim, Ruhul A. & Shafiei, Sahar, 2014. "Urbanization and renewable and non-renewable energy consumption in OECD countries: An empirical analysis," Economic Modelling, Elsevier, vol. 38(C), pages 581-591.
    5. Nigim, K. & Munier, N. & Green, J., 2004. "Pre-feasibility MCDM tools to aid communities in prioritizing local viable renewable energy sources," Renewable Energy, Elsevier, vol. 29(11), pages 1775-1791.
    6. Saraswat, S.K. & Digalwar, Abhijeet K. & Yadav, S.S. & Kumar, Gaurav, 2021. "MCDM and GIS based modelling technique for assessment of solar and wind farm locations in India," Renewable Energy, Elsevier, vol. 169(C), pages 865-884.
    7. Nema, Pragya & Nema, R.K. & Rangnekar, Saroj, 2009. "A current and future state of art development of hybrid energy system using wind and PV-solar: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 2096-2103, October.
    8. Magazzino, Cosimo & Mele, Marco & Schneider, Nicolas, 2021. "A machine learning approach on the relationship among solar and wind energy production, coal consumption, GDP, and CO2 emissions," Renewable Energy, Elsevier, vol. 167(C), pages 99-115.
    9. Dilek Temiz Dinç & Ece C. Akdoğan, 2019. "Renewable Energy Production, Energy Consumption and Sustainable Economic Growth in Turkey: A VECM Approach," Sustainability, MDPI, vol. 11(5), pages 1-14, February.
    10. Guo, Jiacheng & Liu, Zhijian & Li, Ying & Wu, Di & Liu, Xuan & Zhang, Shicong & Yang, Xinyan & Ge, Hua & Zhang, Peiwen, 2022. "Thermodynamic performance analyses and optimization design method of a novel distributed energy system coupled with hybrid-energy storage," Renewable Energy, Elsevier, vol. 182(C), pages 1182-1200.
    11. Speidel, Stuart & Bräunl, Thomas, 2016. "Leaving the grid—The effect of combining home energy storage with renewable energy generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1213-1224.
    12. Sadorsky, Perry, 2009. "Renewable energy consumption, CO2 emissions and oil prices in the G7 countries," Energy Economics, Elsevier, vol. 31(3), pages 456-462, May.
    13. Bobinaite, Viktorija & Tarvydas, Dalius, 2014. "Financing instruments and channels for the increasing production and consumption of renewable energy: Lithuanian case," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 259-276.
    14. Lee, Hsing-Chen & Chang, Ching-Ter, 2018. "Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 92(C), pages 883-896.
    15. Alizadeh, Reza & Soltanisehat, Leili & Lund, Peter D. & Zamanisabzi, Hamed, 2020. "Improving renewable energy policy planning and decision-making through a hybrid MCDM method," Energy Policy, Elsevier, vol. 137(C).
    16. Indre Siksnelyte-Butkiene & Edmundas Kazimieras Zavadskas & Dalia Streimikiene, 2020. "Multi-Criteria Decision-Making (MCDM) for the Assessment of Renewable Energy Technologies in a Household: A Review," Energies, MDPI, vol. 13(5), pages 1-22, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sandra, Michael & Narayanamoorthy, Samayan & Ferrara, Massimiliano & Innab, Nisreen & Ahmadian, Ali & Kang, Daekook, 2024. "A novel decision support system for the appraisal and selection of green warehouses," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    2. Mota, Bruno & Faria, Pedro & Vale, Zita, 2024. "Energy cost optimization through load shifting in a photovoltaic energy-sharing household community," Renewable Energy, Elsevier, vol. 221(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Elkadeem, Mohamed R. & Younes, Ali & Mazzeo, Domenico & Jurasz, Jakub & Elia Campana, Pietro & Sharshir, Swellam W. & Alaam, Mohamed A., 2022. "Geospatial-assisted multi-criterion analysis of solar and wind power geographical-technical-economic potential assessment," Applied Energy, Elsevier, vol. 322(C).
    2. Asadi, Meysam & Ramezanzade, Mohsen & Pourhossein, Kazem, 2023. "A global evaluation model applied to wind power plant site selection," Applied Energy, Elsevier, vol. 336(C).
    3. Ali Mostafaeipour & Seyyed Jalaladdin Hosseini Dehshiri & Seyyed Shahabaddin Hosseini Dehshiri & Mehdi Jahangiri & Kuaanan Techato, 2020. "A Thorough Analysis of Potential Geothermal Project Locations in Afghanistan," Sustainability, MDPI, vol. 12(20), pages 1-17, October.
    4. Rivero-Iglesias, Jose M. & Puente, Javier & Fernandez, Isabel & León, Omar, 2023. "Integrated model for the assessment of power generation alternatives through analytic hierarchy process and a fuzzy inference system. Case study of Spain," Renewable Energy, Elsevier, vol. 211(C), pages 563-581.
    5. Ullah, Zia & Elkadeem, M.R. & Kotb, Kotb M. & Taha, Ibrahim B.M. & Wang, Shaorong, 2021. "Multi-criteria decision-making model for optimal planning of on/off grid hybrid solar, wind, hydro, biomass clean electricity supply," Renewable Energy, Elsevier, vol. 179(C), pages 885-910.
    6. Dimitra G. Vagiona, 2021. "Comparative Multicriteria Analysis Methods for Ranking Sites for Solar Farm Deployment: A Case Study in Greece," Energies, MDPI, vol. 14(24), pages 1-23, December.
    7. Bilgili, Faik & Zarali, Fulya & Ilgün, Miraç Fatih & Dumrul, Cüneyt & Dumrul, Yasemin, 2022. "The evaluation of renewable energy alternatives for sustainable development in Turkey using ‌intuitionistic‌ ‌fuzzy‌-TOPSIS method," Renewable Energy, Elsevier, vol. 189(C), pages 1443-1458.
    8. Paula Donaduzzi Rigo & Graciele Rediske & Carmen Brum Rosa & Natália Gava Gastaldo & Leandro Michels & Alvaro Luiz Neuenfeldt Júnior & Julio Cezar Mairesse Siluk, 2020. "Renewable Energy Problems: Exploring the Methods to Support the Decision-Making Process," Sustainability, MDPI, vol. 12(23), pages 1-27, December.
    9. Murshed, Muntasir, 2019. "Trade Liberalization Policies and Renewable Energy Transition in Low and Middle-Income Countries? An Instrumental Variable Approach," MPRA Paper 97075, University Library of Munich, Germany.
    10. Alkan, Ömer & Albayrak, Özlem Karadağ, 2020. "Ranking of renewable energy sources for regions in Turkey by fuzzy entropy based fuzzy COPRAS and fuzzy MULTIMOORA," Renewable Energy, Elsevier, vol. 162(C), pages 712-726.
    11. Ben Jebli, Mehdi & Ben Youssef, Slim, 2015. "Output, renewable and non-renewable energy consumption and international trade: Evidence from a panel of 69 countries," Renewable Energy, Elsevier, vol. 83(C), pages 799-808.
    12. Huibing Cheng & Shanshui Zheng & Jianghong Feng, 2022. "A Fuzzy Multi-Criteria Method for Sustainable Ferry Operator Selection: A Case Study," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    13. Pei-Hsuan Tsai & Chih-Jou Chen & Ho-Chin Yang, 2021. "Using Porter’s Diamond Model to Assess the Competitiveness of Taiwan’s Solar Photovoltaic Industry," SAGE Open, , vol. 11(1), pages 21582440209, January.
    14. Lau, Lin-Sea & Choong, Chee-Keong & Ng, Cheong-Fatt & Liew, Feng-Mei & Ching, Suet-Ling, 2019. "Is nuclear energy clean? Revisit of Environmental Kuznets Curve hypothesis in OECD countries," Economic Modelling, Elsevier, vol. 77(C), pages 12-20.
    15. Yu, Jinna & Tang, Yuk Ming & Chau, Ka Yin & Nazar, Raima & Ali, Sajid & Iqbal, Wasim, 2022. "Role of solar-based renewable energy in mitigating CO2 emissions: Evidence from quantile-on-quantile estimation," Renewable Energy, Elsevier, vol. 182(C), pages 216-226.
    16. José Carlos Romero & Pedro Linares, 2021. "Multiple Criteria Decision-Making as an Operational Conceptualization of Energy Sustainability," Sustainability, MDPI, vol. 13(21), pages 1-14, October.
    17. Mihaela Simionescu & Yuriy Bilan & Emília Krajňáková & Dalia Streimikiene & Stanisław Gędek, 2019. "Renewable Energy in the Electricity Sector and GDP per Capita in the European Union," Energies, MDPI, vol. 12(13), pages 1-15, June.
    18. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    19. Ben Jebli, Mehdi & Ben Youssef, Slim & Apergis, Nicholas, 2014. "The Dynamic Linkage between CO2 emissions, Economic Growth, Renewable Energy Consumption, Number of Tourist Arrivals and Trade," MPRA Paper 57261, University Library of Munich, Germany.
    20. Magazzino, Cosimo & Giolli, Lorenzo, 2021. "The relationship among railway networks, energy consumption, and real added value in Italy. Evidence form ARDL and Wavelet analysis," Research in Transportation Economics, Elsevier, vol. 90(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:218:y:2023:i:c:s0960148123012077. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.