Sustainable prime movers selection for biogas-based combined heat and power for a community microgrid: A hybrid fuzzy multi criteria decision-making approach with consolidated ranking strategies
Combined heat and power (CHP) based community microgrid using renewable resources such as biogas is gaining fast prominence in municipalities across the world as a strategy to decarbonise energy sector and brings power supply close to the consumers. But for profitable operation of a CHP system, the...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Energy Conversion and Management: X |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590174522001040 |
| _version_ | 1811207636160348160 |
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| author | Moshood Akanni Alao Olawale Mohammed Popoola Temitope Raphael Ayodele |
| author_facet | Moshood Akanni Alao Olawale Mohammed Popoola Temitope Raphael Ayodele |
| author_sort | Moshood Akanni Alao |
| collection | DOAJ |
| description | Combined heat and power (CHP) based community microgrid using renewable resources such as biogas is gaining fast prominence in municipalities across the world as a strategy to decarbonise energy sector and brings power supply close to the consumers. But for profitable operation of a CHP system, the selection of suitable prime movers (PMs) is very germane. It has become a significant issue to assess PM alternatives in detail from the investor’s or policy maker’s view point. Due to varying characteristics of each PM, multi criteria decision making (MCDM) techniques could be efficient tools for selecting optimal PM and making a reasonable decision. In this work, four PMs such as internal combustion engine (ICE), gas turbine (GT), micro-gas turbine (MGT) and fuel cells (FCs) are selected as alternatives with twenty evaluation criteria. The weights of criteria for each PM are evaluated taking a cue from the integration of Fuzzy-Best-Worst (Fuzzy-BWM) and Fuzzy-Entropy methods using fuzzy preference variables. These PMs are ranked using Fuzzy-Combined Compromise Solution (Fuzzy-CoCoSo) on the basis of technical, economic, environmental and social specifications. Thereafter, results based on each weighting preference are merged by using the Borda count and Copeland ranking strategies. The results reveal that initial investment cost in the economic category and footprint in the social category are respectively the most and least significant criteria for PM assessment. It is also revealed that FCs are the most sustainable PM with a compromise score of 2.8053 followed by ICE with a score of 2.5767. The least ranked PM is the MGT with a compromise value of 2.5541. Furthermore, the robustness and reliability of the results are tested by applying a sensitivity analysis and comparative assessment with five existing Fuzzy MCDM methods. This research could be useful to investors and policy makers for the selection of sustainable PM at the planning stage of a biogas-based CHP community microgrid. |
| first_indexed | 2024-04-12T04:08:03Z |
| format | Article |
| id | doaj.art-da470ffd819f47a8860a7d992f17a14c |
| institution | Directory Open Access Journal |
| issn | 2590-1745 |
| language | English |
| last_indexed | 2024-04-12T04:08:03Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Conversion and Management: X |
| spelling | doaj.art-da470ffd819f47a8860a7d992f17a14c2022-12-22T03:48:35ZengElsevierEnergy Conversion and Management: X2590-17452022-12-0116100281Sustainable prime movers selection for biogas-based combined heat and power for a community microgrid: A hybrid fuzzy multi criteria decision-making approach with consolidated ranking strategiesMoshood Akanni Alao0Olawale Mohammed Popoola1Temitope Raphael Ayodele2Department of Electrical Engineering & Centre for Energy and Electric Power, Tshwane University of Technology, Pretoria, South Africa; Corresponding author.Department of Electrical Engineering & Centre for Energy and Electric Power, Tshwane University of Technology, Pretoria, South AfricaDepartment of Electrical and Electronic Engineering, Faculty of Technology, University of Ibadan, Ibadan, NigeriaCombined heat and power (CHP) based community microgrid using renewable resources such as biogas is gaining fast prominence in municipalities across the world as a strategy to decarbonise energy sector and brings power supply close to the consumers. But for profitable operation of a CHP system, the selection of suitable prime movers (PMs) is very germane. It has become a significant issue to assess PM alternatives in detail from the investor’s or policy maker’s view point. Due to varying characteristics of each PM, multi criteria decision making (MCDM) techniques could be efficient tools for selecting optimal PM and making a reasonable decision. In this work, four PMs such as internal combustion engine (ICE), gas turbine (GT), micro-gas turbine (MGT) and fuel cells (FCs) are selected as alternatives with twenty evaluation criteria. The weights of criteria for each PM are evaluated taking a cue from the integration of Fuzzy-Best-Worst (Fuzzy-BWM) and Fuzzy-Entropy methods using fuzzy preference variables. These PMs are ranked using Fuzzy-Combined Compromise Solution (Fuzzy-CoCoSo) on the basis of technical, economic, environmental and social specifications. Thereafter, results based on each weighting preference are merged by using the Borda count and Copeland ranking strategies. The results reveal that initial investment cost in the economic category and footprint in the social category are respectively the most and least significant criteria for PM assessment. It is also revealed that FCs are the most sustainable PM with a compromise score of 2.8053 followed by ICE with a score of 2.5767. The least ranked PM is the MGT with a compromise value of 2.5541. Furthermore, the robustness and reliability of the results are tested by applying a sensitivity analysis and comparative assessment with five existing Fuzzy MCDM methods. This research could be useful to investors and policy makers for the selection of sustainable PM at the planning stage of a biogas-based CHP community microgrid.http://www.sciencedirect.com/science/article/pii/S2590174522001040Prime movers selectionFuzzy-CoCoSoCommunity microgridCombined heat and powerFuel cellsBorda rule |
| spellingShingle | Moshood Akanni Alao Olawale Mohammed Popoola Temitope Raphael Ayodele Sustainable prime movers selection for biogas-based combined heat and power for a community microgrid: A hybrid fuzzy multi criteria decision-making approach with consolidated ranking strategies Energy Conversion and Management: X Prime movers selection Fuzzy-CoCoSo Community microgrid Combined heat and power Fuel cells Borda rule |
| title | Sustainable prime movers selection for biogas-based combined heat and power for a community microgrid: A hybrid fuzzy multi criteria decision-making approach with consolidated ranking strategies |
| title_full | Sustainable prime movers selection for biogas-based combined heat and power for a community microgrid: A hybrid fuzzy multi criteria decision-making approach with consolidated ranking strategies |
| title_fullStr | Sustainable prime movers selection for biogas-based combined heat and power for a community microgrid: A hybrid fuzzy multi criteria decision-making approach with consolidated ranking strategies |
| title_full_unstemmed | Sustainable prime movers selection for biogas-based combined heat and power for a community microgrid: A hybrid fuzzy multi criteria decision-making approach with consolidated ranking strategies |
| title_short | Sustainable prime movers selection for biogas-based combined heat and power for a community microgrid: A hybrid fuzzy multi criteria decision-making approach with consolidated ranking strategies |
| title_sort | sustainable prime movers selection for biogas based combined heat and power for a community microgrid a hybrid fuzzy multi criteria decision making approach with consolidated ranking strategies |
| topic | Prime movers selection Fuzzy-CoCoSo Community microgrid Combined heat and power Fuel cells Borda rule |
| url | http://www.sciencedirect.com/science/article/pii/S2590174522001040 |
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