A Multi-Criteria Decision-Making Approach to Determine the Optimal Hybrid Energy System in Coastal Off-Grid Areas: A Case Study of Bangladesh
Abstract The coastal areas of Bangladesh have a number of off-grid locations, which are out of national grid coverage. Therefore, off-grid technology is the only solution to electrify those areas. At present, solar home system (SHS) is playing pivotal role to fulfil the electricity demand and, also,...
Ausführliche Beschreibung
Autor*in: |
Ali, Tausif [verfasserIn] Ma, Hongzhong [verfasserIn] Nahian, Ahmed Jaudat [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2020 |
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Schlagwörter: |
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Übergeordnetes Werk: |
Enthalten in: Process integration and optimization for sustainability - [Singapore] : Springer Singapore, 2017, 4(2020), 3 vom: 18. Apr., Seite 265-277 |
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Übergeordnetes Werk: |
volume:4 ; year:2020 ; number:3 ; day:18 ; month:04 ; pages:265-277 |
Links: |
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DOI / URN: |
10.1007/s41660-020-00116-9 |
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Katalog-ID: |
SPR040601390 |
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520 | |a Abstract The coastal areas of Bangladesh have a number of off-grid locations, which are out of national grid coverage. Therefore, off-grid technology is the only solution to electrify those areas. At present, solar home system (SHS) is playing pivotal role to fulfil the electricity demand and, also, contributing to the community both economically and socially. However, due to the technical, economic, environmental and social maturity, hybrid energy system (HES) could be more lucrative in the off-grid areas of Bangladesh. Therefore, proper selection of the HES is highly essential. In this study, the focus is given on the coastal off-grid regions to select the optimal HES using the multi-criteria decision-making (MCDM) method. Based on the potentiality of renewable energy resources, six HES alternatives were selected for evaluation. To evaluate the HESs, thirteen criteria were selected based on experts’ agreement, and to check this agreement, content validity was estimated. In addition, criteria importance through intercriteria correlation (CRITIC) method was deployed to find the weights of the criteria. Finally, a new MCDM method named combinative distance-based assessment (CODAS) was applied to select the optimum HES. The results revealed that the PV/battery/biogas/diesel generator HES is the optimum solution for the study area. | ||
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700 | 1 | |a Nahian, Ahmed Jaudat |e verfasserin |4 aut | |
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10.1007/s41660-020-00116-9 doi (DE-627)SPR040601390 (SPR)s41660-020-00116-9-e DE-627 ger DE-627 rakwb eng 330 ASE 330 ASE Ali, Tausif verfasserin aut A Multi-Criteria Decision-Making Approach to Determine the Optimal Hybrid Energy System in Coastal Off-Grid Areas: A Case Study of Bangladesh 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The coastal areas of Bangladesh have a number of off-grid locations, which are out of national grid coverage. Therefore, off-grid technology is the only solution to electrify those areas. At present, solar home system (SHS) is playing pivotal role to fulfil the electricity demand and, also, contributing to the community both economically and socially. However, due to the technical, economic, environmental and social maturity, hybrid energy system (HES) could be more lucrative in the off-grid areas of Bangladesh. Therefore, proper selection of the HES is highly essential. In this study, the focus is given on the coastal off-grid regions to select the optimal HES using the multi-criteria decision-making (MCDM) method. Based on the potentiality of renewable energy resources, six HES alternatives were selected for evaluation. To evaluate the HESs, thirteen criteria were selected based on experts’ agreement, and to check this agreement, content validity was estimated. In addition, criteria importance through intercriteria correlation (CRITIC) method was deployed to find the weights of the criteria. Finally, a new MCDM method named combinative distance-based assessment (CODAS) was applied to select the optimum HES. The results revealed that the PV/battery/biogas/diesel generator HES is the optimum solution for the study area. Hybrid energy system (dpeaa)DE-He213 Off-grid (dpeaa)DE-He213 MCDM (dpeaa)DE-He213 CRITIC (dpeaa)DE-He213 CODAS (dpeaa)DE-He213 Content validity (dpeaa)DE-He213 Ma, Hongzhong verfasserin aut Nahian, Ahmed Jaudat verfasserin aut Enthalten in Process integration and optimization for sustainability [Singapore] : Springer Singapore, 2017 4(2020), 3 vom: 18. Apr., Seite 265-277 (DE-627)876318316 (DE-600)2879697-4 2509-4246 nnns volume:4 year:2020 number:3 day:18 month:04 pages:265-277 https://dx.doi.org/10.1007/s41660-020-00116-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 4 2020 3 18 04 265-277 |
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10.1007/s41660-020-00116-9 doi (DE-627)SPR040601390 (SPR)s41660-020-00116-9-e DE-627 ger DE-627 rakwb eng 330 ASE 330 ASE Ali, Tausif verfasserin aut A Multi-Criteria Decision-Making Approach to Determine the Optimal Hybrid Energy System in Coastal Off-Grid Areas: A Case Study of Bangladesh 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The coastal areas of Bangladesh have a number of off-grid locations, which are out of national grid coverage. Therefore, off-grid technology is the only solution to electrify those areas. At present, solar home system (SHS) is playing pivotal role to fulfil the electricity demand and, also, contributing to the community both economically and socially. However, due to the technical, economic, environmental and social maturity, hybrid energy system (HES) could be more lucrative in the off-grid areas of Bangladesh. Therefore, proper selection of the HES is highly essential. In this study, the focus is given on the coastal off-grid regions to select the optimal HES using the multi-criteria decision-making (MCDM) method. Based on the potentiality of renewable energy resources, six HES alternatives were selected for evaluation. To evaluate the HESs, thirteen criteria were selected based on experts’ agreement, and to check this agreement, content validity was estimated. In addition, criteria importance through intercriteria correlation (CRITIC) method was deployed to find the weights of the criteria. Finally, a new MCDM method named combinative distance-based assessment (CODAS) was applied to select the optimum HES. The results revealed that the PV/battery/biogas/diesel generator HES is the optimum solution for the study area. Hybrid energy system (dpeaa)DE-He213 Off-grid (dpeaa)DE-He213 MCDM (dpeaa)DE-He213 CRITIC (dpeaa)DE-He213 CODAS (dpeaa)DE-He213 Content validity (dpeaa)DE-He213 Ma, Hongzhong verfasserin aut Nahian, Ahmed Jaudat verfasserin aut Enthalten in Process integration and optimization for sustainability [Singapore] : Springer Singapore, 2017 4(2020), 3 vom: 18. Apr., Seite 265-277 (DE-627)876318316 (DE-600)2879697-4 2509-4246 nnns volume:4 year:2020 number:3 day:18 month:04 pages:265-277 https://dx.doi.org/10.1007/s41660-020-00116-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 4 2020 3 18 04 265-277 |
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10.1007/s41660-020-00116-9 doi (DE-627)SPR040601390 (SPR)s41660-020-00116-9-e DE-627 ger DE-627 rakwb eng 330 ASE 330 ASE Ali, Tausif verfasserin aut A Multi-Criteria Decision-Making Approach to Determine the Optimal Hybrid Energy System in Coastal Off-Grid Areas: A Case Study of Bangladesh 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The coastal areas of Bangladesh have a number of off-grid locations, which are out of national grid coverage. Therefore, off-grid technology is the only solution to electrify those areas. At present, solar home system (SHS) is playing pivotal role to fulfil the electricity demand and, also, contributing to the community both economically and socially. However, due to the technical, economic, environmental and social maturity, hybrid energy system (HES) could be more lucrative in the off-grid areas of Bangladesh. Therefore, proper selection of the HES is highly essential. In this study, the focus is given on the coastal off-grid regions to select the optimal HES using the multi-criteria decision-making (MCDM) method. Based on the potentiality of renewable energy resources, six HES alternatives were selected for evaluation. To evaluate the HESs, thirteen criteria were selected based on experts’ agreement, and to check this agreement, content validity was estimated. In addition, criteria importance through intercriteria correlation (CRITIC) method was deployed to find the weights of the criteria. Finally, a new MCDM method named combinative distance-based assessment (CODAS) was applied to select the optimum HES. The results revealed that the PV/battery/biogas/diesel generator HES is the optimum solution for the study area. Hybrid energy system (dpeaa)DE-He213 Off-grid (dpeaa)DE-He213 MCDM (dpeaa)DE-He213 CRITIC (dpeaa)DE-He213 CODAS (dpeaa)DE-He213 Content validity (dpeaa)DE-He213 Ma, Hongzhong verfasserin aut Nahian, Ahmed Jaudat verfasserin aut Enthalten in Process integration and optimization for sustainability [Singapore] : Springer Singapore, 2017 4(2020), 3 vom: 18. Apr., Seite 265-277 (DE-627)876318316 (DE-600)2879697-4 2509-4246 nnns volume:4 year:2020 number:3 day:18 month:04 pages:265-277 https://dx.doi.org/10.1007/s41660-020-00116-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 4 2020 3 18 04 265-277 |
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10.1007/s41660-020-00116-9 doi (DE-627)SPR040601390 (SPR)s41660-020-00116-9-e DE-627 ger DE-627 rakwb eng 330 ASE 330 ASE Ali, Tausif verfasserin aut A Multi-Criteria Decision-Making Approach to Determine the Optimal Hybrid Energy System in Coastal Off-Grid Areas: A Case Study of Bangladesh 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The coastal areas of Bangladesh have a number of off-grid locations, which are out of national grid coverage. Therefore, off-grid technology is the only solution to electrify those areas. At present, solar home system (SHS) is playing pivotal role to fulfil the electricity demand and, also, contributing to the community both economically and socially. However, due to the technical, economic, environmental and social maturity, hybrid energy system (HES) could be more lucrative in the off-grid areas of Bangladesh. Therefore, proper selection of the HES is highly essential. In this study, the focus is given on the coastal off-grid regions to select the optimal HES using the multi-criteria decision-making (MCDM) method. Based on the potentiality of renewable energy resources, six HES alternatives were selected for evaluation. To evaluate the HESs, thirteen criteria were selected based on experts’ agreement, and to check this agreement, content validity was estimated. In addition, criteria importance through intercriteria correlation (CRITIC) method was deployed to find the weights of the criteria. Finally, a new MCDM method named combinative distance-based assessment (CODAS) was applied to select the optimum HES. The results revealed that the PV/battery/biogas/diesel generator HES is the optimum solution for the study area. Hybrid energy system (dpeaa)DE-He213 Off-grid (dpeaa)DE-He213 MCDM (dpeaa)DE-He213 CRITIC (dpeaa)DE-He213 CODAS (dpeaa)DE-He213 Content validity (dpeaa)DE-He213 Ma, Hongzhong verfasserin aut Nahian, Ahmed Jaudat verfasserin aut Enthalten in Process integration and optimization for sustainability [Singapore] : Springer Singapore, 2017 4(2020), 3 vom: 18. Apr., Seite 265-277 (DE-627)876318316 (DE-600)2879697-4 2509-4246 nnns volume:4 year:2020 number:3 day:18 month:04 pages:265-277 https://dx.doi.org/10.1007/s41660-020-00116-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 4 2020 3 18 04 265-277 |
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10.1007/s41660-020-00116-9 doi (DE-627)SPR040601390 (SPR)s41660-020-00116-9-e DE-627 ger DE-627 rakwb eng 330 ASE 330 ASE Ali, Tausif verfasserin aut A Multi-Criteria Decision-Making Approach to Determine the Optimal Hybrid Energy System in Coastal Off-Grid Areas: A Case Study of Bangladesh 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The coastal areas of Bangladesh have a number of off-grid locations, which are out of national grid coverage. Therefore, off-grid technology is the only solution to electrify those areas. At present, solar home system (SHS) is playing pivotal role to fulfil the electricity demand and, also, contributing to the community both economically and socially. However, due to the technical, economic, environmental and social maturity, hybrid energy system (HES) could be more lucrative in the off-grid areas of Bangladesh. Therefore, proper selection of the HES is highly essential. In this study, the focus is given on the coastal off-grid regions to select the optimal HES using the multi-criteria decision-making (MCDM) method. Based on the potentiality of renewable energy resources, six HES alternatives were selected for evaluation. To evaluate the HESs, thirteen criteria were selected based on experts’ agreement, and to check this agreement, content validity was estimated. In addition, criteria importance through intercriteria correlation (CRITIC) method was deployed to find the weights of the criteria. Finally, a new MCDM method named combinative distance-based assessment (CODAS) was applied to select the optimum HES. The results revealed that the PV/battery/biogas/diesel generator HES is the optimum solution for the study area. Hybrid energy system (dpeaa)DE-He213 Off-grid (dpeaa)DE-He213 MCDM (dpeaa)DE-He213 CRITIC (dpeaa)DE-He213 CODAS (dpeaa)DE-He213 Content validity (dpeaa)DE-He213 Ma, Hongzhong verfasserin aut Nahian, Ahmed Jaudat verfasserin aut Enthalten in Process integration and optimization for sustainability [Singapore] : Springer Singapore, 2017 4(2020), 3 vom: 18. Apr., Seite 265-277 (DE-627)876318316 (DE-600)2879697-4 2509-4246 nnns volume:4 year:2020 number:3 day:18 month:04 pages:265-277 https://dx.doi.org/10.1007/s41660-020-00116-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 4 2020 3 18 04 265-277 |
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Therefore, off-grid technology is the only solution to electrify those areas. At present, solar home system (SHS) is playing pivotal role to fulfil the electricity demand and, also, contributing to the community both economically and socially. However, due to the technical, economic, environmental and social maturity, hybrid energy system (HES) could be more lucrative in the off-grid areas of Bangladesh. Therefore, proper selection of the HES is highly essential. In this study, the focus is given on the coastal off-grid regions to select the optimal HES using the multi-criteria decision-making (MCDM) method. Based on the potentiality of renewable energy resources, six HES alternatives were selected for evaluation. To evaluate the HESs, thirteen criteria were selected based on experts’ agreement, and to check this agreement, content validity was estimated. In addition, criteria importance through intercriteria correlation (CRITIC) method was deployed to find the weights of the criteria. Finally, a new MCDM method named combinative distance-based assessment (CODAS) was applied to select the optimum HES. 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Ali, Tausif |
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Ali, Tausif ddc 330 misc Hybrid energy system misc Off-grid misc MCDM misc CRITIC misc CODAS misc Content validity A Multi-Criteria Decision-Making Approach to Determine the Optimal Hybrid Energy System in Coastal Off-Grid Areas: A Case Study of Bangladesh |
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330 ASE A Multi-Criteria Decision-Making Approach to Determine the Optimal Hybrid Energy System in Coastal Off-Grid Areas: A Case Study of Bangladesh Hybrid energy system (dpeaa)DE-He213 Off-grid (dpeaa)DE-He213 MCDM (dpeaa)DE-He213 CRITIC (dpeaa)DE-He213 CODAS (dpeaa)DE-He213 Content validity (dpeaa)DE-He213 |
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A Multi-Criteria Decision-Making Approach to Determine the Optimal Hybrid Energy System in Coastal Off-Grid Areas: A Case Study of Bangladesh |
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multi-criteria decision-making approach to determine the optimal hybrid energy system in coastal off-grid areas: a case study of bangladesh |
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A Multi-Criteria Decision-Making Approach to Determine the Optimal Hybrid Energy System in Coastal Off-Grid Areas: A Case Study of Bangladesh |
abstract |
Abstract The coastal areas of Bangladesh have a number of off-grid locations, which are out of national grid coverage. Therefore, off-grid technology is the only solution to electrify those areas. At present, solar home system (SHS) is playing pivotal role to fulfil the electricity demand and, also, contributing to the community both economically and socially. However, due to the technical, economic, environmental and social maturity, hybrid energy system (HES) could be more lucrative in the off-grid areas of Bangladesh. Therefore, proper selection of the HES is highly essential. In this study, the focus is given on the coastal off-grid regions to select the optimal HES using the multi-criteria decision-making (MCDM) method. Based on the potentiality of renewable energy resources, six HES alternatives were selected for evaluation. To evaluate the HESs, thirteen criteria were selected based on experts’ agreement, and to check this agreement, content validity was estimated. In addition, criteria importance through intercriteria correlation (CRITIC) method was deployed to find the weights of the criteria. Finally, a new MCDM method named combinative distance-based assessment (CODAS) was applied to select the optimum HES. The results revealed that the PV/battery/biogas/diesel generator HES is the optimum solution for the study area. |
abstractGer |
Abstract The coastal areas of Bangladesh have a number of off-grid locations, which are out of national grid coverage. Therefore, off-grid technology is the only solution to electrify those areas. At present, solar home system (SHS) is playing pivotal role to fulfil the electricity demand and, also, contributing to the community both economically and socially. However, due to the technical, economic, environmental and social maturity, hybrid energy system (HES) could be more lucrative in the off-grid areas of Bangladesh. Therefore, proper selection of the HES is highly essential. In this study, the focus is given on the coastal off-grid regions to select the optimal HES using the multi-criteria decision-making (MCDM) method. Based on the potentiality of renewable energy resources, six HES alternatives were selected for evaluation. To evaluate the HESs, thirteen criteria were selected based on experts’ agreement, and to check this agreement, content validity was estimated. In addition, criteria importance through intercriteria correlation (CRITIC) method was deployed to find the weights of the criteria. Finally, a new MCDM method named combinative distance-based assessment (CODAS) was applied to select the optimum HES. The results revealed that the PV/battery/biogas/diesel generator HES is the optimum solution for the study area. |
abstract_unstemmed |
Abstract The coastal areas of Bangladesh have a number of off-grid locations, which are out of national grid coverage. Therefore, off-grid technology is the only solution to electrify those areas. At present, solar home system (SHS) is playing pivotal role to fulfil the electricity demand and, also, contributing to the community both economically and socially. However, due to the technical, economic, environmental and social maturity, hybrid energy system (HES) could be more lucrative in the off-grid areas of Bangladesh. Therefore, proper selection of the HES is highly essential. In this study, the focus is given on the coastal off-grid regions to select the optimal HES using the multi-criteria decision-making (MCDM) method. Based on the potentiality of renewable energy resources, six HES alternatives were selected for evaluation. To evaluate the HESs, thirteen criteria were selected based on experts’ agreement, and to check this agreement, content validity was estimated. In addition, criteria importance through intercriteria correlation (CRITIC) method was deployed to find the weights of the criteria. Finally, a new MCDM method named combinative distance-based assessment (CODAS) was applied to select the optimum HES. The results revealed that the PV/battery/biogas/diesel generator HES is the optimum solution for the study area. |
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3 |
title_short |
A Multi-Criteria Decision-Making Approach to Determine the Optimal Hybrid Energy System in Coastal Off-Grid Areas: A Case Study of Bangladesh |
url |
https://dx.doi.org/10.1007/s41660-020-00116-9 |
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author2 |
Ma, Hongzhong Nahian, Ahmed Jaudat |
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Ma, Hongzhong Nahian, Ahmed Jaudat |
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doi_str |
10.1007/s41660-020-00116-9 |
up_date |
2024-07-03T17:03:00.383Z |
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score |
7.4012613 |