Robust regional low-carbon electricity system planning with energy-water nexus under uncertainties and complex policy guidelines
This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution inform...
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Gespeichert in:
| Autor*in: |
Ji, Ling [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Self-assembled 3D hierarchical MnCO - Rajendiran, Rajmohan ELSEVIER, 2020, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:252 ; year:2020 ; day:10 ; month:04 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.jclepro.2019.119800 |
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ELV049516892 |
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| 245 | 1 | 0 | |a Robust regional low-carbon electricity system planning with energy-water nexus under uncertainties and complex policy guidelines |
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| 520 | |a This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. | ||
| 520 | |a This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. | ||
| 650 | 7 | |a Energy-water nexus |2 Elsevier | |
| 650 | 7 | |a Multi-stage programming |2 Elsevier | |
| 650 | 7 | |a Robust |2 Elsevier | |
| 650 | 7 | |a Power system planning |2 Elsevier | |
| 650 | 7 | |a Uncertainties |2 Elsevier | |
| 700 | 1 | |a Zhang, Beibei |4 oth | |
| 700 | 1 | |a Huang, Guohe |4 oth | |
| 700 | 1 | |a Cai, Yanpeng |4 oth | |
| 700 | 1 | |a Yin, Jianguang |4 oth | |
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10.1016/j.jclepro.2019.119800 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000926.pica (DE-627)ELV049516892 (ELSEVIER)S0959-6526(19)34670-0 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Ji, Ling verfasserin aut Robust regional low-carbon electricity system planning with energy-water nexus under uncertainties and complex policy guidelines 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. Energy-water nexus Elsevier Multi-stage programming Elsevier Robust Elsevier Power system planning Elsevier Uncertainties Elsevier Zhang, Beibei oth Huang, Guohe oth Cai, Yanpeng oth Yin, Jianguang oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:252 year:2020 day:10 month:04 pages:0 https://doi.org/10.1016/j.jclepro.2019.119800 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 252 2020 10 0410 0 |
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10.1016/j.jclepro.2019.119800 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000926.pica (DE-627)ELV049516892 (ELSEVIER)S0959-6526(19)34670-0 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Ji, Ling verfasserin aut Robust regional low-carbon electricity system planning with energy-water nexus under uncertainties and complex policy guidelines 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. Energy-water nexus Elsevier Multi-stage programming Elsevier Robust Elsevier Power system planning Elsevier Uncertainties Elsevier Zhang, Beibei oth Huang, Guohe oth Cai, Yanpeng oth Yin, Jianguang oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:252 year:2020 day:10 month:04 pages:0 https://doi.org/10.1016/j.jclepro.2019.119800 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 252 2020 10 0410 0 |
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10.1016/j.jclepro.2019.119800 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000926.pica (DE-627)ELV049516892 (ELSEVIER)S0959-6526(19)34670-0 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Ji, Ling verfasserin aut Robust regional low-carbon electricity system planning with energy-water nexus under uncertainties and complex policy guidelines 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. Energy-water nexus Elsevier Multi-stage programming Elsevier Robust Elsevier Power system planning Elsevier Uncertainties Elsevier Zhang, Beibei oth Huang, Guohe oth Cai, Yanpeng oth Yin, Jianguang oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:252 year:2020 day:10 month:04 pages:0 https://doi.org/10.1016/j.jclepro.2019.119800 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 252 2020 10 0410 0 |
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10.1016/j.jclepro.2019.119800 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000926.pica (DE-627)ELV049516892 (ELSEVIER)S0959-6526(19)34670-0 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Ji, Ling verfasserin aut Robust regional low-carbon electricity system planning with energy-water nexus under uncertainties and complex policy guidelines 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. Energy-water nexus Elsevier Multi-stage programming Elsevier Robust Elsevier Power system planning Elsevier Uncertainties Elsevier Zhang, Beibei oth Huang, Guohe oth Cai, Yanpeng oth Yin, Jianguang oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:252 year:2020 day:10 month:04 pages:0 https://doi.org/10.1016/j.jclepro.2019.119800 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 252 2020 10 0410 0 |
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10.1016/j.jclepro.2019.119800 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000926.pica (DE-627)ELV049516892 (ELSEVIER)S0959-6526(19)34670-0 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Ji, Ling verfasserin aut Robust regional low-carbon electricity system planning with energy-water nexus under uncertainties and complex policy guidelines 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. Energy-water nexus Elsevier Multi-stage programming Elsevier Robust Elsevier Power system planning Elsevier Uncertainties Elsevier Zhang, Beibei oth Huang, Guohe oth Cai, Yanpeng oth Yin, Jianguang oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:252 year:2020 day:10 month:04 pages:0 https://doi.org/10.1016/j.jclepro.2019.119800 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 252 2020 10 0410 0 |
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The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. 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Robust regional low-carbon electricity system planning with energy-water nexus under uncertainties and complex policy guidelines |
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This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. |
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This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. |
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This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker’s risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. |
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