Advanced predicting technique for optimal operation of wastewater treatment process: A ProActive scheduling approach
Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance wa...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Nawaz, Alam [verfasserIn] |
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E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021transfer 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:303 ; year:2021 ; day:20 ; month:06 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.jclepro.2021.126968 |
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| 520 | |a Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. | ||
| 520 | |a Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. | ||
| 650 | 7 | |a ProActive scheduling |2 Elsevier | |
| 650 | 7 | |a Sequence sets |2 Elsevier | |
| 650 | 7 | |a Processing-unit time |2 Elsevier | |
| 650 | 7 | |a Wastewater |2 Elsevier | |
| 700 | 1 | |a Arora, Amarpreet Singh |4 oth | |
| 700 | 1 | |a Yun, Dahee |4 oth | |
| 700 | 1 | |a Yun, Choa Mun |4 oth | |
| 700 | 1 | |a Lee, Moonyong |4 oth | |
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10.1016/j.jclepro.2021.126968 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001473.pica (DE-627)ELV054057531 (ELSEVIER)S0959-6526(21)01187-2 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Nawaz, Alam verfasserin aut Advanced predicting technique for optimal operation of wastewater treatment process: A ProActive scheduling approach 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. ProActive scheduling Elsevier Sequence sets Elsevier Processing-unit time Elsevier Wastewater Elsevier Arora, Amarpreet Singh oth Yun, Dahee oth Yun, Choa Mun oth Lee, Moonyong oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:303 year:2021 day:20 month:06 pages:0 https://doi.org/10.1016/j.jclepro.2021.126968 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 303 2021 20 0620 0 |
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10.1016/j.jclepro.2021.126968 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001473.pica (DE-627)ELV054057531 (ELSEVIER)S0959-6526(21)01187-2 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Nawaz, Alam verfasserin aut Advanced predicting technique for optimal operation of wastewater treatment process: A ProActive scheduling approach 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. ProActive scheduling Elsevier Sequence sets Elsevier Processing-unit time Elsevier Wastewater Elsevier Arora, Amarpreet Singh oth Yun, Dahee oth Yun, Choa Mun oth Lee, Moonyong oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:303 year:2021 day:20 month:06 pages:0 https://doi.org/10.1016/j.jclepro.2021.126968 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 303 2021 20 0620 0 |
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10.1016/j.jclepro.2021.126968 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001473.pica (DE-627)ELV054057531 (ELSEVIER)S0959-6526(21)01187-2 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Nawaz, Alam verfasserin aut Advanced predicting technique for optimal operation of wastewater treatment process: A ProActive scheduling approach 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. ProActive scheduling Elsevier Sequence sets Elsevier Processing-unit time Elsevier Wastewater Elsevier Arora, Amarpreet Singh oth Yun, Dahee oth Yun, Choa Mun oth Lee, Moonyong oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:303 year:2021 day:20 month:06 pages:0 https://doi.org/10.1016/j.jclepro.2021.126968 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 303 2021 20 0620 0 |
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10.1016/j.jclepro.2021.126968 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001473.pica (DE-627)ELV054057531 (ELSEVIER)S0959-6526(21)01187-2 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Nawaz, Alam verfasserin aut Advanced predicting technique for optimal operation of wastewater treatment process: A ProActive scheduling approach 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. ProActive scheduling Elsevier Sequence sets Elsevier Processing-unit time Elsevier Wastewater Elsevier Arora, Amarpreet Singh oth Yun, Dahee oth Yun, Choa Mun oth Lee, Moonyong oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:303 year:2021 day:20 month:06 pages:0 https://doi.org/10.1016/j.jclepro.2021.126968 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 303 2021 20 0620 0 |
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10.1016/j.jclepro.2021.126968 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001473.pica (DE-627)ELV054057531 (ELSEVIER)S0959-6526(21)01187-2 DE-627 ger DE-627 rakwb eng 540 VZ 35.18 bkl Nawaz, Alam verfasserin aut Advanced predicting technique for optimal operation of wastewater treatment process: A ProActive scheduling approach 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. ProActive scheduling Elsevier Sequence sets Elsevier Processing-unit time Elsevier Wastewater Elsevier Arora, Amarpreet Singh oth Yun, Dahee oth Yun, Choa Mun oth Lee, Moonyong oth Enthalten in Elsevier Science Rajendiran, Rajmohan ELSEVIER Self-assembled 3D hierarchical MnCO 2020 Amsterdam [u.a.] (DE-627)ELV003750353 volume:303 year:2021 day:20 month:06 pages:0 https://doi.org/10.1016/j.jclepro.2021.126968 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 35.18 Kolloidchemie Grenzflächenchemie VZ AR 303 2021 20 0620 0 |
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Advanced predicting technique for optimal operation of wastewater treatment process: A ProActive scheduling approach |
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Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. |
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Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. |
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Anaerobic ammonium oxidation (ANAMMOX) is regarded as a promising biological nitrogen removal (BNR) process in the wastewater treatment field. It is very challenging to control the highly variable parameters along with uncertain processing time and incorporate them into a single system to enhance water quality under cost-effective manner. To address this problem, this study proposes an innovative scheduling model that generates an optimal sequence based on essential processing time (for filling, anoxic, aerobic, settling, and draining processes), using the mixed-integer nonlinear programming methodology, coded in the MATLAB® R2018a framework. A key point of this methodology is that the optimal schedules (predicted as a set of points) saves 16% of energy consumption, contributes to a 24% cost reduction, and aids in lowering greenhouse gas emissions by 69% compared to the conventional nitrification/denitrification process. Rescheduling can be performed by evaluating the processing parameters without further modification of the optimum control parameters. The proposed scheduling model contributes to the development of the ProActive scheduling system, which provides optimal operating conditions for reducing the cost of wastewater processing, in line with sustainable development objectives. |
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