Optimal Coordination of Directional Overcurrent Relays Using Biogeography-Based Optimization Algorithms
Optimal coordination of directional overcurrent relays (DOCRs) is a highly constrained and nonlinear optimization problem. The operating time of each relay depends on two independent variables called plug setting and time multiplier setting. As the network becomes larger and more complex, the number...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Albasri, Fadhel A [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Schlagwörter: |
population-based evolutionary algorithm biogeography-based optimization algorithms directional overcurrent relays constraint-handling techniques |
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| Übergeordnetes Werk: |
Enthalten in: IEEE transactions on power delivery - New York, NY : IEEE, 1986, 30(2015), 4, Seite 1810-1820 |
|---|---|
| Übergeordnetes Werk: |
volume:30 ; year:2015 ; number:4 ; pages:1810-1820 |
| Links: |
|---|
| DOI / URN: |
10.1109/TPWRD.2015.2406114 |
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| Katalog-ID: |
OLC1957848715 |
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| 520 | |a Optimal coordination of directional overcurrent relays (DOCRs) is a highly constrained and nonlinear optimization problem. The operating time of each relay depends on two independent variables called plug setting and time multiplier setting. As the network becomes larger and more complex, the number of relays will increase and, thus, finding the optimal solution becomes very hard. In this paper, a new population-based evolutionary algorithm called biogeography-based optimization (BBO) is proposed and the performance of ten types of constraint-handling techniques is evaluated. In addition, a new hybrid BBO with linear programming (BBO-LP) is proposed to enhance the performance of the conventional BBO algorithm. The performance of the proposed BBO-based algorithms is evaluated by using five test systems. The results show the effectiveness and superiority of the proposed algorithms compared with the performance of the other optimization methods presented in the literature. | ||
| 650 | 4 | |a population-based evolutionary algorithm | |
| 650 | 4 | |a Silicon | |
| 650 | 4 | |a relay protection | |
| 650 | 4 | |a biogeography-based optimization algorithms | |
| 650 | 4 | |a penalty functions | |
| 650 | 4 | |a linear programming | |
| 650 | 4 | |a Relays | |
| 650 | 4 | |a directional overcurrent relay | |
| 650 | 4 | |a directional overcurrent relays | |
| 650 | 4 | |a hybrid BBO | |
| 650 | 4 | |a evolutionary algorithms | |
| 650 | 4 | |a optimal coordination | |
| 650 | 4 | |a Convergence | |
| 650 | 4 | |a evolutionary computation | |
| 650 | 4 | |a constraint handling | |
| 650 | 4 | |a constraint-handling techniques | |
| 650 | 4 | |a Fault currents | |
| 650 | 4 | |a Biogeography-based optimization (BBO) | |
| 650 | 4 | |a Optimization | |
| 650 | 4 | |a overcurrent protection | |
| 700 | 1 | |a Alroomi, Ali R |4 oth | |
| 700 | 1 | |a Talaq, Jawad H |4 oth | |
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10.1109/TPWRD.2015.2406114 doi PQ20160617 (DE-627)OLC1957848715 (DE-599)GBVOLC1957848715 (PRQ)c1329-6be85701aab63c9f92134314eaa7a8edb9d3a67a6815f37eb46d421db6abf95c0 (KEY)0163644820150000030000401810optimalcoordinationofdirectionalovercurrentrelaysu DE-627 ger DE-627 rakwb eng 620 DNB Albasri, Fadhel A verfasserin aut Optimal Coordination of Directional Overcurrent Relays Using Biogeography-Based Optimization Algorithms 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Optimal coordination of directional overcurrent relays (DOCRs) is a highly constrained and nonlinear optimization problem. The operating time of each relay depends on two independent variables called plug setting and time multiplier setting. As the network becomes larger and more complex, the number of relays will increase and, thus, finding the optimal solution becomes very hard. In this paper, a new population-based evolutionary algorithm called biogeography-based optimization (BBO) is proposed and the performance of ten types of constraint-handling techniques is evaluated. In addition, a new hybrid BBO with linear programming (BBO-LP) is proposed to enhance the performance of the conventional BBO algorithm. The performance of the proposed BBO-based algorithms is evaluated by using five test systems. The results show the effectiveness and superiority of the proposed algorithms compared with the performance of the other optimization methods presented in the literature. population-based evolutionary algorithm Silicon relay protection biogeography-based optimization algorithms penalty functions linear programming Relays directional overcurrent relay directional overcurrent relays hybrid BBO evolutionary algorithms optimal coordination Convergence evolutionary computation constraint handling constraint-handling techniques Fault currents Biogeography-based optimization (BBO) Optimization overcurrent protection Alroomi, Ali R oth Talaq, Jawad H oth Enthalten in IEEE transactions on power delivery New York, NY : IEEE, 1986 30(2015), 4, Seite 1810-1820 (DE-627)129382914 (DE-600)165807-4 (DE-576)014769328 0885-8977 nnns volume:30 year:2015 number:4 pages:1810-1820 http://dx.doi.org/10.1109/TPWRD.2015.2406114 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7047892 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_30 GBV_ILN_70 GBV_ILN_2014 GBV_ILN_2016 GBV_ILN_2061 AR 30 2015 4 1810-1820 |
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10.1109/TPWRD.2015.2406114 doi PQ20160617 (DE-627)OLC1957848715 (DE-599)GBVOLC1957848715 (PRQ)c1329-6be85701aab63c9f92134314eaa7a8edb9d3a67a6815f37eb46d421db6abf95c0 (KEY)0163644820150000030000401810optimalcoordinationofdirectionalovercurrentrelaysu DE-627 ger DE-627 rakwb eng 620 DNB Albasri, Fadhel A verfasserin aut Optimal Coordination of Directional Overcurrent Relays Using Biogeography-Based Optimization Algorithms 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Optimal coordination of directional overcurrent relays (DOCRs) is a highly constrained and nonlinear optimization problem. The operating time of each relay depends on two independent variables called plug setting and time multiplier setting. As the network becomes larger and more complex, the number of relays will increase and, thus, finding the optimal solution becomes very hard. In this paper, a new population-based evolutionary algorithm called biogeography-based optimization (BBO) is proposed and the performance of ten types of constraint-handling techniques is evaluated. In addition, a new hybrid BBO with linear programming (BBO-LP) is proposed to enhance the performance of the conventional BBO algorithm. The performance of the proposed BBO-based algorithms is evaluated by using five test systems. The results show the effectiveness and superiority of the proposed algorithms compared with the performance of the other optimization methods presented in the literature. population-based evolutionary algorithm Silicon relay protection biogeography-based optimization algorithms penalty functions linear programming Relays directional overcurrent relay directional overcurrent relays hybrid BBO evolutionary algorithms optimal coordination Convergence evolutionary computation constraint handling constraint-handling techniques Fault currents Biogeography-based optimization (BBO) Optimization overcurrent protection Alroomi, Ali R oth Talaq, Jawad H oth Enthalten in IEEE transactions on power delivery New York, NY : IEEE, 1986 30(2015), 4, Seite 1810-1820 (DE-627)129382914 (DE-600)165807-4 (DE-576)014769328 0885-8977 nnns volume:30 year:2015 number:4 pages:1810-1820 http://dx.doi.org/10.1109/TPWRD.2015.2406114 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7047892 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_30 GBV_ILN_70 GBV_ILN_2014 GBV_ILN_2016 GBV_ILN_2061 AR 30 2015 4 1810-1820 |
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10.1109/TPWRD.2015.2406114 doi PQ20160617 (DE-627)OLC1957848715 (DE-599)GBVOLC1957848715 (PRQ)c1329-6be85701aab63c9f92134314eaa7a8edb9d3a67a6815f37eb46d421db6abf95c0 (KEY)0163644820150000030000401810optimalcoordinationofdirectionalovercurrentrelaysu DE-627 ger DE-627 rakwb eng 620 DNB Albasri, Fadhel A verfasserin aut Optimal Coordination of Directional Overcurrent Relays Using Biogeography-Based Optimization Algorithms 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Optimal coordination of directional overcurrent relays (DOCRs) is a highly constrained and nonlinear optimization problem. The operating time of each relay depends on two independent variables called plug setting and time multiplier setting. As the network becomes larger and more complex, the number of relays will increase and, thus, finding the optimal solution becomes very hard. In this paper, a new population-based evolutionary algorithm called biogeography-based optimization (BBO) is proposed and the performance of ten types of constraint-handling techniques is evaluated. In addition, a new hybrid BBO with linear programming (BBO-LP) is proposed to enhance the performance of the conventional BBO algorithm. The performance of the proposed BBO-based algorithms is evaluated by using five test systems. The results show the effectiveness and superiority of the proposed algorithms compared with the performance of the other optimization methods presented in the literature. population-based evolutionary algorithm Silicon relay protection biogeography-based optimization algorithms penalty functions linear programming Relays directional overcurrent relay directional overcurrent relays hybrid BBO evolutionary algorithms optimal coordination Convergence evolutionary computation constraint handling constraint-handling techniques Fault currents Biogeography-based optimization (BBO) Optimization overcurrent protection Alroomi, Ali R oth Talaq, Jawad H oth Enthalten in IEEE transactions on power delivery New York, NY : IEEE, 1986 30(2015), 4, Seite 1810-1820 (DE-627)129382914 (DE-600)165807-4 (DE-576)014769328 0885-8977 nnns volume:30 year:2015 number:4 pages:1810-1820 http://dx.doi.org/10.1109/TPWRD.2015.2406114 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7047892 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_30 GBV_ILN_70 GBV_ILN_2014 GBV_ILN_2016 GBV_ILN_2061 AR 30 2015 4 1810-1820 |
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10.1109/TPWRD.2015.2406114 doi PQ20160617 (DE-627)OLC1957848715 (DE-599)GBVOLC1957848715 (PRQ)c1329-6be85701aab63c9f92134314eaa7a8edb9d3a67a6815f37eb46d421db6abf95c0 (KEY)0163644820150000030000401810optimalcoordinationofdirectionalovercurrentrelaysu DE-627 ger DE-627 rakwb eng 620 DNB Albasri, Fadhel A verfasserin aut Optimal Coordination of Directional Overcurrent Relays Using Biogeography-Based Optimization Algorithms 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Optimal coordination of directional overcurrent relays (DOCRs) is a highly constrained and nonlinear optimization problem. The operating time of each relay depends on two independent variables called plug setting and time multiplier setting. As the network becomes larger and more complex, the number of relays will increase and, thus, finding the optimal solution becomes very hard. In this paper, a new population-based evolutionary algorithm called biogeography-based optimization (BBO) is proposed and the performance of ten types of constraint-handling techniques is evaluated. In addition, a new hybrid BBO with linear programming (BBO-LP) is proposed to enhance the performance of the conventional BBO algorithm. The performance of the proposed BBO-based algorithms is evaluated by using five test systems. The results show the effectiveness and superiority of the proposed algorithms compared with the performance of the other optimization methods presented in the literature. population-based evolutionary algorithm Silicon relay protection biogeography-based optimization algorithms penalty functions linear programming Relays directional overcurrent relay directional overcurrent relays hybrid BBO evolutionary algorithms optimal coordination Convergence evolutionary computation constraint handling constraint-handling techniques Fault currents Biogeography-based optimization (BBO) Optimization overcurrent protection Alroomi, Ali R oth Talaq, Jawad H oth Enthalten in IEEE transactions on power delivery New York, NY : IEEE, 1986 30(2015), 4, Seite 1810-1820 (DE-627)129382914 (DE-600)165807-4 (DE-576)014769328 0885-8977 nnns volume:30 year:2015 number:4 pages:1810-1820 http://dx.doi.org/10.1109/TPWRD.2015.2406114 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7047892 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_30 GBV_ILN_70 GBV_ILN_2014 GBV_ILN_2016 GBV_ILN_2061 AR 30 2015 4 1810-1820 |
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10.1109/TPWRD.2015.2406114 doi PQ20160617 (DE-627)OLC1957848715 (DE-599)GBVOLC1957848715 (PRQ)c1329-6be85701aab63c9f92134314eaa7a8edb9d3a67a6815f37eb46d421db6abf95c0 (KEY)0163644820150000030000401810optimalcoordinationofdirectionalovercurrentrelaysu DE-627 ger DE-627 rakwb eng 620 DNB Albasri, Fadhel A verfasserin aut Optimal Coordination of Directional Overcurrent Relays Using Biogeography-Based Optimization Algorithms 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Optimal coordination of directional overcurrent relays (DOCRs) is a highly constrained and nonlinear optimization problem. The operating time of each relay depends on two independent variables called plug setting and time multiplier setting. As the network becomes larger and more complex, the number of relays will increase and, thus, finding the optimal solution becomes very hard. In this paper, a new population-based evolutionary algorithm called biogeography-based optimization (BBO) is proposed and the performance of ten types of constraint-handling techniques is evaluated. In addition, a new hybrid BBO with linear programming (BBO-LP) is proposed to enhance the performance of the conventional BBO algorithm. The performance of the proposed BBO-based algorithms is evaluated by using five test systems. The results show the effectiveness and superiority of the proposed algorithms compared with the performance of the other optimization methods presented in the literature. population-based evolutionary algorithm Silicon relay protection biogeography-based optimization algorithms penalty functions linear programming Relays directional overcurrent relay directional overcurrent relays hybrid BBO evolutionary algorithms optimal coordination Convergence evolutionary computation constraint handling constraint-handling techniques Fault currents Biogeography-based optimization (BBO) Optimization overcurrent protection Alroomi, Ali R oth Talaq, Jawad H oth Enthalten in IEEE transactions on power delivery New York, NY : IEEE, 1986 30(2015), 4, Seite 1810-1820 (DE-627)129382914 (DE-600)165807-4 (DE-576)014769328 0885-8977 nnns volume:30 year:2015 number:4 pages:1810-1820 http://dx.doi.org/10.1109/TPWRD.2015.2406114 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7047892 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_30 GBV_ILN_70 GBV_ILN_2014 GBV_ILN_2016 GBV_ILN_2061 AR 30 2015 4 1810-1820 |
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Albasri, Fadhel A ddc 620 misc population-based evolutionary algorithm misc Silicon misc relay protection misc biogeography-based optimization algorithms misc penalty functions misc linear programming misc Relays misc directional overcurrent relay misc directional overcurrent relays misc hybrid BBO misc evolutionary algorithms misc optimal coordination misc Convergence misc evolutionary computation misc constraint handling misc constraint-handling techniques misc Fault currents misc Biogeography-based optimization (BBO) misc Optimization misc overcurrent protection Optimal Coordination of Directional Overcurrent Relays Using Biogeography-Based Optimization Algorithms |
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620 DNB Optimal Coordination of Directional Overcurrent Relays Using Biogeography-Based Optimization Algorithms population-based evolutionary algorithm Silicon relay protection biogeography-based optimization algorithms penalty functions linear programming Relays directional overcurrent relay directional overcurrent relays hybrid BBO evolutionary algorithms optimal coordination Convergence evolutionary computation constraint handling constraint-handling techniques Fault currents Biogeography-based optimization (BBO) Optimization overcurrent protection |
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ddc 620 misc population-based evolutionary algorithm misc Silicon misc relay protection misc biogeography-based optimization algorithms misc penalty functions misc linear programming misc Relays misc directional overcurrent relay misc directional overcurrent relays misc hybrid BBO misc evolutionary algorithms misc optimal coordination misc Convergence misc evolutionary computation misc constraint handling misc constraint-handling techniques misc Fault currents misc Biogeography-based optimization (BBO) misc Optimization misc overcurrent protection |
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Optimal Coordination of Directional Overcurrent Relays Using Biogeography-Based Optimization Algorithms |
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optimal coordination of directional overcurrent relays using biogeography-based optimization algorithms |
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Optimal Coordination of Directional Overcurrent Relays Using Biogeography-Based Optimization Algorithms |
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Optimal coordination of directional overcurrent relays (DOCRs) is a highly constrained and nonlinear optimization problem. The operating time of each relay depends on two independent variables called plug setting and time multiplier setting. As the network becomes larger and more complex, the number of relays will increase and, thus, finding the optimal solution becomes very hard. In this paper, a new population-based evolutionary algorithm called biogeography-based optimization (BBO) is proposed and the performance of ten types of constraint-handling techniques is evaluated. In addition, a new hybrid BBO with linear programming (BBO-LP) is proposed to enhance the performance of the conventional BBO algorithm. The performance of the proposed BBO-based algorithms is evaluated by using five test systems. The results show the effectiveness and superiority of the proposed algorithms compared with the performance of the other optimization methods presented in the literature. |
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Optimal coordination of directional overcurrent relays (DOCRs) is a highly constrained and nonlinear optimization problem. The operating time of each relay depends on two independent variables called plug setting and time multiplier setting. As the network becomes larger and more complex, the number of relays will increase and, thus, finding the optimal solution becomes very hard. In this paper, a new population-based evolutionary algorithm called biogeography-based optimization (BBO) is proposed and the performance of ten types of constraint-handling techniques is evaluated. In addition, a new hybrid BBO with linear programming (BBO-LP) is proposed to enhance the performance of the conventional BBO algorithm. The performance of the proposed BBO-based algorithms is evaluated by using five test systems. The results show the effectiveness and superiority of the proposed algorithms compared with the performance of the other optimization methods presented in the literature. |
| abstract_unstemmed |
Optimal coordination of directional overcurrent relays (DOCRs) is a highly constrained and nonlinear optimization problem. The operating time of each relay depends on two independent variables called plug setting and time multiplier setting. As the network becomes larger and more complex, the number of relays will increase and, thus, finding the optimal solution becomes very hard. In this paper, a new population-based evolutionary algorithm called biogeography-based optimization (BBO) is proposed and the performance of ten types of constraint-handling techniques is evaluated. In addition, a new hybrid BBO with linear programming (BBO-LP) is proposed to enhance the performance of the conventional BBO algorithm. The performance of the proposed BBO-based algorithms is evaluated by using five test systems. The results show the effectiveness and superiority of the proposed algorithms compared with the performance of the other optimization methods presented in the literature. |
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Optimal Coordination of Directional Overcurrent Relays Using Biogeography-Based Optimization Algorithms |
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