An enhanced RCGA for a rapid and reliable load flow solution of electrical power systems
The paper presents a reliable and fast load flow solution by using a real-coded genetic algorithm (RCGA), bus reduction technique and sparsity technique. The proposed load flow solution firstly used reduction technique to eliminate the load buses. Then, the power flow problem is solved for the gener...
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International Journal of Electrical Power & Energy Systems
2012
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my.um.eprints.78212019-10-09T09:22:35Z http://eprints.um.edu.my/7821/ An enhanced RCGA for a rapid and reliable load flow solution of electrical power systems Kubba, H. Mokhlis, Hazlie TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering The paper presents a reliable and fast load flow solution by using a real-coded genetic algorithm (RCGA), bus reduction technique and sparsity technique. The proposed load flow solution firstly used reduction technique to eliminate the load buses. Then, the power flow problem is solved for the generator buses only using real-coded GA to calculate the phase angles. Thus, the load flow problem becomes a single objective function, where the voltage magnitudes are specified resulted in reduced computation time for the solution. Once the phase angle has been calculated, the system is restored by calculating the voltages of the load buses in terms of the calculated voltages of the generator buses. A sparsity technique is used to reduce the computation time further as well as the storage requirements. The proposed load flow solution also can efficiently solve the load flow problems for ill-conditioned power systems whereas the conventional RCGA alone fails to solve these systems. The proposed method was demonstrated on 14-bus IEEE, 30-bus IEEE and 300-bus IEEE, and a practical system 362-busbar Iraqi National Grid. The proposed solution has reliable convergence, a highly accurate solution and much less computing time for on-line applications. The method can conveniently be applied for on-line analysis and planning studies of large power systems. (C) 2012 Elsevier Ltd. All rights reserved. International Journal of Electrical Power & Energy Systems 2012 Article PeerReviewed Kubba, H. and Mokhlis, Hazlie (2012) An enhanced RCGA for a rapid and reliable load flow solution of electrical power systems. International Journal of Electrical Power & Energy Systems, 43 (1). pp. 304-312. ISSN 0142-0615 http://ac.els-cdn.com/S0142061512001615/1-s2.0-S0142061512001615-main.pdf?_tid=ff533ad4-a7d5-11e2-ba56-00000aacb35e&acdnat=1366255013_fc8e076de54262b0b44f4a5d5ae363db DOI 10.1016/j.ijepes.2012.04.034 |
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TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Kubba, H. Mokhlis, Hazlie An enhanced RCGA for a rapid and reliable load flow solution of electrical power systems |
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The paper presents a reliable and fast load flow solution by using a real-coded genetic algorithm (RCGA), bus reduction technique and sparsity technique. The proposed load flow solution firstly used reduction technique to eliminate the load buses. Then, the power flow problem is solved for the generator buses only using real-coded GA to calculate the phase angles. Thus, the load flow problem becomes a single objective function, where the voltage magnitudes are specified resulted in reduced computation time for the solution. Once the phase angle has been calculated, the system is restored by calculating the voltages of the load buses in terms of the calculated voltages of the generator buses. A sparsity technique is used to reduce the computation time further as well as the storage requirements. The proposed load flow solution also can efficiently solve the load flow problems for ill-conditioned power systems whereas the conventional RCGA alone fails to solve these systems. The proposed method was demonstrated on 14-bus IEEE, 30-bus IEEE and 300-bus IEEE, and a practical system 362-busbar Iraqi National Grid. The proposed solution has reliable convergence, a highly accurate solution and much less computing time for on-line applications. The method can conveniently be applied for on-line analysis and planning studies of large power systems. (C) 2012 Elsevier Ltd. All rights reserved. |
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Kubba, H. Mokhlis, Hazlie |
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Kubba, H. Mokhlis, Hazlie |
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Kubba, H. |
title |
An enhanced RCGA for a rapid and reliable load flow solution of electrical power systems |
title_short |
An enhanced RCGA for a rapid and reliable load flow solution of electrical power systems |
title_full |
An enhanced RCGA for a rapid and reliable load flow solution of electrical power systems |
title_fullStr |
An enhanced RCGA for a rapid and reliable load flow solution of electrical power systems |
title_full_unstemmed |
An enhanced RCGA for a rapid and reliable load flow solution of electrical power systems |
title_sort |
enhanced rcga for a rapid and reliable load flow solution of electrical power systems |
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International Journal of Electrical Power & Energy Systems |
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2012 |
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http://eprints.um.edu.my/7821/ http://ac.els-cdn.com/S0142061512001615/1-s2.0-S0142061512001615-main.pdf?_tid=ff533ad4-a7d5-11e2-ba56-00000aacb35e&acdnat=1366255013_fc8e076de54262b0b44f4a5d5ae363db |
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1648736078787510272 |
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13.160551 |