Multi-Objective Optimal Power Flow Solution Using Genetic Algorithm
| dc.contributor.author | Kaur, Tanvir | |
| dc.contributor.supervisor | Nijhawan, Parag | |
| dc.date.accessioned | 2012-12-26T09:48:02Z | |
| dc.date.available | 2012-12-26T09:48:02Z | |
| dc.date.issued | 2012-12-26T09:48:02Z | |
| dc.description | M.E. (Power Systems and Electric Drives) | en |
| dc.description.abstract | The main function of Optimal Power Flow (OPF) solution is to minimize the fuel cost, losses and fuel emissions (NOx, SOx and COx) while the system is operating within its security limits. This solution can be applied on problem involving either a single objective function or multiple objective functions. Even though, excellent advancements have been made in classical methods, they suffer from disadvantages because of the extremely limited capability to solve real-world large-scale power system problems. They are weak in handling qualitative constraints. The major advantage of the GA is that it is relatively versatile for handling various qualitative constraints. It can find multiple optimal solutions in single simulation run. So they are quite suitable in solving multi-objective optimization problems. In this thesis, Genetic Algorithm (GA) based multi-objective optimal power flow (OPF) solution is obtained for the IEEE 30-bus 6-generator system. | en |
| dc.description.sponsorship | Electrical and Instrumentation Engineering Department, Thapar University, Patiala | en |
| dc.format.extent | 2015909 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/10266/2166 | |
| dc.language.iso | en | en |
| dc.subject | Multi-objective optimal power flow | en |
| dc.subject | genetic algorithm | en |
| dc.subject | weighted sum method | en |
| dc.title | Multi-Objective Optimal Power Flow Solution Using Genetic Algorithm | en |
| dc.type | Thesis | en |