ANALISIS OPTIMAL POWER FLOW MENGGUNAKAN ALGORITMA GENETIKA DENGAN MEMPERTIMBANGKAN SECURITY CONSTRAINTS
Power system demands require power system operation to distribute generated electric power. The purpose of power system operation is distributed electric power with high reliability with minimum amount of total generation cost, without violated security constraints such as voltage and generation. Op...
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| Format: | Thesis |
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[Yogyakarta] : Universitas Gadjah Mada
2013
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| _version_ | 1826047306448764928 |
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| author | , MUHAMMAD RIDWAN , Sarjiya, S.T., M.T., Ph.D |
| author_facet | , MUHAMMAD RIDWAN , Sarjiya, S.T., M.T., Ph.D |
| author_sort | , MUHAMMAD RIDWAN |
| collection | UGM |
| description | Power system demands require power system operation to distribute generated electric power. The purpose of power system operation is distributed electric power with high reliability with minimum amount of total generation cost, without violated security constraints such as voltage and generation. Optimal power flow is the solution of that problem to determine optimal control with respect to various constraints. Nowdays optimal power flow continues to expand with algorithms that divided into conventional and heuristic methods. One of the heuristic methods is genetic algorithm that used in this research to find total cost minimization of power system operation. Genetic algorithm method combined with newton raphson power flow used for calculating optimal power flow. Design of experiment is used to determine values of genetic variables.Those metods is used to find total cost minimization in study case of case 6 and case ieee 30 buses. After that, voltage constraint is given in the system and tested in generator contingency conditions. Results of total cost minimization in that study case are shown and compared with conventional method used to the same objective. Proposed of this research is using genetic algorithm method to find total cost minimization of optimal power flow simulation. This research shows that total generaation cost calculated with genetic method is cheaper 0.43% than Matlab Interior Point Solution, in normal and contingency condition. In addition, the use of genetic method also gives better convergence in contingency condition. |
| first_indexed | 2024-03-13T23:08:21Z |
| format | Thesis |
| id | oai:generic.eprints.org:124840 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T23:08:21Z |
| publishDate | 2013 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1248402016-03-04T08:40:35Z https://repository.ugm.ac.id/124840/ ANALISIS OPTIMAL POWER FLOW MENGGUNAKAN ALGORITMA GENETIKA DENGAN MEMPERTIMBANGKAN SECURITY CONSTRAINTS , MUHAMMAD RIDWAN , Sarjiya, S.T., M.T., Ph.D ETD Power system demands require power system operation to distribute generated electric power. The purpose of power system operation is distributed electric power with high reliability with minimum amount of total generation cost, without violated security constraints such as voltage and generation. Optimal power flow is the solution of that problem to determine optimal control with respect to various constraints. Nowdays optimal power flow continues to expand with algorithms that divided into conventional and heuristic methods. One of the heuristic methods is genetic algorithm that used in this research to find total cost minimization of power system operation. Genetic algorithm method combined with newton raphson power flow used for calculating optimal power flow. Design of experiment is used to determine values of genetic variables.Those metods is used to find total cost minimization in study case of case 6 and case ieee 30 buses. After that, voltage constraint is given in the system and tested in generator contingency conditions. Results of total cost minimization in that study case are shown and compared with conventional method used to the same objective. Proposed of this research is using genetic algorithm method to find total cost minimization of optimal power flow simulation. This research shows that total generaation cost calculated with genetic method is cheaper 0.43% than Matlab Interior Point Solution, in normal and contingency condition. In addition, the use of genetic method also gives better convergence in contingency condition. [Yogyakarta] : Universitas Gadjah Mada 2013 Thesis NonPeerReviewed , MUHAMMAD RIDWAN and , Sarjiya, S.T., M.T., Ph.D (2013) ANALISIS OPTIMAL POWER FLOW MENGGUNAKAN ALGORITMA GENETIKA DENGAN MEMPERTIMBANGKAN SECURITY CONSTRAINTS. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=65000 |
| spellingShingle | ETD , MUHAMMAD RIDWAN , Sarjiya, S.T., M.T., Ph.D ANALISIS OPTIMAL POWER FLOW MENGGUNAKAN ALGORITMA GENETIKA DENGAN MEMPERTIMBANGKAN SECURITY CONSTRAINTS |
| title | ANALISIS OPTIMAL POWER FLOW MENGGUNAKAN ALGORITMA GENETIKA DENGAN MEMPERTIMBANGKAN SECURITY CONSTRAINTS |
| title_full | ANALISIS OPTIMAL POWER FLOW MENGGUNAKAN ALGORITMA GENETIKA DENGAN MEMPERTIMBANGKAN SECURITY CONSTRAINTS |
| title_fullStr | ANALISIS OPTIMAL POWER FLOW MENGGUNAKAN ALGORITMA GENETIKA DENGAN MEMPERTIMBANGKAN SECURITY CONSTRAINTS |
| title_full_unstemmed | ANALISIS OPTIMAL POWER FLOW MENGGUNAKAN ALGORITMA GENETIKA DENGAN MEMPERTIMBANGKAN SECURITY CONSTRAINTS |
| title_short | ANALISIS OPTIMAL POWER FLOW MENGGUNAKAN ALGORITMA GENETIKA DENGAN MEMPERTIMBANGKAN SECURITY CONSTRAINTS |
| title_sort | analisis optimal power flow menggunakan algoritma genetika dengan mempertimbangkan security constraints |
| topic | ETD |
| work_keys_str_mv | AT muhammadridwan analisisoptimalpowerflowmenggunakanalgoritmagenetikadenganmempertimbangkansecurityconstraints AT sarjiyastmtphd analisisoptimalpowerflowmenggunakanalgoritmagenetikadenganmempertimbangkansecurityconstraints |