OPTIMASI TRANSMISSION EXPANSION PLANNING BERBASIS ALGORITMA GENETIKA DENGAN MEMPERTIMBANGKAN RUGI-RUGI DAYA
| Main Authors: | , Ikrima Alfi, S.T., , Sarjiya, S.T., M.T., Ph.D. |
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| Format: | Thesis NonPeerReviewed |
| Terbitan: |
[Yogyakarta] : Universitas Gadjah Mada
, 2014
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| Subjects: | |
| Online Access: |
https://repository.ugm.ac.id/128372/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=68714 |
Daftar Isi:
- Transmission Expansion Planning (TEP) is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. Its task is to minimize the network construction and operational cost, while meeting imposed technical, economic and reliability constraints. Genetic Algorithms (GAs) have demonstrated the ability to deal with non-convex, nonlinear, mixed-integer optimization problems, like the TEP problem, better than a number of mathematical methodologies. This study is divided into two scenarios, scenario 1 is simulated TEP without considering power losses and scenario 2 is simulated by considering the TEP power loss. TEP simulation is applied to the Garver 6 bus system 230 kV and 400 kV. Different value of LLmax (Line Loading maximum) included in TEP constraints is 50%, 40% and 30%. Simulation results shows the use of a voltage level of 400 kV is more economical than the 230 kV. TEP with scenario 1 has the initial investment cost is lower compared with TEP scenario 2. However, at the time of implementation, scenario 2 after the 9th year have lower operational costs. LLmax value affects the number of lines that must be added, smaller value of LLmax the more lines to be added.