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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jalilzadeh, S. Kazemi, A. Mahdavi, M. Haddadian, H. |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Electr. Eng., Zanjan Univ., Zanjan (Jalilzadeh, S.) |
| Abstract | Up to now, various methods have been presented for solution of the static transmission network expansion planning (STNEP) problem. However, in all of these methods, STNEP problem has been solved regardless to voltage level of transmission lines and role of voltage level in reducing annual losses of the network. In this paper, STNEP has been studied considering voltage level, network losses and number of bundle lines (which cause different network annual losses) using decimal codification based genetic algorithm (DCGA). Genetic Algorithms (GAs) have demonstrated the ability to deal with non-convex, nonlinear, integer-mixed optimization problems, like the TNEP problem, better than a number of mathematical methodologies. The proposed method is tested on an actual transmission network of the Azerbaijan regional electric company, Iran to illustrate its robust performance. The results show that considering the network losses in a power system with different voltage levels, decreases the operational costs considerably and the network satisfies the requirement of delivering electric power more safely and reliably to load centers. |
| Starting Page | 1580 |
| Ending Page | 1585 |
| File Size | 471437 |
| Page Count | 6 |
| File Format | |
| ISBN | 9787900714138 |
| DOI | 10.1109/DRPT.2008.4523657 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-04-06 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | DRPT |
| Subject Keyword | Voltage Propagation losses Power system reliability Cost function Genetic algorithms Power system planning Power transmission lines Substations Testing Power generation economics GA TNEP etwork Losses undle Lines |
| Content Type | Text |
| Resource Type | Article |
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