Rekonfigurasi Jaringan Distribusi untuk Meminimisasi Rugi-Rugi pada Penyulang Kabut di Gardu Induk Teluk Betung Menggunakan Metode Binary Particle Swarm Optimization (BPSO)
Main Article Content
Keywords
Abstract
Distribution network reconfiguration is needed to minimize losses, especially in densely populated areas. Various reconfiguration methods and techniques have been proposed for the purpose of minimizing power losses. This paper presents a reconfiguration of the distribution network using the binary particle swarm optimization (BPSO) with a case study in Kabut feeder at the Teluk Betung substation. Reconfiguration is performed only by creating new lines without changing the number of lines. The results showed that with the planned four new lines, BPSO method can find new configuration to further minimizes losses. Active power losses resulting from the new configuration is 47.1043 kW or decreased by 1.81% of active power losses before the reconfiguration, i.e. 47.9477 kW. Voltage profile on each bus is better than those of before reconfiguration, where the minimum voltage obtained is 0.98603 per unit compared with a minimum voltage of 0.98597 per unit prior to reconfiguration. However, the selection of the best initial position of the whole of particle swarms outside loop configuration formed by new lines may cause a failure to find the best configuration.
Keywords : Reconfiguration, distribution network, loss minimization, BPSO, feeder
Abstrak—Rekonfigurasi jaringan distribusi sangat diperlukan untuk mengurangi rugi-rugi khususnya pada daerah yang berpenduduk padat. Berbagai metode dan teknik rekonfigurasi telah diusulkan untuk tujuan meminimalkan rugi-rugi daya. Makalah ini menyajikan rekonfigurasi jaringan distribusi dengan menggunakan metode binary particle swarm optimization (BPSO) dengan studi kasus penyulang Kabut di gardu induk Teluk Betung. Rekonfigurasi dilakukan hanya dengan membuat saluran baru tanpa merubah jumlah saluran. Hasil penelitian menunjukkan bahwa dengan merencanakan empat saluran baru, metode BPSO dapat menemukan konfigurasi baru yang lebih meminimalkan rugi-rugi. Rugi-rugi daya aktif yang dihasilkan dari konfigurasi baru sebesar 47,1043 kW atau berkurang sebesar 1,81% dari rugi-rugi daya aktif sebelum rekonfigurasi, yakni 47,9477 kW. Profil tegangan pada setiap bus juga lebih baik dari tegangan sebelum rekonfigurasi, dimana tegangan minimum yang diperoleh adalah sebesar 0,98603 per unit dibandingkan dengan tegangan minimum 0,98597 per unit sebelum rekonfigurasi. Namun pemilihan posisi awal terbaik dari seluruh kumpulan partikel di luar lup konfigurasi yang dibentuk oleh saluran baru dapat menyebabkan kegagalan untuk menemukan konfigurasi terbaik.
Kata Kunci : Rekonfigurasi, jaringan distribusi, minimisasi rugi-rugi, BPSO, penyulang
References
[2] Baran, M.E. and Wu, F.F.,
Network Reconfiguration in Distribution System for Loss Reduction and Load Balancing, IEEE Trans. on Power Delivery, vol.4, no.2, pp.1401-1407 (1989).
[3] Wagner, T.P., Chikhani, A.Y., and Hackam, R., Feeder Reconfiguration for Loss Reduction: An Application of Distribution Automation, IEEE Trans. on Power Delivery, vol.6, no.4, pp.1922-1933 (1991).
[4] Lin, C.H., Chen, C.S., Wu, C.J., and Kang, M.S., Application of Immune Algorithm to Optimal Switching Operation for Distribution Loss Minimisation and Loading Balance, IEE Proc. Generation, Transmission and Distribution, vol.150, no.2, pp.183-189 (2003).
[5] Salazar, H., Gallego, R., and Romero, R., Artificial Neural Networks and Clustering Techniques Applied in Reconfiguration of Distribution Systems, IEEE Trans. on Power Delivery, vol.21, no.3, pp.1735-1742 ( 2006).
[6] Ahuja, A., and Pahwa, A., Using Ant Colony Optimization for Loss Minimization in Distribution Networks, Proc. of 37th Annual North American Power Symposium, pp.470-474 (2005).
[7] Hsu, F.Y., and Tsai, M.S., A Multi-Objective Evolution Programming Method for Feeder Reconfiguration of Power Distribution System, Proc. of the 13th International Conference on Intelligent Systems Application to Power Systems, pp.55-60 (2005).
[8] Eberhart R.C. and Kennedy J., A Discrete Binary Version of the Particle Swarm Algorithm, Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, vol. 5, pp.4104-4108 (1997).
[9] Xiaoling, J., Jianguo, Z., Ying, S., Kejun, L., and Boqin, Z., Distribution Network Reconfiguration for Load Balancing Using Binary Particle Swarm Optimization, International Conference on Power System Technology (PowerCon) Volume I, pp.507-510 (2004).
[10] Wu, W.C., Tsai, M.S., and Hsu, F.Y., A New Binary Coding Particle Swarm Optimization for Feeder Reconfiguration, International Conference on Intelligent Systems Application to Power Systems (ISAP), pp.1-6 (2007).
[11] Tandon, A., and Saxena, D., Optimal Reconfiguration of Electrical Distribution Network Using Selective Particle Swarm Optimization Algorithm, International Conference on Power, Control and Embedded Systems (ICPCES), pp.1-6 (2014).
[12] PT. PLN (Persero) UPT Tanjung Karang, .Data Pengukuran Gardu dan Single Line Diagram Penyulang GI Teluk Betung, (2012).
[13] MATLAB 7.12.0.635 (R2011a) User Guide, www.mathwork.com, (2011).
[14] Zimmerman, R.D., Murillo-Sanchez, C.E. and Thomas, R.J., Matpower: Steady-State Operations, Planning and Analysis Tools for Power Systems Research and Education, IEEE Trans. on Power Systems, vol.26, no.1, pp.12-19 (2011).
Article Sidebar
Article Details
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
The authors declare that:
1. This paper has not been published in the same form elsewhere.
2. It will not be submitted anywhere else for publication prior to acceptance/rejection by this Journal.
3. A copyright permission is obtained for materials published elsewhere and which require this permission for reproduction.