Optimisasi Economic Dispatch dengan Transmission Loss Menggunakan Metode Extended Lagrange Multiplier dan Gaussian Particle Swarm Optimization (Gpso)

Authors

  • Siti Komsiyah Bina Nusantara University

DOI:

https://doi.org/10.21512/comtech.v5i1.2620

Keywords:

economic dispatch, optimization, GPSO, Extended Lagrange Multiplier

Abstract

In the operating process of electrical energy, economic planning is the main goal to be achieved. The goal of economic dispatch problem is determining the combination of optimal power distribution to a number of operating generator units so that the electricity demand in a certain area is fulfilled without ignoring the constraints that exist, so it is obtained a minimum total generation cost. Optimization method that is used is the Gaussian Particle Swarm Optimization (GPSO), while for the validation of the results, the obtained solution with the GPSO will be compared with the solution obtained by mathematical methods Extended Lagrange Multiplier (ELM) or the Lagrange multiplier method which its functions are expanded. The solution that is calculated is generation output in Megawatt of 23 thermal generating units system in Mahakam, East Kalimantan, which had a total cost of optimal generating (minimum).
Dimensions

Plum Analytics

References

Aziz, A.M.A., Musirin, J.I., Rahman, T.K.A. (2006). Solving Economic Dispatch using Evolutionary Programming. First International Power and Energy Conference PECon, Putra Jaya, Malaysia, 144-149.

Bahtiar. (2008). Optimisasi Operasi Pembangkit Sistem Mahakam PT PLN (persero) wilayah Kalimantan Timur menggunakan Breeder Genetic Algorithm (BGA). Tesis, Institut Teknologi Sepuluh Nopember Surabaya, Surabaya.

Dieu, V.N., Ongsakul, W. (2007) Augmented Lagrange Hopfield Network for Large Scale Economic Dispatch. International Symposium on Electrical and Electronics Engineering, HCM City, Vietnam, 2: 19-26.

Kirschen, D. S. (2004). Fundamentals of Power System Economic. Hardback.

Komsiyah, S. (2009). Aplikasi Metode Gaussian Particle Swarm Optimization dan Lagrange Multiplier Pada Masalah Economic Dispatch. Thesis Institut Teknologi Sepuluh Nopember Surabaya.

Laoufi, A., Hazzab, A., Rahli, M. (2006). Economic Power Dispatch Using Fuzzy-Genetic Algorithm, International Jourrnal of Applied Engineering Research, 1(3): 409-426.

Marsudi, D. (2006). Operasi Sistem Tenaga Listrik, edisi pertama, Yogyakarta: Penerbit Graha Ilmu.

Ongsakul, W., Dechanupaprittha, S., Ngamroo, I. (2004). Parallel tabu search algorithm for constrained economic dispatch. IEE Proceeding of Generation, Transmission and Distribution, 151:157-166.

Panigrahi, B.K., Pandi, V.R., Das, S. (2008). Adaptive Particle Swarm Optimization approach for static and dynamic economic load dispatch. Journal of Energy Conversion and Management, 49: 1407-1415.

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Published

2014-06-30

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