OPTIMAL PLACEMENT OF DISTRIBUTED GENERATION (DG) UNITS IN POWER SYSTEM USING REPEATED LOAD FLOW ANALYSIS METHOD
Abstract
In this paper, Repeated Load Flow Analysis method has been used to determine the optimal placement of Distributed Generation (DG) units in power system. A test network - 73-bus Port Harcourt 33 kV Power distribution system has been simulated in Electrical Transient Analyzer program (ETAP 12.6) software using Newton Raphson (N-R) load flow method. The optimal placement of the DGs is selected at the candidate load buses where voltage profile rises to acceptable limit through load flow repeated simulation. The result obtained identified the following buses: 16, 31, 37, 53, 57, 58, 59, 67, and 69 and as optimal DG placement. The result obtained after DG placement reveals acceptable voltage levels at the problem buses and the entire network
Keywords:
Distributed Generation, Distribution System, Newton Raphson (N-R), Load Flow MethodDownloads
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https://doi.org/10.5281/zenodo.8367108Issue
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References
Amanifar, O., & Hamedani, M.E. (2011). Optimal distributed generation placement and sizing for loss and THD reduction and voltage profile improvement in distribution systems using particle swarm optimization and sensitivity analysis. International Journal on Technical and Physical Problems of Engineering, 3(7), 47-53.
Ayodele, T.R., Ogunjuyibe, A.S.O., & Akinola, O.O. (2015). Optimal location, sizing, and appropriate technology selection of distributed generators for minimizing power loss using Genetic Algorithm. Journal of Renewable Energy. http://dx.doi.org/10.1155/2015/832917
Basudev, D., & Bimal, C.D. (2013). Impact of distributed generation on reliability of the distribution System. Journal of Electrical and Electronics Engineering, 8(1), 42-50.
Borges, C.L.T., & Falcao, D.M. (2006). Optimal distributed generation allocation for reliability, losses, and voltage improvement. International Journal of Electrical Power Energy System, 28(6), 413-420.
Caisheng, W., & Hashem, N. (2004). Analytical approaches for optimal placement of distributed generator sources in power systems. IEEE Transactions on Power Systems, 19(4), 2068-2076.
Chizindu Stanley Esobinenwu (2021). Impact of Distributed Generation in Power System using Particle Swarm Optimization. International Journal of Innovative Scientific & Engineering Technologies Research, 9(1), 20-25.
Chizindu Stanley Esobinenwu and J.P. Iloh (2019). Optimal Placement of Distributed Generation in Power System using Particle Swarm Optimization. Global Scientific Journals, 7(11), 1513–1522.
Chizindu Stanley Esobinenwu, A.J. Atuchukwu, and J.P. Iloh (2019). Sensitivity Analysis for Optimal Distributed Generation Placement in Port Harcourt 33kV Power Distribution System. International Research Journal of Engineering and Technology (IRJET), 6(11), 1710-1721.
Chizindu Stanley Esobinenwu, S.O.E. Ogbogu, and J.P. Iloh (2019). Evaluation of the Voltage Profile of Port Harcourt 33kV Power Distribution System. American Journal of Engineering Research (AJER), 8(11), 20-33.
Funso, K.A., & Michael, O.O. (2013). Investigation of Nigerian 330KV Electrical Network with Distributed Generation- Part 1: Basic Analysis. Electrical and Electronic Engineering, 3(2), 49-71.
Georgilakis, P.S., & Hatziargyriou, N.D. (2013). Optimal distributed generation placement in power distribution networks: models, methods, and future research. IEEE Transactions on Power Systems, 28(3), 3420–3428.
Greatbank, J.A., Popovic, D.H., Begovic, M., Pregelji, A., & Green, T.C. (2003). Optimization for security and reliability of power systems with distributed generation.
Hasibuan, A., Masri, S., & Othman, W. (2018). Effect of distributed generation installation on power loss using genetic algorithm method. IOP Conference Series: Materials Science and Engineering. https://doi.org/10.1088/1757-899x/308/1/012034
Julius, K.C., & Nicodemus, A.O. (2013). A GA/IPSO based approach for system loss reduction and voltage profile improvement employing arithmetic crossover and mutation. International Journal of Engineering Science and Technology, 5(7), 1501-1510.
Kashem, M.A., Negnevitsk, M., & Ledwich, G. (2007). Optimal distributed generation parameters for reducing losses with economic consideration, 2007 IEEE Power Engineering Society General Meeting. https://doi.org/10.1109/pes.2007.386058
Mario, S., Zvonimir, K.F., & Marinko, S. (2018). Review of non-traditional optimization methods for allocation of distributed generation and energy storage in distribution system, Technical Gazette, 25(1), 294-301.
Mournika, L.P., Amit, J., & James, R.K. (2017). Particle swarm optimization application for optimal location of multiple distributed generators in power distribution network. Journal of Electrical and Electronic Systems, 6(4), 244- 248.
Nweke, J.N., Ekwue, A.O., & Ejiogu, E.C. (2016). Optimal location of distributed generation on the Nigerian power system. Nigerian Journal of Technology, 35(2), 398-403.
Pathak, S., & Vaidya, B.N. (2012). Optimal power flow by particle swarm optimization for reactive loss minimization. International Journal of Scientific and Technology Research, 1(1), 1-6.
Poulami, D., Sudip, K.N., Sourav, S, & Sankar, N.P. (2016). An approach to optimize FIR filter coefficients using the GA, PSO, and BAT algorithm and their comparative analysis. https://doi.org/10.1109/iccece.2016.8009579
