The growing gap between electric power generated and that demanded is of utmost concern especially in developing economy, hence calling for measures to argument the existing power generated of which DG is a more viable aspect to explore in curtailing this challenges; although been confronted with issue of location and sizing. This research applied Adaptive neuro fuzzy logic technique to optimize DG location and size. A 24 bus radial network was used to demonstrate this process and having a suitable location and size at optimal position reduces power losses and also improves the voltage profile at the buses. The method was simulated using ANFIS toolbox MATLAB R2013b (22.214.171.1241) 64-bit software and tested using Gwagwalada injection sub-station feeder 1 system. The results obtained were compared to that obtained using ANN. It was observed that adaptive neuro fuzzy logic technique performed better in terms of reducing power losses compared to ANN technique. The percentage reduction in the power loss at the buses cumulatively is 48.96% for ANN while adaptive neuro fuzzy logic technique is 49.21%. The voltage profile of the networks after optimizing the DG location and sizes using adaptive neuro fuzzy logic technique were also found to be much improved with the lowest bus voltage improved from 0.9284 to 1.05pu.
K. Satish, B.B.R Sai, T. Barjeev, K. Vishal, "Optimal Placement of Distributed Generation in Distribution Network," International Journal of Engineering, Science and Technology, Vol. 3, No. 3, 2011, pp. 47-55.
Power System, http://circuitglobe.com/power-system.html Accessed 15/05/2018 12:59
T.A. Short, Electric Power Distribution Handbook, Boca Raton, Florida, USA, CRC press, 2004, pp.1-33, Available https://goodboygunawan.files.wordpress.com/2010/03/electric-power-distribution-handbook.pdf
M. Mohammad, M.A. Nasab, “PSO Based Multi Objective Approach for Optimal Sizing and Placement of Distributed Generation,” Research Journal of Applied Science, Engineering and Technology, Vol. 2, No. 8, 2011, pp 832-837.
H.Z. Bhattacharya, and C.A. Canizares, “Distributed Generation: Current Status and Challenges,” IEEE Proceedings Vol. 21, No. 2, 2004, pp 157-164.
T.N. Shukla, S.P. Singh, and K.B Naik, “Allocation of Optimal Distributed Generation Using GA for Minimum System Losses in Radial Distribution Networks,” International Journal of Engineering, Science and Technology, Vol. 2, No. 3, 2010, pp 94-106.
W. Minnan, Z. Jin, “A Novel Method for Distributed Generation and Capacitor Optimal Placement Considering Voltage Profile, ISBN 978-14577-10025, IEEE, 2011. Available https://hub.hku.hk/bitstream/10722/133711/1/Content.pdf?accept=1
S. Sulaimon, Energy commission of Nigeria, The Guardian Newspapers, 5th January 2015
G. Koeppel, Distributed Generation: Literature Review and outline of the Swiss Solution, Zurich, Internal Report, November 2003.
CIGRE WG 37–23, “Impact of increasing contribution of dispersed generation on power system”, final report, September 1998.
T. Ackermann, G. Andersson, and L. Solder, "Distributed generation: a definition," Electric Power System Research, Vol.57, No.3, April 2001, pp.195-204.
A.R Wallace and G.P. Harrison, “Planning for optimal accommodation of dispersed generation in distribution networks,” Proceedings 17th International Conference on Electricity Distribution CIRED, Barcelona, Spain, May 2003, pp. 234- 254.
C.J. Dent, L.F. Ochoa and G.P. Harrison, “Network distributed generation capacity analysis using OPF with voltage step constraints,” IEEE Transactions on Power Systems, 2010, Vol. 25, No. 1, pp 296 -304.
G.P. Harrison, A. Piccolo, P. Siano and A.R. Wallace, “Hybrid GA and OPF evaluation of network capacity for distributed generation connections,” Electric Power Systems Research Vol. 78, 2008, pp. 392–398.
V.C Thierry, V. Gustavo, “Coordinated Voltage Control of Distributed Networks Hosting Dispersed Generation,” 22nd International Conference on Electricity Distribution (CIRED), Stockholm, 2014.
D. Singh, K.S. Verma, “Multiobjective optimization for DG planning with load models,” IEEE Transactions on Power Systems, Vol. 24, No.1, pp. 427-436, 2009.
R.K Singh and S.K. Goswami, “Optimum allocation of distributed generations based on nodal pricing for profit, loss reduction, and voltage improvement including voltage rise issue,” Electrical Power and Energy Systems, Vol. 32, 2010, pp. 637–644.
C.L Su, “Comparative Analysis of Voltage Control Strategies in Distributed Network with Distributed Generation,” ISBN:978-4244-4241-6/09/ IEEE, 2009.
H. Khan and M.A Choudhry, “Implementation of distributed generation (IDG) algorithm for performance enhancement of distribution feeder under extreme load growth,” Electrical Power and Energy Systems, Vol. 32, 2010, pp 985–997.
N. Acharya, P. Mahat and N. Mithulananthan, “An analytical approach for DG allocation in primary distribution network,” Electrical Power and Energy Systems, Vol. 28, 2006, pp. 669–678.
S.A Benson, J.K Ogunjuyigbe, Impact of Weather Variables on The Electricity Power Demand Forecast Using Fuzzy Logic Technique, Nigerian Journal of Technology, Vol 37, No. 2, April 2018, pp. 450-453.
This work is licensed under a Creative Commons Attribution 4.0 International License.
The names and email addresses entered in this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party.
Submission of the manuscript represents that the manuscript has not been published previously and is not considered for publication elsewhere.