Optimal Location and Sizing of Distributed Generation in Distribution Network Using Adaptive Neuro-Fuzzy Logic Technique

Evans Chinemezu Ashigwuike and Stephen Adole Benson
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Evans Chinemezu Ashigwuike: Department of Electrical and Electronic Engineering, University of Abuja, Nigeria
Stephen Adole Benson: Department of Electrical and Electronic Engineering, University of Abuja, Nigeria

European Journal of Engineering and Technology Research, 2019, vol. 4, issue 4, 83-89

Abstract: 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 (8.2.0.701) 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.

Keywords: Distributed Generation; Optimization; Power Loss; Voltage Stability Index (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:4:y:2019:i:4:id:61237

DOI: 10.24018/ejeng.2019.4.4.1237

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