Distribution Network Reliability and Efficiency Enhancement Using Distributed Generation

Abstract

The Nigerian power sector is faced with many challenges such as: generation deficit, inefficiency and power loss over lengthy transmission and distribution lines, contribution to greenhouse gas emission, weak and dilapidated transmission and distribution infrastructure, dependence on fossil fuels, insufficient power. Efforts should be put in place by relevant authorities to improve the power sector. With the distribution network being the closest to the final consumer, efforts should be made to make it more efficient. This study therefore aims at improving the performance of poor distribution network using Distributed Generation (DG), optimally placed and sized in the network. The Asaba, 2 X 15MVA, 33/11kV injection substation in Asaba, Delta state of Nigeria consisting of Anwai road feeder and SPC feeder radiating outwardly from this injection substation was the focus of this study. Relevant data collected from Benin Electricity Distribution Company (BEDC) was used to carry out load flow study. The simulation and analysis of the result and injection of photovoltaic (PV) DG of Asaba injection substation distribution network using Newton-Raphson iteration technique in ETAP 12.6environment to ascertain the overall performance of the network under base loading condition was modelled from a drawn detailed single line diagram of the network. DGs were optimally placed in specific buses in the network using loss sensitivity analysis. The result revealed that prior to DG placement in the network, only 10.4% of the buses were within statutory voltage limit (394.25V – 435.75V or 0.95p.u – 1.05p.u) and 89.6% of the load buses in the network violated the statutory voltage limit and high losses (active and reactive) of 1329.08kW and 2031kVar. After the optimal placement of DG, the active and reactive power losses on the network reduced by 57.5% and 70.7%. While the voltage profile improved by 94.8%, thereby increasing the capacity, reliability and efficiency of distribution network.