Enhancing power Quality and Reliability in Distribution System using Sequential Learning Neural Network
Author(s):
A.S. Chaitra, Dr.H.R. Sudarshana Reddy, Dr.A. Manjunatha, Dr.M.S. Nagaraja
Keywords:
Network Reconfiguration, SLNN, Distribution Network, DG Replacement
Abstract
To supply reliable and secure power to the consumers in developing countries like India, where electrical power demand had grown up unexpectedly & unpredictably is a challenging task. Power loss minimization and voltage instability has become a major concern in many power distribution networks and many blackouts had been reported. In India, 13-18% of total power generated is lost in distribution system as losses.Also in the current scenario, considering the installation cost of 1MW generating capacity unit in India, the power loss minimization has gained huge importance, and have fascinated many researchers working in power systems. From past three decades, numerous researches had been carried out for power loss minimization and voltage profile enhancement in distribution systems.Therefore this research investigates the distribution system operations and aims to propose new techniques for improved power loss minimization and voltage profile enhancement. The objective of this study is to develop Sequential Learning Neural Network (SLNN) for solving the distributed generation placement problem, the distribution network reconfiguration problem, the capacitor placement problem, and the problem of a combination of the three. The simulated results are encouraging and demonstrate well the effectiveness of the proposed techniques. The simulated results are also compared with the results of other methods available in the literature. It is observed that the performance of proposed technique is better than the other classical techniques in terms of quality of solutions.
Article Details
Unique Paper ID: 166827

Publication Volume & Issue: Volume 11, Issue 2

Page(s): 2065 - 2075
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