It is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO is a metaheuristic as it makes few or no assumptions about the problem being optimized and can search very large spaces of candidate solutions.
Published in Chapter:
Enrichment of Distribution System Stability Through Artificial Bee Colony Algorithm and Artificial Neural Network
Gummadi Srinivasa Rao (V. R. Siddhartha Engineering College (Autonomous), India), Y. P. Obulesh (VIT University, India), and B. Venkateswara Rao (V. R. Siddhartha Engineering College (Autonomous), India)
Copyright: © 2019
|Pages: 21
DOI: 10.4018/978-1-5225-8030-0.ch002
Abstract
In this chapter, an amalgamation of artificial bee colony (ABC) algorithm and artificial neural network (ANN) approach is recommended for optimizing the location and capacity of distribution generations (DGs) in distribution network. The best doable place in the network has been approximated using ABC algorithm by means of the voltage deviation, power loss, and real power deviation of load buses and the DG capacity is approximated by using ANN. In this, single DG and two DGs have been considered for calculation of doable place in the network and capacity of the DGs to progress the voltage stability and reduce the power loss of the system. The power flow of the system is analyzed using iterative method (The Newton-Raphson load flow study) from which the bus voltages, active power, reactive power, power loss, and voltage deviations of the system have been achieved. The proposed method is tested in MATLAB, and the results are compared with particle swarm optimization (PSO) algorithm, ANN, and hybrid PSO and ANN methods for effectiveness of the proposed system.