"Improvement of power quality in distributed generation system using optimization techniques"

Vishal Patidar , Raghunandan Singh Baghel

PSO, MATLAB, Voltage Stability, Load Flow, Distribution Generation, Artificial Neural Networks

The distributed generation (DG) generates electrical power in the distribution networks or on the network user side. In distribution networks, DGs have significant role to perform for reduction of real power and enhancing the stability in voltage of power system. Distribution companies find that it is an effective way of minimizing losses, handling the great cost of energy that is not supplied or preventing or delaying the expansion of the network. But, precise positioning and sizing of DGs in network is the crucial problem because in case the position of DGs is not appropriate, then the increased size can cause a big risk and loss for system. The installations of DG require special attention and studies to enhance the reliability and performance of the system. When the DGs are placed optimally, it can minimize the cost of operation and network losses and enhances the power quality. In order to determine the optimum size and location of DGs, various approaches have been introduced in the literature. Thus, various approaches were proposed till now for optimal placement and sizing of DGs, however, they do not provide the optimal results for voltage stability enhancement and power loss reduction. Therefore, in proposed work, three approaches are presented i.e. PSO-Sim, PSO and GA, for the optimal placement and sizing of DG units. These approaches are proposed with the intention to improve the voltage stability and minimize power loss by optimal placement of DGs. The implementation of these approaches is performed in IEEE-33 bus test system. The performance of the proposed approaches is analyzed in terms of three different parameters i.e. VSI, voltage profile and power losses, and the obtained results demonstrates the efficiency of GA approach over other two proposed approaches.

Volume 13 Issue 9, September-2025

Pages : c432-c439