Optimal capacitor placement using genetic Algorithm on radial distribution network.

Abstract

The power generated by generation centers is transferred to load centers through transmission or distribution systems and it is not meeting the load demand mainly due to the losses and poor voltage regulation occurring in the networks. One of the most efficient methods of reduction of power losses on the power network is placement of capacitors. Capacitor banks have previously been installed on the network, however conventional ‘trial and error’ methods have been employed achieving little or no technical loss improvement which calls for optimization of the placement and sizing of capacitors. The project is carried out with an objective of identifying the optimal location and sizes of the capacitors in a radial distribution network to have a reduction in power cost and capacitor costs. The network data is modelled and a load flow before optimization is carried out. The results are used to compute the loss sensitivity factors which identify the potential locations for capacitor placement. The objective function to be minimized is the sum of power loss cost function and the capacitor cost function which is formulated using the network constraints. The genetic algorithm is developed and implemented to determine the sizes of capacitors while minimizing power loss cost and capacitor cost. Using the genetic algorithm technique, the technical performance of the network is improved, there is a significant improvement in the voltage regulation on the network and a significant reduction in the network power losses and the cost. The algorithm is effective in determining optimal locations and sizes of capacitors as compared to results obtained from the conventional methods.