In the method, the high-potential buses are identified using the sequential power loss index, and the PSO algorithm is used to find the optimal size and location of capacitors, and the authors in have developed enhanced particle swarm optimization (EPSO) for the optimal placement of capacitors to reduce loss in the distribution system.
The feasibility and effectiveness of the proposed algorithm for optimal placement and sizing of capacitor banks in distribution systems, with the definition of a suitable control pattern, have been proved. 1. Introduction
The objective function of the capacitor optimal placement in distribution networks is the cost of installed capacitors, installation costs, etc., and the cost of power and energy losses.
Capacitors’ placement at optimal locations in the distribution network and their sizing can reduce losses. This also increases feeders’ ampacity and improves the voltage profile, which leads to reduced network investments [4, 5]. The extent of benefits depends on the location, size, and type of the capacitors.
A fuzzy-based approach for optimal placement of fixed capacitors and their sizing in a radial distribution network is adopted in , while in , the presence of voltage and current harmonics is reported. In , the GA is employed for the optimal capacitor allocation.
The optimal capacitance problem has many variables and parameters, such as capacitor size and optimal capacitor location. In addition, constraints such as bus voltages are also involved. In this paper, objectives and constraints are considered as follows: Different objectives in the case of capacitor placement can be considered.