Optimal Placement of Reclosers in a Radial Distribution System for Reliability Improvement

There is a need for the optimal positioning of protective devices to maximize customers satisfaction per their demands. Such arrangement advances the distribution system reliability to maximum achievable. Thus, radial distribution system (RDS) reliability can be improved by placing reclosers at suitable feeder sections. This article presents comprehensive details of an attempt to determine the reclosers’ optimal location in an RDS to maximize the utility profit by reliability improvement. Assessment of different reliability indices such as SAIDI, SAIFI, CAIFI, CAIDI, etc., with recloser placement, exhibits a considerable improvement in these indices in contrast with the absence of recloser. Consequently, a new bidirectional formulation has been proposed for the optimized arrangement of reclosers’. This formulation efficiently handles the bidirectional power flow, resulting from distributed generation (DG) unit (s) in the system. The proposed model has been solved for a test system by utilizing the Genetic algorithm (GA) optimization method. Later, test results conclude that reclosers’ optimal placement contributes significantly towards utility profit with minimum investment and outage costs.

Coordinated planning in improving power quality considering the use of nonlinear load in radial distribution system

<span lang="EN-US">Power quality has an important role in the distribution of electrical energy. The use of non-linear load can generate harmonic spread which can reduce the power quality in the radial distribution system. This research is in form of coordinated planning by combining distributed generation placement, capacitor placement and network reconfiguration to simultaneously minimize active power losses, total harmonic distortion (THD), and voltage deviation as an objective function using the particle swarm optimization method. This optimization technique will be tested on two types of networks in the form 33-bus and 69-bus IEEE Standard Test System to show effectiveness of the proposed method. The use of MATLAB programming shows the result of simulation of increasing power quality achieved for all scenario of proposed method.</span>

Optimal distributed generation placement using artificial intelligence for improving active radial distribution system

There are several profits of distributed generator (DG) units which are believed for improving the safety of the distribution power grids. However, these profits can be maximized by ensuring optimum sizing and positioning of DG units because an arbitrary location of DG units may adversely affect and jeopardize power grids which could contribute to maximising of power loss and degradation of the voltage profile. Therefore, several approaches were suggested to ensure optimum position and size of DGs. The primary aim of this article is for establishing technique for optimum scheduling and operating of DG to lessen power loss, revamp voltage profile and overall network reliability. Artificial intelligence method called particle swarm optimization (PSO) is utilized for finding the best site and size of DG to lessen power loss and boost the voltage profile. In this paper, IEEE 33 distribution system is utilized to display applicability of PSO. The results of the PSO are compared with the results gotten by other methods in the literature. Finally, the results show that the PSO is superior than the other methods.