Optimal Sizing and Location of DG Units for Enhancing Voltage Profile and Minimizing Real Power Losses in the Radial Power Systems Based on PSO Technique

Abstract

Distributed generation (DG) units have an important number of economic, environmental and technical features, which can contribute to the improvement of the reliability and security of the electric grid. However, all benefits that mentioned before cannot be maximised and enhanced unless the best sizing and position of distributed generation units are accurately determined. The arbitrary placement of DG units can lead to negative influences on the electrical networks. A noteworthy number of methods have been suggested to compute the optimal sizing and position of Distributed generation (DG) units in distribution networks. However, some of them focused on an analytical approach to estimate the optimum allocation of DG units in the radial distribution networks. Indeed, although this method was considered both constant and variable loads, as well as this method, overcome the problem of convergence, but the optimal sizing of DG units was not considered. The main intention of this study is to improve a technique that based on an intelligent algorithm for optimal planning and operation of DG technologies to minimise the real power losses, boost the voltage profile and enhance the overall reliability. IEEE Node-15 system has been taken to perform this study based on a MATLAB environment.in a single paragraph.

Grid Performance Enhancement Study Under Restricted Placement and Sizing of PV Distributed Generation

“…The author in [13] has devised an appropriate approach for sizing and positioning a single PV-DG unit on a threephase unbalanced radial distribution feeder. Also, [14] used a PSO technique to find the ideal size and location for single and multiple DGs, with the main goals being to improve the voltage profile and reduce active power losses.…”

Studies enhancement of transient stability by single machine infinite bus system and setting purpose genetic algorithm

“…To enhance stability in single machine infinite bus (SMIB) used probabilistic signature scheme (PSS), genetic algorithm (GA) used to define parameters PSS [12]. Static var compensator (SVC) is used to set SMIB and matrix metalloproteinases (MMPS) parameters with the GA, we note that the network is unstable when not in use SVC [13]- [15].…”