This project is design based on the paper "Optimal Location and Capacity of STATCOM for Voltage stability Enhancement using ACO plus GA". This project presents a study of short-term hourly load forecasting using Artificial Neural Networks (ANNs). This project is designed with Ant Colony Optimization (ACO) plus Genetic Algorithms (GA) for optimal capacity and location of a new STATCOM with ECI model in a power system. The simulation shows the optimal location and capacity of new STATCOM with ECI model to enhance power system voltage stability by using GACO. The ability of the GA operated after can promote the Ant Colony Optimization (ACO) efficiency. The objective of GA is to improve the searching quality of ants by optimizing themselves to generate a better result because the ants produced randomly by pheromone process are not necessarily better. This method can not only enhance the neighborhood search but can also search the optimum solution quickly to advance convergence.

                STATCOM connected to the power system

Request source code for academic purpose, fill REQUEST FORM or contact +91 7904568456 by whatsapp or, fee applicable.

SIMULATION VIDEO DEMO                                                                                                                                     

You can DOWNLOAD Matlab code and reference paper.