ANT COLONY BASED LOAD FLOW OPTIMISATION USING MATLAB
- Keshav Bansal
- Miteshwar Singh
- Kapil Upamanyu
– Ant colony Optimisation (ACO), Constrained Load Flow (CLF), Genetic Algorithms (GA)
This paper presents a solution to the network constrained optimisation problem using Ant Colony Optimisation (ACO) algorithm. This algorithm consists of artificial agents, called ants, which cooperate among themselves to find an optimal solution to the Constrained Load Flow (CLF) problem. These ants communicate with each other using pheromone matrix, pheromone being a chemical released by real ants for finding the shortest path from food source to their nest. The study revolves around finding the optimum settings of three tap changing transformers, which gives minimum power losses while maintaining a constant demand. The above method is applied to the standard IEEE 30-bus system and results are compared with the solutions obtained from conventional methods. The MATLAB code is developed for the same, and compared with the conventional approach
Keshav Bansal, Miteshwar Singh, Kapil Upamanyu. "ANT COLONY BASED LOAD FLOW OPTIMISATION USING MATLAB".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.1, Issue 2, pp.50 - 54, URL :https://rjwave.org/ijedr/papers/IJEDR1302010.pdf
Volume 1 Issue 2
Pages. 50 - 54