DESIGN OF FIREFLY AND ANT LION ALGORITHM FOR OPTIMAL ALLOCATION OF MULTIPLE DG

     This project is design based on the paper "Optimal Allocation of Multiple Distributed Generators in Distribution System using Firefly Algorithm". Renewable sources can supply a clean and smart solution to the increased demands. Optimal allocation (sizing and siting) of multiple distributed generators (DGs) in the distribution system is an important issue due to increasing demands. Location and sizing of DG have affected largely on the system losses. This project presents an effective technique for determining the optimal location and sizing of DGs for minimizing power losses, operational costs and improving the voltage profile and voltage stability index of the radial distribution system (RDS). The entire problem is divided into two subproblems. The first location of DGs is finding out by using the integrated approach loss sensitivity factor (LSF) and voltage stability factor (VSF) concepts. In this project, Ant Lion Optimization Algorithm (ALOA) and Firefly Algorithm are designed for optimal location and sizing of DG for various distribution systems. The Optimization Algorithm is used to deduce the locations and sizing of DG from the elected buses. The proposed algorithm is tested on two IEEE radial distribution systems IEEE 33 and 69 bus test systems with considering constant power load at different load levels. Fitness function based on equation 16 (power loss index, total operating cost, voltage deviation index, voltage stability index) and Load Flow based on equation 5 from the reference paper-1.

Reference Paper-1: Optimal Allocation of Multiple Distributed Generators in Distribution System using Firefly Algorithm
Author’s Name:
Sureshkumar Sudabattula and Kowsalya M
Source:
Journal of Electrical Engineering
Year:
2017
Reference Paper-2: Ant Lion Optimization Algorithm for optimal location and sizing of renewable distributed generations
Author’s Name: E.S. Ali, S.M. Abd Elazim, and A.Y. Abdelaziz
Source: Elsevier- Renewable Energy
Year:2016
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