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Wednesday 20 September 2017

Optimal Location and Sizing of DG using Genetic Algorithm and Fuzzy logic

Optimal Location and Sizing of DG using Genetic Algorithm and Fuzzy logic

The project proposes a comparison between Fuzzy Logic and Genetic Algorithm for optimal location and sizing of distributed generation in a distribution network. The objective function consists of both power losses and investment costs and the methods are tested on the IEEE 14,30 and 57-Bus system. The Fuzzy logic method includes a fuzzy inference system (FIS) containing a set of rules which are considered to determine the DG placement suitability index of each node in the distribution system. The optimal sizing of DG unit is obtained with the help of mathematical expressions. The study covers a comparison between the proposed approaches and shows the importance of installing the right amount of DG in the best suited location.

Simulation Performed as listed below,

·       14-IEEE Bus System with DG Size of 1,2 and 3 using Fuzzy Logic
·       30-IEEE Bus System with DG Size of 1,2 and 3 using Fuzzy Logic
·       57-IEEE Bus System with DG Size of 1,2 and 3 using Fuzzy Logic
·       14,30 and 57-IEEE Bus System without DG using Fuzzy Logic

·       14-IEEE Bus System with DG Size of 1,2 and 3 using Genetic Algorithm
·       30-IEEE Bus System with DG Size of 1,2 and 3 using Genetic Algorithm
·       57-IEEE Bus System with DG Size of 1,2 and 3 using Genetic Algorithm
·       14,30 and 57-IEEE Bus System without DG using Genetic Algorithm

Reference Paper-1: Optimal Distributed Generation Location and Sizing using Genetic Algorithms
Author's Name: Sujata Huddar, B. Kantharaj, K. R. Mohan, S. B. Patil, Rudresh Magadum
Source: IEEE
Year: 2009
Reference Paper-2: Optimal Location and Sizing of DG using Fuzzy logic
Author's Name: I. Pisică, C. Bulac, Member, IEEE, and M. Eremia, Senior Member, IEEE
Source: International Journal of Modern Engineering Research (IJMER)
Year: 2014

Reference Source Code available @ http://www.verilogcourseteam.com/matlab-electrical8

Simulation Video Demo