AN EFFICIENT COUPLED GENETIC ALGORITHM AND LOAD FLOW ALGORITHM FOR OPTIMAL PLACEMENT OF DISTRIBUTED GENERATORS

Authors

  • Rashed Mobin Department Of Electrical Engineering.,Meghnad Saha Institute Of Technology,Kolkata,India
  • Mr.Ambarnath Banerji(HOD) Department Of Electrical Engineering.,Meghnad Saha Institute Of Technology,Kolkata,India
  • Utsav Das Department Of Electrical Engineering.,Meghnad Saha Institute Of Technology,Kolkata,India

Keywords:

INTRODUCTION, LOAD FLOW, GA FOR DGs PLACEMENT, CASE STUDY

Abstract

A genetic algorithm is used in conjunction with an efficient load flow programme to determine the optimal locations of the predefined DGs with MATLAB & MATPOWER software. The best location for the DGs is determined using the genetic algorithm. The branch electrical loss is considered as the objective function and the system total loss represent the fitness evaluation function for driving the GA. The load flow equations are considered as equality constraints and the equations of nodal voltage and branch capacity are considered as inequality constraints. The approach is tested on a 9 &14 bus IEEE distribution feeder.

Downloads

Published

2021-03-27

Issue

Vol. 2 No. 4 (2015): IJIERT

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0 DEED).

You are free to:

  1. Share — copy and redistribute the material in any medium or format
  2. The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

  1. Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  2. NonCommercial — You may not use the material for commercial purposes .
  3. NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
  4. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Notices:

You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .

No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.

 

Rights of Authors

Authors retain the following rights:
1. Copyright and other proprietary rights relating to the article, such as patent rights,
2. the right to use the substance of the article in future works, including lectures and books,
3. the right to reproduce the article for own purposes, provided the copies are not offered for sale,
4. the right to self-archive the article.