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Environment Friendly BB-BC Optimized Economic Dispatch with Real and Reactive Power Constraints

by H. K. Verma, Prachi Mafidar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 43 - Number 4
Year of Publication: 2012
Authors: H. K. Verma, Prachi Mafidar
10.5120/6090-8266

H. K. Verma, Prachi Mafidar . Environment Friendly BB-BC Optimized Economic Dispatch with Real and Reactive Power Constraints. International Journal of Computer Applications. 43, 4 ( April 2012), 10-15. DOI=10.5120/6090-8266

@article{ 10.5120/6090-8266,
author = { H. K. Verma, Prachi Mafidar },
title = { Environment Friendly BB-BC Optimized Economic Dispatch with Real and Reactive Power Constraints },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 4 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 10-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number4/6090-8266/ },
doi = { 10.5120/6090-8266 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:32:31.016203+05:30
%A H. K. Verma
%A Prachi Mafidar
%T Environment Friendly BB-BC Optimized Economic Dispatch with Real and Reactive Power Constraints
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 4
%P 10-15
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The basic objective of Economic Dispatch (ED) of electric power generation is to schedule the committed generating unit outputs to meet the load demand at minimum operating cost subject to equality and inequality constraints. In recent years with increasing awareness about environmental issues this problem has taken an essential development i. e. economic dispatch now includes the dispatch of power to minimize pollutants (from fossil fuel power generating units), as well as to achieve minimum cost. This paper presents comparative study of two algorithms namely Particle Swarm Optimization (PSO) and Big Bang-Big Crunch Optimization (BB-BC) which are implemented on Environment Friendly BB-BC Optimized Economic Dispatch with Real and Reactive Power Constraints problem. It is shown that the performance of BB-BC method demonstrates superiority over PSO algorithm.

References
  1. K. Sathish Kumar, V. Tamilselvan, N. Murali, R. Rajaram, N. Shanmuga Sundaram, T. Jayabarathi, "Economic Load Dispatch with Emission Constraints using Various PSO Algorithms", WSEAS Transactions on Power Systems, Issue 9, Volume 3, September 2008.
  2. U_ur Güvenç, "Combined Economic Emission Dispatch Solution using Genetic Algorithm Based on Similarity Crossover", Scientific Research and Essays Vol. 5(17), pp. 2451-2456, 4 September, 2010.
  3. K. Senthil M. E. , "Combined Economic Emission Dispatch using Evolutionary Programming Technique", IJCA Special Issue on "Evolutionary Computation for Optimization Techniques" ECOT, 2010.
  4. A. Lakshmi Devi, O. Vamsi Krishna, " Combined Economic and Emission Dispatch Using Evolutionary Algorithms-A Case Study" ARPN Journal of Engineering and Applied Sciences, Vol. 3, No. 6, December 2008.
  5. Yee Ming Chen, Wen-Shiang Wang, "Economic Power Dispatch of Power System with Emission Controlled using Particle Swarm Optimization" 12th WSEAS International Conference on SYSTEMS, Heraklion, Greece, July 22-24, 2008.
  6. C. Rani, AfshinYazdani, "Emission Constrained Economic Dispatch using Various PSO Algorithm", International Journal Of Power System Operation and Energy Management (IJPSOEM) Volume-1, Issue-1, 2011
  7. O. K. Erol, I. Eksin, "A new optimization method: Big Bang–Big Crunch," Advances in Engineering Software, Elsevier, vol. 37, pp. 106–111, 2006.
  8. A. Kaveh, S. Talatahari, "Size optimization of space trusses using Big Bang–Big Crunch algorithm," Computers and Structures, vol. 87 (17-18), pp. 1129-1140, 2009.
  9. Y. Labbi, D. Ben Attuos," Big Bang Big Crunch Optimization algorithm for economic dispatch with valve-point effect", Journal of Theoretical and Applied Information Technology.
  10. D. C. Secui, I. Felea, S. Dzitac, L. Popper, "A Swarm Intelligence Approach to the Power Dispatch Problem", Int. J. of Computers, Communications & Control, Vol. V (2010), No. 3, pp. 375-384.
  11. J. Kennedy and R. C. Eberhart, "Particle swarm optimization", Proceedings of IEEE International Conference on Neural Networks (ICNN'95), Vol. IV, pp. 1942-1948, Perth, Australia, 1995.
  12. Frans Van den Bergh, "An Analysis of Particle Swarm Optimizers", University of Pertoria, Pertoria November 2001.
  13. Tufan Kumbasar, Engin Ye?il, ?brahim Eksin, Müjde Güzelkaya, "Inverse Fuzzy Model Control With Online Adaptation via Big Bang-Big Crunch Optimization", ISCCSP 2008, Malta, 12-14 March 2008.
  14. Hakkl M. Gene;, ibrahim Eksin, Osman K. Erol, "Big Bang - Big Crunch Optimization Algorithm Hybridized With Local Directional Moves and Application to Target Motion Analysis Problem", IEEE 201 0.
  15. Ghaith M. Jaradat, Masri Ayob, "Big Bang-Big Crunch Optimization Algorithm to Solve the Course Timetabling Problem", IEEE 2010.
  16. M. Kripka, M. L. Kripka, "Big Crunch Optimization Method," EngOpt 2008 - International Conference on Engineering Optimization Rio de Janeiro, Brazil, June, 2008.
Index Terms

Computer Science
Information Sciences

Keywords

Particle Swarm Optimization Big Bang–big Crunch Economic Dispatch Emission Dispatch Fuel Cost Function Total Emission Function Penalty Factor

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