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Optimal Bidding strategy in South Region Day-ahead Market Model using New Aggregated Demand Model and Hybrid Technique

by V. Madhu Sudana Reddy, B. Subramanyam, M. Surya Kalavathi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 131 - Number 7
Year of Publication: 2015
Authors: V. Madhu Sudana Reddy, B. Subramanyam, M. Surya Kalavathi
10.5120/ijca2015907383

V. Madhu Sudana Reddy, B. Subramanyam, M. Surya Kalavathi . Optimal Bidding strategy in South Region Day-ahead Market Model using New Aggregated Demand Model and Hybrid Technique. International Journal of Computer Applications. 131, 7 ( December 2015), 24-33. DOI=10.5120/ijca2015907383

@article{ 10.5120/ijca2015907383,
author = { V. Madhu Sudana Reddy, B. Subramanyam, M. Surya Kalavathi },
title = { Optimal Bidding strategy in South Region Day-ahead Market Model using New Aggregated Demand Model and Hybrid Technique },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 131 },
number = { 7 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 24-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume131/number7/23462-2015907383/ },
doi = { 10.5120/ijca2015907383 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:26:53.790589+05:30
%A V. Madhu Sudana Reddy
%A B. Subramanyam
%A M. Surya Kalavathi
%T Optimal Bidding strategy in South Region Day-ahead Market Model using New Aggregated Demand Model and Hybrid Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 131
%N 7
%P 24-33
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper a half breed calculation (ABC_PSO) comprising of Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) in light of demonstrating for the ideal offering systems in an aggressive power force business sector is proposed. We set forward a novel enhanced strategy which enhances the Profit of the suppliers. In the aforementioned technique ideal using so as to offer parameters are controlled the two periods of the Artificial Bee Colony (ABC). From the streamlined parameters the definite arrangement is anticipated by utilizing third phase of the ABC calculation i.e scout honey bee. Here, the honey bee's populace speed and the position vector are enhanced by utilizing the method of PSO rather than Scout honey bee, to locate the precise offering parameters. The Indian Energy Exchange (IEX) hourly based burden request dataset is utilized for using so as to foresee the heap Artificial Neural Network (ANN) system. At long last the proposed system is executed in the MATLAB/simulink stage and viability is investigated by utilizing the correlation of distinctive procedures like Artificial Bee Colony (ABC) calculation, Particle Swarm Optimization (PSO) calculation, ABC_PSO. The aftereffects of examination exhibited the prevalence of the proposed approach and affirm its capability to take care of the issue.

References
  1. D. L. Post, S. S. Coppinger, and G. B. Sheblé, “Application of auctions as a pricing mechanism for the interchange of electric power,” IEEE Trans. Power Syst., vol. 10, pp. 1580–1584, Aug. 1995.
  2. G. B. Sheblé, Computational Auction Mechanisms for Restructured Power Industry Operation. Norwell, MA: Kluwer, 1999.
  3. M. Shahidehpour and M. Marvali, Maintenance Scheduling in Restructured Power Systems. Norwell, MA: Kluwer, 2000.
  4. David, A.K. and Fushuan, “Strategic bidding in competitive electricity markets: a literature survey”, IEEE Power Engineering Society Summer Meeting, Seattle, WA, July 16–20, vol. 4, pp. 2168–2173, 2000.
  5. TengshunPeng and Kevin Tomsovic, “Congestion Influence on Bidding Strategiesin an Electricity Market”, IEEE Transactions on Power Systems, Vol. 18, No. 3, pp. 1054-1061, 2003.
  6. Gountis, V.P. and Bakirtzis, ‘Bidding strategies for electricity producers in a competitive electricity marketplace” IEEE Transactions on Power Systems, Vol.19, No.1 , 356–365, 2004.
  7. J. Vijaya Kumar, D.M. Vinod Kumar, “Particle swarm optimization based optimal bidding strategy in an open Electricity market”, International Journal of Engineering, Science and Technology Vol. 3, No. 6, , pp. 283-294, 2011.
  8. Reinhard Haas, Christian Panzer, Gustav Resch , Mario Ragwitz , Gemma Reece and Anne Held, “A historical review of promotion strategies for electricity from renewable energy sources in EU countries”, Elsevier in its journal Renewable and Sustainable Energy Reviews,Vol. 15, No. 2, pp.1003-1034, 2011.
  9. J.Vijaya Kumar, D.M.Vinod Kumar and K.Edukondalu, "Strategic bidding using fuzzy adaptive gravitational search algorithm in a pool based electricity market", Applied Soft Computing, Vol.13, No.5, pp.2445–2455, 2013.
  10. Dervis Karaboga and Bahriye Basturk, "Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems", World Congress on Foundations of Fuzzy Logic and Soft Computing, pp.789-798, 2007.
  11. Indian Electricity Exchange [Online]: Available: www.iexindia.com
Index Terms

Computer Science
Information Sciences

Keywords

ABC PSO ANN optimal bidding electricity power market

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