Economic load dispatch using a chemotactic differential evolution algorithm

Arijit Biswas, Sambarta Dasgupta, Bijaya K. Panigrahi, V. Ravikumar Pandi, Swagatam Das, Ajith Abraham, Youakim Badr

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

This paper presents a novel stochastic optimization approach to solve constrained economic load dispatch (ELD) problem using Hybrid Bacterial Foraging-Differential Evolution optimization algorithm. In this hybrid approach computational chemotaxis of BFOA, which may also be viewed as a stochastic gradient search, has been coupled with DE type mutation and crossover of the optimization agents. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints (ramp rate limits) and prohibited operating zones. Simulations were performed over various standard test systems with different number of generating units and comparisons are performed with other existing relevant approaches. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques.

Original languageEnglish (US)
Title of host publicationHybrid Artificial Intelligence Systems - 4th International Conference, HAIS 2009, Proceedings
Pages252-260
Number of pages9
DOIs
StatePublished - Nov 16 2009
Event4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009 - Salamanca, Spain
Duration: Jun 10 2009Jun 12 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5572 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009
CountrySpain
CitySalamanca
Period6/10/096/12/09

Fingerprint

Differential Evolution Algorithm
Economics
Stochastic Gradient
Methodology
Chemotaxis
Foraging
Stochastic Optimization
Test System
Hybrid Approach
Crossover
Optimization Algorithm
Mutation
Robustness
Unit
Optimization
Simulation
Standards

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Biswas, A., Dasgupta, S., Panigrahi, B. K., Pandi, V. R., Das, S., Abraham, A., & Badr, Y. (2009). Economic load dispatch using a chemotactic differential evolution algorithm. In Hybrid Artificial Intelligence Systems - 4th International Conference, HAIS 2009, Proceedings (pp. 252-260). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5572 LNAI). https://doi.org/10.1007/978-3-642-02319-4_30
Biswas, Arijit ; Dasgupta, Sambarta ; Panigrahi, Bijaya K. ; Pandi, V. Ravikumar ; Das, Swagatam ; Abraham, Ajith ; Badr, Youakim. / Economic load dispatch using a chemotactic differential evolution algorithm. Hybrid Artificial Intelligence Systems - 4th International Conference, HAIS 2009, Proceedings. 2009. pp. 252-260 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{92f1cbd2f8bd4e36aa8c67c7983d21d9,
title = "Economic load dispatch using a chemotactic differential evolution algorithm",
abstract = "This paper presents a novel stochastic optimization approach to solve constrained economic load dispatch (ELD) problem using Hybrid Bacterial Foraging-Differential Evolution optimization algorithm. In this hybrid approach computational chemotaxis of BFOA, which may also be viewed as a stochastic gradient search, has been coupled with DE type mutation and crossover of the optimization agents. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints (ramp rate limits) and prohibited operating zones. Simulations were performed over various standard test systems with different number of generating units and comparisons are performed with other existing relevant approaches. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques.",
author = "Arijit Biswas and Sambarta Dasgupta and Panigrahi, {Bijaya K.} and Pandi, {V. Ravikumar} and Swagatam Das and Ajith Abraham and Youakim Badr",
year = "2009",
month = "11",
day = "16",
doi = "10.1007/978-3-642-02319-4_30",
language = "English (US)",
isbn = "3642023185",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "252--260",
booktitle = "Hybrid Artificial Intelligence Systems - 4th International Conference, HAIS 2009, Proceedings",

}

Biswas, A, Dasgupta, S, Panigrahi, BK, Pandi, VR, Das, S, Abraham, A & Badr, Y 2009, Economic load dispatch using a chemotactic differential evolution algorithm. in Hybrid Artificial Intelligence Systems - 4th International Conference, HAIS 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5572 LNAI, pp. 252-260, 4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009, Salamanca, Spain, 6/10/09. https://doi.org/10.1007/978-3-642-02319-4_30

Economic load dispatch using a chemotactic differential evolution algorithm. / Biswas, Arijit; Dasgupta, Sambarta; Panigrahi, Bijaya K.; Pandi, V. Ravikumar; Das, Swagatam; Abraham, Ajith; Badr, Youakim.

Hybrid Artificial Intelligence Systems - 4th International Conference, HAIS 2009, Proceedings. 2009. p. 252-260 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5572 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Economic load dispatch using a chemotactic differential evolution algorithm

AU - Biswas, Arijit

AU - Dasgupta, Sambarta

AU - Panigrahi, Bijaya K.

AU - Pandi, V. Ravikumar

AU - Das, Swagatam

AU - Abraham, Ajith

AU - Badr, Youakim

PY - 2009/11/16

Y1 - 2009/11/16

N2 - This paper presents a novel stochastic optimization approach to solve constrained economic load dispatch (ELD) problem using Hybrid Bacterial Foraging-Differential Evolution optimization algorithm. In this hybrid approach computational chemotaxis of BFOA, which may also be viewed as a stochastic gradient search, has been coupled with DE type mutation and crossover of the optimization agents. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints (ramp rate limits) and prohibited operating zones. Simulations were performed over various standard test systems with different number of generating units and comparisons are performed with other existing relevant approaches. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques.

AB - This paper presents a novel stochastic optimization approach to solve constrained economic load dispatch (ELD) problem using Hybrid Bacterial Foraging-Differential Evolution optimization algorithm. In this hybrid approach computational chemotaxis of BFOA, which may also be viewed as a stochastic gradient search, has been coupled with DE type mutation and crossover of the optimization agents. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints (ramp rate limits) and prohibited operating zones. Simulations were performed over various standard test systems with different number of generating units and comparisons are performed with other existing relevant approaches. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques.

UR - http://www.scopus.com/inward/record.url?scp=71049134006&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=71049134006&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-02319-4_30

DO - 10.1007/978-3-642-02319-4_30

M3 - Conference contribution

AN - SCOPUS:71049134006

SN - 3642023185

SN - 9783642023187

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 252

EP - 260

BT - Hybrid Artificial Intelligence Systems - 4th International Conference, HAIS 2009, Proceedings

ER -

Biswas A, Dasgupta S, Panigrahi BK, Pandi VR, Das S, Abraham A et al. Economic load dispatch using a chemotactic differential evolution algorithm. In Hybrid Artificial Intelligence Systems - 4th International Conference, HAIS 2009, Proceedings. 2009. p. 252-260. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-02319-4_30