Evolutionary algorithms for bid-based dynamic economic load dispatch: a large-scale test case

Sunny Orike; David W. Corne

doi:10.1109/CIDUE.2014.7007869

Evolutionary algorithms for bid-based dynamic economic load dispatch: a large-scale test case

Sunny Orike, David W. Corne

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

The bid-based dynamic economic load dispatch problem (BBDELD) is an optimization problem that arises in the modern context of a de-regulated national energy market, and involves matching bids from competing generating companies to the demands of consumers (regions) so as to maximize a measure of 'social profit'. We present a novel approach to solving the BBDELD, and introduce a large-scale test-case designed to reflect the deregulated Nigerian electricity industry. We build on previous work on smart evolutionary algorithm approaches to the static economic load dispatch (SELD) and dynamic economic load dispatch (DELD) problems, and also the BBELD (the non-dynamic form). We evaluate the performance of two evolutionary algorithm, previously reported on small-scale test cases of the BBELD, on dynamic extensions of those test cases (with demand profiles varied over 24 periods), and we introduce a new large-scale test case based on Nigerian sector data, involving 40 generators, 11 customers in 24 dispatch periods. The results demonstrate that the two approaches reported seem more effective than previous approaches on the previously reported cases (when tested on the non-dynamic versions for which prior results are available), and are capable of dealing successfully with the country's large-scale test case.

Original language	English
Title of host publication	IEEE SSCI 2014: 2014 IEEE Symposium Series on Computational Intelligence - CIDUE 2014: 2014 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, Proceedings
Publisher	IEEE
Pages	69-76
Number of pages	8
ISBN (Print)	9781479945160
DOIs	https://doi.org/10.1109/CIDUE.2014.7007869
Publication status	Published - 2015
Event	2014 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments - Orlando, United Kingdom Duration: 9 Dec 2014 → 12 Dec 2014

Conference

Conference	2014 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments
Abbreviated title	CIDUE 2014
Country/Territory	United Kingdom
City	Orlando
Period	9/12/14 → 12/12/14

Keywords

deregulation
economic load dispatch
evolutionary algorithm
power system
smart mutation

Access to Document

10.1109/CIDUE.2014.7007869

Cite this

Orike, S., & Corne, D. W. (2015). Evolutionary algorithms for bid-based dynamic economic load dispatch: a large-scale test case. In IEEE SSCI 2014: 2014 IEEE Symposium Series on Computational Intelligence - CIDUE 2014: 2014 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, Proceedings (pp. 69-76). Article 7007869 IEEE. https://doi.org/10.1109/CIDUE.2014.7007869

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title = "Evolutionary algorithms for bid-based dynamic economic load dispatch: a large-scale test case",

abstract = "The bid-based dynamic economic load dispatch problem (BBDELD) is an optimization problem that arises in the modern context of a de-regulated national energy market, and involves matching bids from competing generating companies to the demands of consumers (regions) so as to maximize a measure of 'social profit'. We present a novel approach to solving the BBDELD, and introduce a large-scale test-case designed to reflect the deregulated Nigerian electricity industry. We build on previous work on smart evolutionary algorithm approaches to the static economic load dispatch (SELD) and dynamic economic load dispatch (DELD) problems, and also the BBELD (the non-dynamic form). We evaluate the performance of two evolutionary algorithm, previously reported on small-scale test cases of the BBELD, on dynamic extensions of those test cases (with demand profiles varied over 24 periods), and we introduce a new large-scale test case based on Nigerian sector data, involving 40 generators, 11 customers in 24 dispatch periods. The results demonstrate that the two approaches reported seem more effective than previous approaches on the previously reported cases (when tested on the non-dynamic versions for which prior results are available), and are capable of dealing successfully with the country's large-scale test case.",

keywords = "deregulation, economic load dispatch, evolutionary algorithm, power system, smart mutation",

author = "Sunny Orike and Corne, {David W.}",

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Orike, S & Corne, DW 2015, Evolutionary algorithms for bid-based dynamic economic load dispatch: a large-scale test case. in IEEE SSCI 2014: 2014 IEEE Symposium Series on Computational Intelligence - CIDUE 2014: 2014 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, Proceedings., 7007869, IEEE, pp. 69-76, 2014 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, Orlando, United Kingdom, 9/12/14. https://doi.org/10.1109/CIDUE.2014.7007869

Evolutionary algorithms for bid-based dynamic economic load dispatch: a large-scale test case. / Orike, Sunny; Corne, David W.
IEEE SSCI 2014: 2014 IEEE Symposium Series on Computational Intelligence - CIDUE 2014: 2014 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, Proceedings. IEEE, 2015. p. 69-76 7007869.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - The bid-based dynamic economic load dispatch problem (BBDELD) is an optimization problem that arises in the modern context of a de-regulated national energy market, and involves matching bids from competing generating companies to the demands of consumers (regions) so as to maximize a measure of 'social profit'. We present a novel approach to solving the BBDELD, and introduce a large-scale test-case designed to reflect the deregulated Nigerian electricity industry. We build on previous work on smart evolutionary algorithm approaches to the static economic load dispatch (SELD) and dynamic economic load dispatch (DELD) problems, and also the BBELD (the non-dynamic form). We evaluate the performance of two evolutionary algorithm, previously reported on small-scale test cases of the BBELD, on dynamic extensions of those test cases (with demand profiles varied over 24 periods), and we introduce a new large-scale test case based on Nigerian sector data, involving 40 generators, 11 customers in 24 dispatch periods. The results demonstrate that the two approaches reported seem more effective than previous approaches on the previously reported cases (when tested on the non-dynamic versions for which prior results are available), and are capable of dealing successfully with the country's large-scale test case.

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BT - IEEE SSCI 2014: 2014 IEEE Symposium Series on Computational Intelligence - CIDUE 2014: 2014 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, Proceedings

PB - IEEE

Y2 - 9 December 2014 through 12 December 2014

ER -

Evolutionary algorithms for bid-based dynamic economic load dispatch: a large-scale test case

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Keywords

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