Economic dispatch in multi-area using particle swarm optimization in electricity market

E. Nasr Azadani; S. H. Hosseinian; B. Moradzadeh; P. Hasanpor

doi:10.1109/MEPCON.2008.4562353

Economic dispatch in multi-area using particle swarm optimization in electricity market

E. Nasr Azadani, S. H. Hosseinian, B. Moradzadeh, P. Hasanpor

Not published at VTT

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

5 Citations (Scopus)

Abstract

Competitive bidding for energy and ancillary services is increasingly recognized as an important part of electricity markets. On the other hand, the transmission capacity limits should be considered to optimize the total market cost. In this paper, a new approach based on Constrained Particle Swarm Optimization (CPSO) is developed to address the multi-product and multi-area electricity market dispatch problem. Constraint handling is based on feasibility rules and probability distribution. CPSO method offers a new solution for optimizing the total market cost in a multi-area competitive electricity market considering system constraints. The proposed approach is verified with several cases studies with quadratic and non-smooth cost functions.

Original language	English
Title of host publication	12th International Middle East Power System Conference, MEPCON 2008
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	559-564
ISBN (Electronic)	978-1-4244-1934-0
ISBN (Print)	978-1-4244-1933-3
DOIs	https://doi.org/10.1109/MEPCON.2008.4562353
Publication status	Published - 18 Sep 2008
MoE publication type	A4 Article in a conference publication
Event	2008 12th International Middle East Power System Conference, MEPCON 2008 - Aswan, Egypt Duration: 12 Mar 2008 → 15 Mar 2008

Conference

Conference	2008 12th International Middle East Power System Conference, MEPCON 2008
Country	Egypt
City	Aswan
Period	12/03/08 → 15/03/08

Fingerprint

Keywords

Energy bidding price
Particle swarm optimization
Reserve bidding price

Cite this

Azadani, E. N., Hosseinian, S. H., Moradzadeh, B., & Hasanpor, P. (2008). Economic dispatch in multi-area using particle swarm optimization in electricity market. In 12th International Middle East Power System Conference, MEPCON 2008 (pp. 559-564). [4562353] IEEE Institute of Electrical and Electronic Engineers . https://doi.org/10.1109/MEPCON.2008.4562353

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keywords = "Energy bidding price, Particle swarm optimization, Reserve bidding price",

author = "Azadani, {E. Nasr} and Hosseinian, {S. H.} and B. Moradzadeh and P. Hasanpor",

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Azadani, EN, Hosseinian, SH, Moradzadeh, B & Hasanpor, P 2008, Economic dispatch in multi-area using particle swarm optimization in electricity market. in 12th International Middle East Power System Conference, MEPCON 2008., 4562353, IEEE Institute of Electrical and Electronic Engineers , pp. 559-564, 2008 12th International Middle East Power System Conference, MEPCON 2008, Aswan, Egypt, 12/03/08. https://doi.org/10.1109/MEPCON.2008.4562353

Economic dispatch in multi-area using particle swarm optimization in electricity market. / Azadani, E. Nasr; Hosseinian, S. H.; Moradzadeh, B.; Hasanpor, P.

12th International Middle East Power System Conference, MEPCON 2008. IEEE Institute of Electrical and Electronic Engineers , 2008. p. 559-564 4562353.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AB - Competitive bidding for energy and ancillary services is increasingly recognized as an important part of electricity markets. On the other hand, the transmission capacity limits should be considered to optimize the total market cost. In this paper, a new approach based on Constrained Particle Swarm Optimization (CPSO) is developed to address the multi-product and multi-area electricity market dispatch problem. Constraint handling is based on feasibility rules and probability distribution. CPSO method offers a new solution for optimizing the total market cost in a multi-area competitive electricity market considering system constraints. The proposed approach is verified with several cases studies with quadratic and non-smooth cost functions.

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Access to Document

10.1109/MEPCON.2008.4562353

Link to publication in Scopus