Wind-PV-storage optimal environomic design using multi-objective Artificial Bee Colony

H. Shayeghi; M. Moradzadeh; Y. Hashemi; M. Saif; L. Vandevelde

doi:10.1109/APPEEC.2015.7381057

Wind-PV-storage optimal environomic design using multi-objective Artificial Bee Colony

H. Shayeghi, M. Moradzadeh, Y. Hashemi, M. Saif, L. Vandevelde

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

Abstract

This paper proposes a multi-objective optimization formulation to design a hybrid wind-photovoltaic-storage system to supply the demand. This design problem aims to minimize the annual cost of the overall system as well as the CO2 emissions, and is solved by Artificial Bee Colony (ABC) algorithm. Solar irradiation, wind speed, and load data are assumed deterministic. Prices are all empirical and components of hybrid system are commercially available. A test system in the Northwestern Iran is investigated. The presented technique yields the optimal number of system devices such that the economic and environmental profits are maximized. A fuzzy decision making (FDM) method is applied for finding the best compromise solution from the set of Pareto-optimal solutions obtained by ABC.

Original language	English
Title of host publication	Proceedings of the 2015 IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2015
Publisher	IEEE Computer Society
Number of pages	5
Volume	2016-January
ISBN (Electronic)	9781467381321
DOIs	https://doi.org/10.1109/APPEEC.2015.7381057
Publication status	Published - 12 Jan 2016
Externally published	Yes
Event	IEEE PES Asia-Pacific Power and Energy Engineering Conference - Brisbane, Australia Duration: 15 Nov 2015 → 18 Nov 2015 Conference number: 10

Conference

Conference	IEEE PES Asia-Pacific Power and Energy Engineering Conference
Abbreviated title	APPEEC 2015
Country/Territory	Australia
City	Brisbane
Period	15/11/15 → 18/11/15

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10.1109/APPEEC.2015.7381057

Cite this

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title = "Wind-PV-storage optimal environomic design using multi-objective Artificial Bee Colony",

abstract = "This paper proposes a multi-objective optimization formulation to design a hybrid wind-photovoltaic-storage system to supply the demand. This design problem aims to minimize the annual cost of the overall system as well as the CO2 emissions, and is solved by Artificial Bee Colony (ABC) algorithm. Solar irradiation, wind speed, and load data are assumed deterministic. Prices are all empirical and components of hybrid system are commercially available. A test system in the Northwestern Iran is investigated. The presented technique yields the optimal number of system devices such that the economic and environmental profits are maximized. A fuzzy decision making (FDM) method is applied for finding the best compromise solution from the set of Pareto-optimal solutions obtained by ABC.",

author = "H. Shayeghi and M. Moradzadeh and Y. Hashemi and M. Saif and L. Vandevelde",

note = "No full text in Eprints. HN 26/10/2017; IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2015 ; Conference date: 15-11-2015 Through 18-11-2015",

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Shayeghi, H, Moradzadeh, M, Hashemi, Y, Saif, M & Vandevelde, L 2016, Wind-PV-storage optimal environomic design using multi-objective Artificial Bee Colony. in Proceedings of the 2015 IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2015. vol. 2016-January, 7381057, IEEE Computer Society, IEEE PES Asia-Pacific Power and Energy Engineering Conference, Brisbane, Queensland, Australia, 15/11/15. https://doi.org/10.1109/APPEEC.2015.7381057

Wind-PV-storage optimal environomic design using multi-objective Artificial Bee Colony. / Shayeghi, H.; Moradzadeh, M.; Hashemi, Y. et al.

Proceedings of the 2015 IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2015. Vol. 2016-January IEEE Computer Society, 2016. 7381057.

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

TY - GEN

T1 - Wind-PV-storage optimal environomic design using multi-objective Artificial Bee Colony

AU - Shayeghi, H.

AU - Moradzadeh, M.

AU - Hashemi, Y.

AU - Saif, M.

AU - Vandevelde, L.

N1 - Conference code: 10

PY - 2016/1/12

Y1 - 2016/1/12

N2 - This paper proposes a multi-objective optimization formulation to design a hybrid wind-photovoltaic-storage system to supply the demand. This design problem aims to minimize the annual cost of the overall system as well as the CO2 emissions, and is solved by Artificial Bee Colony (ABC) algorithm. Solar irradiation, wind speed, and load data are assumed deterministic. Prices are all empirical and components of hybrid system are commercially available. A test system in the Northwestern Iran is investigated. The presented technique yields the optimal number of system devices such that the economic and environmental profits are maximized. A fuzzy decision making (FDM) method is applied for finding the best compromise solution from the set of Pareto-optimal solutions obtained by ABC.

AB - This paper proposes a multi-objective optimization formulation to design a hybrid wind-photovoltaic-storage system to supply the demand. This design problem aims to minimize the annual cost of the overall system as well as the CO2 emissions, and is solved by Artificial Bee Colony (ABC) algorithm. Solar irradiation, wind speed, and load data are assumed deterministic. Prices are all empirical and components of hybrid system are commercially available. A test system in the Northwestern Iran is investigated. The presented technique yields the optimal number of system devices such that the economic and environmental profits are maximized. A fuzzy decision making (FDM) method is applied for finding the best compromise solution from the set of Pareto-optimal solutions obtained by ABC.

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M3 - Conference contribution

AN - SCOPUS:84965062508

VL - 2016-January

BT - Proceedings of the 2015 IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2015

PB - IEEE Computer Society

T2 - IEEE PES Asia-Pacific Power and Energy Engineering Conference

Y2 - 15 November 2015 through 18 November 2015

ER -

Wind-PV-storage optimal environomic design using multi-objective Artificial Bee Colony

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