Cuckoo Search Algorithm for Integration Wind Power Generation to Meet Load Demand Growth

S Makhloufi, S. D Koussa, Gobind Gopalakrishna Pillai

Research output: Contribution to conferencePaperResearchpeer-review

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Abstract

This article presents a new efficient method for optimal placement and sizing of wind power generators (WPG) in power networks with an objective of coping maximum loadability margin and minimizing reactive power loss. A new total voltage stability based on continuation power flow (CPF) theorem is used to model the problem. The method also highlights the effects of random characteristics of wind resources on loadability margin. Cuckoo search algorithm is applied to find the optimum placement and sizing of WPG since it presents several advantages of few control parameters, high solution quality and fast computational time. The experiment results of IEEE 9-bus show that the optimum location and size of WPGs are different from those considering power system loss and voltage deviation in objective function of the optimization process. A significant effect of the random characteristic of wind resource during load demand growth is revealed. The simulation results show that the CSA can be an efficient and promising method for optimal placement and sizing of WPG in power networks problem.
Original languageEnglish
Publication statusPublished - 6 Jun 2017
EventIEEE 17th International Conference on Environment and Electrical Engineering - Milan, Italy
Duration: 6 Jun 20179 Jun 2017

Conference

ConferenceIEEE 17th International Conference on Environment and Electrical Engineering
Abbreviated titleEEEIC 2017
CountryItaly
CityMilan
Period6/06/179/06/17

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Wind power
Power generation
Reactive power
Voltage control
Electric potential
Experiments

Cite this

Makhloufi, S., Koussa, S. D., & Gopalakrishna Pillai, G. (2017). Cuckoo Search Algorithm for Integration Wind Power Generation to Meet Load Demand Growth. Paper presented at IEEE 17th International Conference on Environment and Electrical Engineering, Milan, Italy.
Makhloufi, S ; Koussa, S. D ; Gopalakrishna Pillai, Gobind. / Cuckoo Search Algorithm for Integration Wind Power Generation to Meet Load Demand Growth. Paper presented at IEEE 17th International Conference on Environment and Electrical Engineering, Milan, Italy.
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abstract = "This article presents a new efficient method for optimal placement and sizing of wind power generators (WPG) in power networks with an objective of coping maximum loadability margin and minimizing reactive power loss. A new total voltage stability based on continuation power flow (CPF) theorem is used to model the problem. The method also highlights the effects of random characteristics of wind resources on loadability margin. Cuckoo search algorithm is applied to find the optimum placement and sizing of WPG since it presents several advantages of few control parameters, high solution quality and fast computational time. The experiment results of IEEE 9-bus show that the optimum location and size of WPGs are different from those considering power system loss and voltage deviation in objective function of the optimization process. A significant effect of the random characteristic of wind resource during load demand growth is revealed. The simulation results show that the CSA can be an efficient and promising method for optimal placement and sizing of WPG in power networks problem.",
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Makhloufi, S, Koussa, SD & Gopalakrishna Pillai, G 2017, 'Cuckoo Search Algorithm for Integration Wind Power Generation to Meet Load Demand Growth' Paper presented at IEEE 17th International Conference on Environment and Electrical Engineering, Milan, Italy, 6/06/17 - 9/06/17, .

Cuckoo Search Algorithm for Integration Wind Power Generation to Meet Load Demand Growth. / Makhloufi, S; Koussa, S. D; Gopalakrishna Pillai, Gobind.

2017. Paper presented at IEEE 17th International Conference on Environment and Electrical Engineering, Milan, Italy.

Research output: Contribution to conferencePaperResearchpeer-review

TY - CONF

T1 - Cuckoo Search Algorithm for Integration Wind Power Generation to Meet Load Demand Growth

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AU - Koussa, S. D

AU - Gopalakrishna Pillai, Gobind

PY - 2017/6/6

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N2 - This article presents a new efficient method for optimal placement and sizing of wind power generators (WPG) in power networks with an objective of coping maximum loadability margin and minimizing reactive power loss. A new total voltage stability based on continuation power flow (CPF) theorem is used to model the problem. The method also highlights the effects of random characteristics of wind resources on loadability margin. Cuckoo search algorithm is applied to find the optimum placement and sizing of WPG since it presents several advantages of few control parameters, high solution quality and fast computational time. The experiment results of IEEE 9-bus show that the optimum location and size of WPGs are different from those considering power system loss and voltage deviation in objective function of the optimization process. A significant effect of the random characteristic of wind resource during load demand growth is revealed. The simulation results show that the CSA can be an efficient and promising method for optimal placement and sizing of WPG in power networks problem.

AB - This article presents a new efficient method for optimal placement and sizing of wind power generators (WPG) in power networks with an objective of coping maximum loadability margin and minimizing reactive power loss. A new total voltage stability based on continuation power flow (CPF) theorem is used to model the problem. The method also highlights the effects of random characteristics of wind resources on loadability margin. Cuckoo search algorithm is applied to find the optimum placement and sizing of WPG since it presents several advantages of few control parameters, high solution quality and fast computational time. The experiment results of IEEE 9-bus show that the optimum location and size of WPGs are different from those considering power system loss and voltage deviation in objective function of the optimization process. A significant effect of the random characteristic of wind resource during load demand growth is revealed. The simulation results show that the CSA can be an efficient and promising method for optimal placement and sizing of WPG in power networks problem.

M3 - Paper

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Makhloufi S, Koussa SD, Gopalakrishna Pillai G. Cuckoo Search Algorithm for Integration Wind Power Generation to Meet Load Demand Growth. 2017. Paper presented at IEEE 17th International Conference on Environment and Electrical Engineering, Milan, Italy.