UMP Institutional Repository

Wind Farm Reactive Power Optimization by Using Imperialist Competitive Algorithm

Soheilirad, M. and Hizam, H. and Farzan, P. and Hojabri, Mojgan and Fallah, S. N. and Soheilirad, G. (2013) Wind Farm Reactive Power Optimization by Using Imperialist Competitive Algorithm. In: 2013 International Conference on Power, Energy and Control (ICPEC) . .

[img] PDF
Wind_Farm_Reactive_Power_Optimization_by_Using.pdf - Published Version
Restricted to Repository staff only

Download (236kB) | Request a copy


In this paper a new evolutionary computing method based on imperialist competitive algorithm (ICA) is used for optimization of the reactive power in a wind farm. The output power and also the reactive power of wind farms are not constant due to the oscillation in wind speed. Reactive power optimization is known as an efficient way to have an improvement in power quality and also to reduce power loss. The conventional optimization algorithms have some drawbacks, such as slow convergence and premature. ICA as one of the newest optimization algorithm could be applied in order to optimization of the reactive power and overcomes the difficulties which are coming from the traditional methods. In this paper, the reactive power consumption of a wind turbine is optimized by using (ICA) method. To illustrate the application of the method, a wind farm with some uncertainties is provided. Finally the results of the ICA method are compared with the one of conventional method. Results show that the proposed reactive power optimization method is simple and effective.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Renewable Energy; Wind Farm,Reactive Power Optimization; Evolutionary Computing; Imperialist Competitive Algorith
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 02 Jul 2014 03:06
Last Modified: 09 Jan 2018 06:43
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item