Wind farm layout optimization by using definite point selection and genetic algorithm

Shakoor, Rabia and Hassan, Mohammad Yusri and Abdur, Raheem and Nadia, Rasheed and Mohd Nasir, Mohamad Na'im (2014) Wind farm layout optimization by using definite point selection and genetic algorithm. In: 2014 IEEE International Conference on Power and Energy (PECon), , 1-3 Dec 2014, Sarawak, Malaysia.

[img] PDF
07062439.pdf - Published Version
Restricted to Registered users only

Download (353kB) | Request a copy


At present, wind energy industry is facing major design constraints in boosting the power output. These can be overcome by setting up the right turbine at the right place. This paper proposes an optimized layout design of a wind farm by using Definite Point selection(DPS) and genetic algorithm, which can minimize the cost per unit power and minimum wake effects, while sustaining the obligatory space between adjacent turbines for operation safety. The existing cost per unit power can be reduced by changing the dimensions of wind farm with constant area. In this study, the velocity deficits caused by the wakes of each turbine were calculated by using Jensens wake model. The total area of wind farm 2 Km x 2 Km was divided into 10x10 cells with each cell having dimensions 200 m x 200 m. The results showed that power output of the wind farm by using the same area in different dimension was increased even when the total numbers of wind turbines were the same. It was observed that 32 wind turbines in 2 Km x 2 Km area could produce a total power of 16,251.56 kW with fitness value of 0.001537. The present research results had been validated using the results from previous studies.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: optimization, wake effect, wind farm, Jensen's wake mode, genetic algorithm
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Electrical Engineering > Department of Industrial Power
Date Deposited: 06 Apr 2015 01:47
Last Modified: 28 May 2015 04:38
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item