Wind farm layout optimization by using Definite Point selection and genetic algorithm

Abstract

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.

Wind Farm Layout: Modeling and Optimization Using Genetic Algorithm

“…On the other hand, Chowdhury et al opted for particle swarm optimization to resolve the non-linear optimization problem that affects the wind turbine layout and employs turbines of varying diameters [6]. Shakoor et al (2014) studied a combination of generic and definite point selection algorithms to approach the optimal wind turbine layout design problem [7]. Christopher Elkinton et al [8] focused on minimizing the production costs of the wind turbine farm and maximizing the power output by reducing wake effects.…”

The Application of Water Cycle Optimization Algorithm for Optimal Placement of Wind Turbines in Wind Farms

“…Shakoor [14] Genetic algorithm The linear Jensen's wake model was employed with definite selection criteria.…”

“…Many previous works have sought to identify the optimal distribution of WTs within a WF [8][9][10][11][12][13][14][15][16][17][18][19][20][21]. The summary of these related works is presented in Table 1.…”

Investigation into the Optimal Wind Turbine Layout Patterns for a Wind Farm in Walvis Bay, Namibia

“…Rabia Shakoor, Mohammad Yusri Hassan, Abdur Raheem, Nadia Rasheed and Mohamad Na'im Mohd Nasir used Definite Point Selection (DPS) and Genetic Algorithm to optimally arrange wind turbines in a wind farm by minimizing the cost per unit power and minimizing the wake effects [14]. The cost per unit power was minimized by changing the dimensions of the wind farm while keeping the area of the wind farm constant by which the area is the same as the area used in [5,13].…”

“…The cost per unit power was minimized by changing the dimensions of the wind farm while keeping the area of the wind farm constant by which the area is the same as the area used in [5,13]. By comparing the results in [14] to the results in [8] and [13] that the power output of the wind farm increased by using the same area with different dimensions when the total number of wind turbines in a wind farm were the same.…”