Complete Schedule

Presentation Type

Poster Presentation (UNI Access Only)

Keywords

Wind turbines--Location; Wind power plants--Equipment and supplies;

Abstract

Wind energy utilization is growing rapidly in the last decades. More specifically, the number of offshore wind farm projects has been increased significantly in recent years. The electrical energy is generated through wind turbines that are placed in certain locations for maximum wind power extraction. In offshore wind farms, many wind turbines are placed in a certain order and connected to each other to deliver the generated power to the closest power grid. The exact locations of wind turbines in a wind farm are decided based on certain criteria in order to deliver maximum power. After deciding on the wind turbine micro-sittings, how to connect the turbines electrically is another major question specifically for cable cost minimization. Literature presents many researches on the wind turbine installation and location identifications that increase the wind farm power output. However, there are a few researches on the collection system cabling for cost optimization. This study presents a method for Wind Farm Layout Optimization Problem (WFLOP) that has the objection function of collection system cable cost and power losses. The objective function is minimized using Genetic algorithm and multiple travelling sales man algorithm. The proposed method is tested with a wind farm that includes over 100 turbines and realistic system parameters. Results show that the cable installation costs are minimized together with the system power losses.

Start Date

3-4-2018 11:00 AM

End Date

3-4-2018 1:30 PM

Faculty Advisor

Sadik Kucuksari

Department

Department of Technology

File Format

application/pdf

Embargo Date

4-11-2019

Available for download on Thursday, April 11, 2019

Off-Campus Access

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Apr 3rd, 11:00 AM Apr 3rd, 1:30 PM

Wind Farm Layout Optimization Using Genetic Algorithm and Multiple Traveling Sales Man Algorithm

Wind energy utilization is growing rapidly in the last decades. More specifically, the number of offshore wind farm projects has been increased significantly in recent years. The electrical energy is generated through wind turbines that are placed in certain locations for maximum wind power extraction. In offshore wind farms, many wind turbines are placed in a certain order and connected to each other to deliver the generated power to the closest power grid. The exact locations of wind turbines in a wind farm are decided based on certain criteria in order to deliver maximum power. After deciding on the wind turbine micro-sittings, how to connect the turbines electrically is another major question specifically for cable cost minimization. Literature presents many researches on the wind turbine installation and location identifications that increase the wind farm power output. However, there are a few researches on the collection system cabling for cost optimization. This study presents a method for Wind Farm Layout Optimization Problem (WFLOP) that has the objection function of collection system cable cost and power losses. The objective function is minimized using Genetic algorithm and multiple travelling sales man algorithm. The proposed method is tested with a wind farm that includes over 100 turbines and realistic system parameters. Results show that the cable installation costs are minimized together with the system power losses.