Title :
A new tool for wind farm optimal design
Author :
González, J. Serrano ; Rodrìguez, Á G González ; Mora, J. Castro ; Santos, J. Riquelme ; Payán, M. Burgos
Author_Institution :
Dept. Electr. Eng., Univ. of Seville, Sevilla, Spain
Abstract :
An evolutive algorithm (EA) for wind farm optimal design is presented. The algorithm objective is to optimize the profits given an investment on a wind farm. Net Present Value (NPV) will be used as a figure of the revenue in the proposed method. To estimate the NPV is necessary to calculate the initial capital investment and net cash flow throughout the wind farm life cycle. The maximization of the NPV means the minimization of the investment and the maximization of the net cash flows (to maximize the generation of energy and minimize the power losses). Both terms depend mainly of the number and type of wind turbines, the tower height and geographical position, electrical layout, among others. Besides, other auxiliary costs must be to keep in mind to calculate the initial investment such as the cost of auxiliary roads or tower foundations. The complexity of the problem is mainly due to the fact that there is not analytic function to model the wind farm costs and most of the main variables are linked.
Keywords :
poles and towers; power generation economics; wind power plants; wind turbines; evolutive algorithm; net cash flow maximization; net present value estimation; tower height; wind farm optimal design; wind turbines; Algorithm design and analysis; Costs; Investments; Life estimation; Poles and towers; Power generation; Roads; Wind energy generation; Wind farms; Wind turbines; Wind farms; evolutive algorithm; genetic algorithm; optimization;
Conference_Titel :
PowerTech, 2009 IEEE Bucharest
Conference_Location :
Bucharest
Print_ISBN :
978-1-4244-2234-0
Electronic_ISBN :
978-1-4244-2235-7
DOI :
10.1109/PTC.2009.5281977