Title :
Optimal number of DFIG wind turbines in farm using Pareto genetic algorithm to minimize cost and turbines fault effect
Author :
Khattara, A. ; Becherif, M. ; Ayad, M.Y. ; Bahri, M. ; Aboubou, A.
Author_Institution :
Lab. of Energy Syst. Modeling, UMKB Univ., Biskra, Algeria
Abstract :
With the development of power system, the wind power is considered as a promising solution due to its properties (clean and free source energy, high efficiency). Doubly fed induction generator (DFIG) wind turbines are widely used today in wind farms and their installation and maintenance raise many technical problems such as the minimization of the wind turbine fault effect on the grid and cost minimization. In this paper, a mathematical approximation and a Pareto genetic algorithm program are developed to calculate the minimum installation and maintenance cost of a wind farm with the minimum lost of power during permanent and transient line fault. This approach allows obtaining the optimal number of DFIG wind turbines that should be connected in the same bus regarding the considered criteria. A typical IEEE 14-bus network is modeled using the PSAT to verify the line fault ride through (LFRT) capability of the farm to evaluate the cost effectiveness and the fault effect.
Keywords :
Pareto optimisation; approximation theory; asynchronous generators; genetic algorithms; wind turbines; DFIG wind turbines; IEEE 14-bus network; PSAT; Pareto genetic algorithm; cost minimization; doubly fed induction generator wind turbines; line fault ride through capability; mathematical approximation; power system development; wind power; wind turbine fault effect; Genetic algorithms; Maintenance engineering; Power system stability; Transient analysis; Wind farms; Wind power generation; Wind turbines; DFIG; Distribution; Genetic algorithm; LFRT; Line fault; PSAT; Pareto;
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
DOI :
10.1109/IECON.2013.6699997