Horizontal axis wind turbine systems: optimization using genetic algorithms

Abstract

A method for the optimization of a grid-connected wind turbine system is presented. The behaviour of the system components is coupled in a non-linear way, and optimization must take into account technical and economical aspects of the complete system design. The annual electrical energy cost is estimated using a cost model for the wind turbine rotor, nacelle and tower and an energy output model based on the performance envelopes of the power coefficient of the rotor, C P , on the Weibull parameters k and c and on the power law coefficient ˛of the wind profile. In this study the site is defined with these three parameters and the extreme wind speed V max . The model parameters vary within a range of possible values. Other elements of the project (foundation, grid connection, financing cost, etc.) are taken into account through coefficients. The optimal values of the parameters are determined using genetic algorithms, which appear to be efficient for such a problem. These optimal values were found to be very different for a Mediterranean site and a northern European site using our numerical model. Optimal wind turbines at the Mediterranean sites considered in this article have an excellent profitability compared with reference northern European wind turbines. Most of the existing wind turbines appear to be well designed for northern European sites but not for Mediterranean sites.

Site-specific design optimization of horizontal-axis wind turbine systems using PSO algorithm

“…where h denotes the hub height (m), c o is the value of shape parameter at the reference height (h o ), and α is the coefficient of the ground surface friction [12].…”

“…where C L /C d is the lift-to-drag ratio, λ is the amount of lift generated by a wing divided by the drag, and p is the number of blades [12].…”

“…When the wind speed is greater than the nominal speed, the power output is decreased by controlling the pitch angle of blades. For various wind speeds, the produced power can be found by using the following equation [12]:…”

“…The amount of produced energy by a WTS changes according to the site, because different sites have different wind characteristics in terms of mean wind speed, frequency, and direction. Accordingly, there have been a number of studies on performing site-specific design optimization of WTSs in the literature [5,[10][11][12][13][14][15][16][17][18]. A basic model for COE was given in [5].…”

“…In that study, the blade element momentum theory given in [11] was used to compute the amount of energy production. In [12][13][14][15]18], site-specific methods for optimizing WTSs based on cost reduction, for which the objective function was per cost of energy, were proposed. Design optimization was performed to maximize produced energy at minimum cost and site wind characteristics were incorporated into the design process.…”