A Response Surface-Based Cost Model for Wind Farm Design

A Response Surface-Based Wind Farm Cost (RS-WFC) model is developed for the engineering planning of wind farms. The RS-WFC model is developed using Extended Radial Basis Functions (E-RBF) for onshore wind farms in the U.S. This model is then used to explore the influences of different design and economic parameters, including number of turbines, rotor diameter and labor cost, on the cost of a wind farm. The RS-WFC model is composed of three components that estimate the effects of engineering and economic factors on (i) the installation cost, (ii) the annual Operation and Maintenance (O&M) cost, and (iii) the total annual cost of a wind farm. The accuracy of the cost model is favorably established through comparison with pertinent commercial data. The final RS-WFC model provided interesting insights into cost variation with respect to critical engineering and economic parameters. In addition, a newly developed analytical wind farm engineering model is used to determine the power generated by the farm, and the subsequent Cost of Energy (COE). This COE is optimized for a unidirectional uniform “incoming wind speed” scenario using Particle Swarm Optimization (PSO). We found that the COE could be appreciably minimized through layout optimization, thereby yielding significant cost savings.

► We present a Response Surface-Based Wind Farm Cost (RS-WFC) model for wind farm design.
► The model could estimate installation cost, Operation and Maintenance cost, and total annual cost of a wind farm.
► The Cost of Energy is optimized using Particle Swarm Optimization.
► Layout optimization could yield significant cost savings.