Optimal placement of wind turbines: A Monte Carlo approach with large historical data set

Abstract

Numerous technical issues arise with the close spacing of multiple wind turbines in a wind farm, particularly one with a severely limited spatial footprint. One of the most important factors under consideration is the wake effect. Since the energy losses due to wakes can significantly decrease the energy production and lead to fluctuations in the output power of a wind farm it is desired to determine optimal positions for installing multiple wind turbines. In the current study, an algorithm that determines an optimal positioning of multiple wind mills in a small footprint wind park under multiple wake effects is introduced. This approach is a mathematical method which explores the various possible positioning combinations via a Monte Carlo-like random search methodology and finds the best choice which maximizes the objective. Matlab (©Mathworks) is used to numerically generate the algorithm and obtain an optimal solution. The case study considered for implementing this algorithm is the Minnesota State University 2-year grant project for installation and testing of four small wind turbine systems on campus. Statistical data from the Weather Analysis Laboratory for Teaching and Educational Resources (WALTER) on campus, consisting of wind speed and direction data over a period of one year is considered to determine the annual power generated.