Monte-Carlo simulations based hub height optimization using FLORIS for two interacting onshore wind farms

Abstract

This study focuses on finding the optimum hub height (i.e., tower height) distributions for two interacting on-shore wind farms that are located on relatively complex terrain. Different optimization scenarios are studied, which take into account both the wind farm power output and the relevant cost variations due to changing hub heights. Simulations are performed using the Flow Redirection and Induction in Steady State (FLORIS) framework, which is modified to represent significant variations in hub height levels due to elevation differences, hence partial wake interactions that are occurring as a consequence, are more realistically represented. Optimization is based on a systematic procedure that includes introducing definitions of overall evaluation criterion parameters for objective setting and generation of design of experiments tables and related data via FLORIS simulations to properly cover the design space. A Pareto analysis of generated data to find the most influential parameters is then performed, and response surfaces are generated to represent these variations, which are, in turn, used for Monte Carlo based simulations to determine the optimized hub height distributions. Overall, the optimized results show a reasonable increase can be achieved in wind farm power output levels, while total tower height levels (hence related cost levels) are either not changing or in some cases even getting reduced for the wind farms in consideration.