Calibration and implementation of analytical wake models in an operational wind farm for the optimisation of wind power applications

Abstract

The output power in wind farms is highly related to the behaviour and interaction of the turbine wakes in them. The fact of modeling the wakes in wind farms the most accurate possible way by using a simple analytical wake model (AWM) is of a great relevance. Recently, it has been raised the question whether AWMs can be calibrated according to the local conditions in the wind farm, in an attempt to reduce their predictive uncertainty. To this regard, one parameter of the AWMs that has been shown highly sensitive to the flow conditions is the wake growth rate, with a proven positive, linear relationship with respect to the turbulence intensity. In this line, the first goal of this project is to calibrate different AWMs for an offshore, operational wind farm, in order to increase their accuracy when estimating the wind farm power output. The second goal of this project is to asses twp types of wakes superposition models on different analytical wake modes. To accomplish them first is designed an available framework for the assessment of analytical wake models using the operational off-shore wind farm dataset.

Outgoing