Brief communication: Real-time estimation of the optimal tip-speed ratio for controlling wind turbines with degraded blades
Year: 2024
Type: article
Abstract: . Rotor performance is adversely affected by wear and tear of blade surfaces caused, for example, by rain, snow, icing, dirt, bugs, ageing, etc. Blade surface degradation changes the aerodynamic properties of the rotor, which in turn changes the optimal tip-speed ratio (TSR) and the corresponding maximum power coefficient. Below rated wind speed, if a turbine continues to operate at the manufacturer designed optimal TSR, the rotor power could decrease more than necessary unless the optimal TSR is corrected to compensate for blade degradation or other off-design conditions. Re-tuning the tip-speed ratio in these off-design conditions can lead to an improvement in energy capture. In this work, we describe a real-time algorithm to re-tune the tip-speed ratio to its optimal, but unknown, value under blade degradation. The algorithm uses power measurements only and a Log-of-Power Proportional-Integral Extremum Seeking Control (LP-PIESC) strategy to re-tune the TSR. The value of this algorithm is demonstrated using it to command the TSR set-point required by a generator speed control loop that maximizes power generated below rated wind speeds. Comparison of this solution with a baseline controller that uses the optimal TSR for a rotor with clean blades demonstrates improvements in energy capture between 0.5 % and 3.4 %, depending on the severity of blade degradation and the wind conditions. These results are obtained using the OpenFAST simulation tool, the NREL 5-MW reference turbine and the Reference Open-Source Controller developed by the US National Renewable Energy Laboratory.
Source: Wind energy science
Authors: Devesh Kumar, Mario Rotea
Institution: The University of Texas at Dallas
Language: English
Topic: Wind Turbine Control Systems
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,132
OpenAlex ID: W4404195674