Document Type

Open Access Thesis

Embargo Period

5-13-2014

Degree Program

Mechanical Engineering

Degree Type

Master of Science in Mechanical Engineering (M.S.M.E.)

Year Degree Awarded

2014

Month Degree Awarded

September

Advisor Name

Matthew

Advisor Middle Initial

A

Advisor Last Name

Lackner

Co-advisor Name

Jon

Co-advisor Middle Initial

G

Co-advisor Last Name

McGowan

Abstract

NEW GENERATOR CONTROL ALGORITHMS FOR SMART-BLADED WIND TURBINES TO IMPROVE POWER CAPTURE IN BELOW RATED CONDITIONS

APRIL 2014

BRYCE BAUTISTA AQUINO

B.S.M.E., UNIVERSITY OF MASSACHUSETTS AMHERST

M.S.M.E., UNIVERSITY OF MASSACHUSETTS AMHERST

Directed by: Professor Matthew A. Lackner

ABSTRACT

With wind turbines growing in size, operation and maintenance has become a more important area of research with the goal of making wind energy more profitable. Wind turbine blades are subjected to intense fluctuating loads that can cause significant damage over time. The need for advanced methods of alleviating blade loads to extend the lifespan of wind turbines has become more important as worldwide initiatives have called for a push in renewable energy. An area of research whose goal is to reduce the fatigue damage is smart rotor control. Smart bladed wind turbines have the ability to sense aerodynamic loads and compute an actuator response to manipulate the aerodynamics of the wind turbine. The wind turbine model for this research is equipped with two different smart rotor devices. Independent pitch actuators for each blade and trailing edge flaps (TEFs) on the outer 70 to 90% of the blade span are used to modify aerodynamic loads. Individual Pitch Control (IPC) and Individual Flap Control (IFC) are designed to control these devices and are implemented on the NREL 5 MW wind turbine.

The consequences of smart rotor control lie in the wind turbine’s power capture in below rated conditions. Manipulating aerodynamic loads on the blades cause the rotor to decelerate, which effectively decreases the rotor speed and power output by 1.5%. Standard Region 2 generator torque control laws do not take into consideration variations in rotor dynamics which occur from the smart rotor controllers. Additionally, this research explores new generator torque control algorithms that optimize power capture in below rated conditions.

FAST, an aeroelastic code for the simulation of wind turbines, is utilized to test the capability and efficacy of the controllers. Simulation results for the smart rotor controllers prove that they are successful in decreasing the standard deviation of blade loads by 26.3% in above rated conditions and 12.1% in below rated conditions. As expected, the average power capture decreases by 1.5%. The advanced generator torque controllers for Region 2 power capture have a maximum average power increase of 1.07% while still maintaining load reduction capabilities when coupled with smart rotor controllers. The results of this research show promise for optimizing wind turbine operation and increasing profitability.