California State University, Sacramento

Our group studies the advanced flow diagnostic techniques and their applications in renewable energy systems. 

Areas of interest:

1) Development and optimization of the renewable energy generation systems

• Wind/solar resource assessment

• Wind turbine aerodynamics and wake interference

• Wind turbine icing physics and anti-/de-icing strategies

• Wind turbine power forecast under extreme weathers

• Wind turbine health monitoring and control optimization

• Hybrid renewable energy system

2) Advanced Flow Diagnostics and Instrumentations

• Particle image velocimetry (PIV) and stereoscopic PIV techniques.

• Digital image projection (DIP) technique and 3D shape reconstruction

• Infrared thermometry technique

• Shadowgraph and Schlieren techniques

• LiDAR measurement

High-speed imaging technique measures dynamic ice accretion and transient water transport behaviors

Digital image projection technique quantifies the 3-dimensional shapes of the ice structures and water flows

Transient 3-dimensional shapes of the rivulet flows

Quantified ice structures accreted over both surfaces of an airfoil

Particle image velocimetry technique characterizes the aerodynamic properties of an ice accreting airfoil

Instantaneous PIV measurements reveal the dynamic changes of the airflow over an ice accretion airfoil

Lift (left) & drag (right) coefficients v.s. ice accretion time

A hybrid strategy combining minimum leading-edge electric-heating and superhydro-/ice-phobic surface coating for wind turbine icing mitigation (save ~90% power consumption)
 

Field campaign to study the wind turbine water interference in a large-scale (300 MW) wind farm using scanning LiDARs

LiDARs (left) and velocity contours of wind turbine wake regions (right). Stars show the locations of wind turbines.

Field campaign to measure the blade ice structures for utility-scale wind turbines using a drone-imaging system