CSL team receives $500,000 grant to improve wind turbine efficiency

Changing, unpredictable behavior challenges computer-based systems, especially in large, interconnected networks. Volatile behavior—such as wind variances that affect the performance of a network of wind turbines—inspired a team of CSL researchers to investigate the ways systems communicate and collaborate with one other in the face of adversarial conditions.

The team, led by CSL Professors Carolyn Beck, Angelia Nedich, and Alex Olshevsky, received a $500,000 grant from the National Science Foundation, titled “Design of Network Dynamics for Strategic Team-Competition.” The goal of the grant is to create a method that allows each unit of a team to perform well individually, despite unstable conditions, while maximizing output as a group.

“Wind turbines, for example, work in a team to produce electricity. We want to figure out ways to group them, set their blade angles and rotation speeds, so that we’re maximizing power output, even given the nature of the wind blowing different ways, at different times, and at different speeds,” said Beck, an associate professor of industrial and enterprise systems.

Since the grant started earlier this year, graduate student Lucas Buccafusca has looked at the dynamics of wind turbine systems, developing techniques that capitalize on the symmetry of the wind turbine systems to maximize power output, assuming the wind is the same. Future work will focus on varying wind.

“It is pretty complicated—each rotating blade creates a downstream wake and every turbine faces the problem of setting an appropriate rotation speed under complex interactions,” said Olshevsky. “The problem is to determine rotation speeds for the individual turbines that maximize the total energy from the wind, while dealing with the wake effects from neighboring turbines and unpredictable variations in the speed and direction of the wind.”

This work applies to many other systems, including the power grid, traffic networks, environmental monitoring networks, and more.

“We’re trying to make the dynamic systems communicate optimally and with the minimum amount of energy, in the face of uncertainty and disturbances,” said Nedich.