Application of
Stochastic Filtering and Control Methodology to the Optimization of Wind
Turbine Control Design
A. V. Balakrishnan
03-01
EISG Project
Title: Application of Stochastic Filtering and Control Methodology to the
Optimization of Wind Turbine Control Design
EISG Grant Number: 03-01
PIER Area: Renewable Energy Technologies
Principal Investigator: A. V. Balakrishnan
Contact Information: Phone:
(310) 825-1594, email: bal@ee.ucla.edu
Organization: University of California, Los Angeles
Grant Amount: $74,993
Grant Term: 12 Months
Project Description:
§ Proposes to demonstrate the feasibility of applying stochastic filtering and control theories to the problem of improving energy production and mitigating transient fatigue loads for large-scale wind turbines.
Proposed Outcomes:
§ A comprehensive nonlinear dynamical system model for large-scale wind turbines will be developed and tested as part of the project.
Anticipated Benefits:
§ Potential to reduce the cost of energy for wind-generated electricity by 3-5%.
§ The proposed advanced optimal control algorithms have the potential to increase the power captured and prolong the lifetime of wind turbines.