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Control Seminar

Extremum Seeking for Wind and Solar Energy

Azad Ghaffari Postdoctoral Research Fellow University of Michigan, Department of Mechnical Engineering
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Environmental parameters, e.g. solar irradiance and wind speed, define the power map for Photovoltaic( PV) and Wind Energy Conversion Systems (WECS). Maximum Power Point Tracking (MPPT) algorithms, which may also contain internal control loops to achieve desired closed-loop performance, are the key elements to extract maximum achievable power from wind and solar systems. Conventional model-based MPPT algorithms require a priori knowledge of the system and environmental conditions in order to maintain energy production at its feasible peak. Also, the inner control loops of the WECS are generally composed of cascaded PID loops, which are known to be highly efficient during steady state. However, the transient performance of WECS is of special interest de to the intermittent nature of wind power. Hence, a more sophisticated inner-loop algorithm based on the idea of Field-Oriented Control (FOC) is introduced, which in combination, with a gradient-based Extremum Seeking (ES) guarantees MPPT. Replacing the gradient-based ES with the Newton-based ES, which uses the inverse estimate of the Hessian and the gradient vector, results in uniform and user-assignable transients for a wide range of power maps. An estimate of the Hessian is given using a perturbation matrix. Also, a Riccati estimator is used to calculate the inverse of the Hessian. Various simulations on the WECS and experiments on the PV systems are presented to verify the validity of the proposed algorithms.
Azad Ghaffari is a Postdoctoral Research Fellow in the Mechanical Engineering Department at the University of Michigan. He received his B.S. degree in electrical engineering and the M.S. degree in control engineering from the K.N. Toosi University of Technology. Tehran, Iran, and the Ph.D. degree in mechanical and aerospace engineering from the Joint Doctoral Program between San Diego State University and the University of California, San Diego, CA. USA. His current research interests include distributed supervisory controller design for swapping modularity, cross-coupling control of multi-axis servo systems, demand response in power systems, extremum seeking and its application to maximum power point tracking in photovoltaic and wind energy conversion systems, induction machines, power electronics, and sliding mode control.

Sponsored by

Bosch, Eaton, Ford, MathWorks, and Toyota