Wind turbines work over a wide range of conditions and have long operating life. As a result, the optimal parameters of the control system may change from initial design specifications. Turbine wear and tear change the aerodynamic characteristics of the blades, and thus the rotor performance. Local atmospheric conditions and topography produce wind patterns which are specific to the site, while operations in wind farms add further variability due to wake interactions. In these cases, tuning a turbine's control parameters to the site-specific operating conditions has the potential to reduce power losses and/or excessive loads at low cost. Extremum seeking control (ESC) is an algorithm to tune control parameters for power maximization below rated wind speeds. Our team at the University of Texas at Dallas has designed and evaluated various instances of the ESC algorithm using simplified numerical models (NREL FAST), fully developed Large Eddy Simulations (UTD-WF) and field testing at the DOE National Renewable Energy Laboratory (NREL). This presentation will explain the fundamental principles of the ESC algorithm, review the results of a field-test evaluation of the ESC algorithm for single-turbine power maximization (where the ESC has achieved 8-12% improvement in energy capture) and discuss practical implementations of ESC for wind farm power maximization.