Extremum seeking for wind and solar energy applications

Invented in 1922, extremum seeking (ES) is one of the oldest feedback methods. However, its purpose is not regulation but optimization. For this reason, applications of ES have often come from energy systems. The first noted publication on ES in the West is Draper and Li's application to spark timing optimization in internal combustion engines [1]. In the ensuing decades, ES has been applied to gas turbines and even nuclear fusion reactors. Renewable energy applications have brought a new focus on the capabilities of ES algorithms. In this article we present applications of ES in two types of energy conversion systems for renewable energy sources: wind and solar energy. In both areas the goal is maximum power point tracking (MPPT), i.e., the extraction of the maximum feasible energy from the system under uncertainty and in the absence of a priori modeling knowledge about the systems. For the wind energy conversion system (WECS) we perform MPPT by tuning the set point for the turbine speed using scalar ES. For the photovoltaic (PV) array system, we perform MPPT by tuning the duty cycles of the DC/DC converters employed in the system using multivariable ES. For the photovoltaic system we provide experimental results.