Extremum-Seeking Control With Adaptive Excitation: Application to a Photovoltaic System

Abstract

-The objective of this study is to improve the performance of the extremum-seeking control ( ) technique in terms of time and accuracy of convergence towards the optimum operating point of a dynamic system subject to the effect of external disturbances. More precisely, the idea is to reduce the undesirable effect of time scale separation in on the performance of the closed loop system. The method consists in adaptively controlling the excitation signal amplitude using a neural network (NN) model, which gives a real-time estimate of the optimal operating point based on the measurement of the external disturbances. Stability of the proposed with adaptive excitation, referred to in the following as , is demonstrated. The superiority of compared to in terms of accuracy and time of convergence to the optimum is demonstrated both theoretically and experimentally, in the case of the optimization of a photovoltaic panel system (PV).

Design and Experimental Implementation of a Hysteresis Algorithm to Optimize the Maximum Power Point Extracted from a Photovoltaic System

“…The external load of the PV panel is imposed onto it, and then the DC/DC converter drives the current to the load according to the MPPT objective. In other words, the converter is used to perform impedance matching [20]. This means that the duty cycle of the converter has a direct effect in the load seen by the PV panel when the load is connected to the output of the converter.…”

“…The most common DC/DC converters used in a PV panel area are the Boost converter and the Buck converter. Both converters accomplish the objective to adjust the equivalent impedance seen by the PV module at its terminals by using the relation between the PV module and the load voltage [20,23,24].…”

“…The value of this Maximum Power Point depends on the current irradiance and the cell temperature and it is then necessary for an MPPT algorithm to ensure that the PV system operates with its maximum power conversion efficiency, or as close as possible, even when these conditions change. However, in real operating conditions, the influence of a temperature variation on the PV panel may be negligible compared to the irradiation changes [20,21]. In general, the MPPT is an important challenge because the condition that determines the amount of energy into the PV module may change at any time [22].…”

“…Additionally, varied versions of conventional MPPTs, such as the modified version of the most popular techniques (HC, P&O, IndCond) have been developed to mitigate the drawbacks resulting from using the traditional algorithms [36,37]. Moreover, extremum seeking control techniques have also been implemented to realize the MPPT [20,21,30,38]. Finally, there are other control techniques that have been applied to extract the MPP from a PV cell by improving the behavior of classic techniques previously mentioned.…”

On the Extremum-Seeking Control Design and Application for Anaerobic Digestion Processes

“…Since the model and/or cost function of the optimized system are not available, ESC transforms the optimization problem into a control problem ensuring convergence to zero of the estimated gradient [15]. Therefore, obtaining gradient information for an unknown function is a key element for ESC.…”