Extremum seeking control of PV system based on least- squares approach (real-time optimization)

Abstract

Today renewable energy has become an absolute necessity taking into account the price of fossil energies and the pollution resulting from her large exploitation. Solar radiation can be converted directly into electrical energy, in the form of direct current, by means of a solar cell. Finding the maximum power point is an essential part in photovoltaic systems. Indeed, the output power varies greatly depending on illumination, temperature, but also the overall aging of the system. In order to operate a PV generator as often as possible at its optimum power, we must introduce a controller and a static converter which will act as an adapter between the source and the load. Many works review the different maximum power methods to adjust the optimal output power and improve the efficiency of the PV system. These methods are broadly classified into several categories. In this paper, such an experimental regulator based on a power mathematical technique is proposed, which is founded on least squares method to estimate the maximum power when operating sub-optimally. This technique makes it possible to compare experimental data, generally tainted with measurement errors, with a mathematical model supposed to write these data. This study gives the opportunity to experimentally test a mathematical method with a PV system which mainly uses a BOOST chopper. The DC / DC converter and the regulator are designed and produced within the research unit while using an STM32F4 microcontroller over sun. The results obtained from the use of this optimization technique clearly show the very high fidelity between the real values of the current and voltage and their optimal estimated values with a certain uncertainty which does not exceed almost 2%, which shows a good agreement. In the same way, this approach makes it possible to minimize the oscillations around the MPP, which already makes it possible to improve the efficiency of the system which is very close to 100% in experimental tests.