# Efficient Wireless Monitoring and Control of a Grid-Connected Photovoltaic System
## 1 Introduction  
There are two essential reasons why the use of renewable energy is attractive--environmental protection and the increasing demand for energy consumption. Among the different renewable energy sources, solar energy through photovoltaic systems (PV) is rapidly spreading in recent years as solar farms or distributed photovoltaic systems. As it is widely known, solar energy has several advantages such as cleanness, broad availability, and low maintenance, but it has a limited energy conversion efficiency, which makes it crucial to guarantee the correct operation of the PV system components. That refers to the whole PV system, consisting of the PV modules connected in series and/or parallel, and the DC/DC and DC/AC converters when they are connected to the power grid. Moreover, improving system performance in PV installations requires monitoring, which makes the continuous investigation of advanced monitoring and control techniques a necessity to keep up with the advances of the technology. Monitoring focuses on measuring production and checking the operation of the converter and communication devices. The monitoring and control systems for PV installations include sensors, a data acquisition system, and data analysis algorithms [1]. The PV modules are responsible for converting photon energy into electrical power, and they are exposed to outdoor environments, hence to the negative effects of soiling,heavy rain, hail, strong wind, etc. To maintain their efficiency close to the nominal efficiency, it is required to monitor their main parameters with sensors to detect if the solar modules suffer any fault, partial shading conditions, or aging degradation. With the appearance of these conditions, the hot spots [2], in the PV modules can make the PV system efficiency decrease and accelerate the degradation of the modules. Therefore, the sensors to detect early faults play an important role in PV systems. On the other hand, the DC/DC converter transforms the voltage from one DC level to another DC level. In this case, the DC/DC converter used is a boost topology, which can only increase the input voltage level. The control of the boost converter is responsible for searching the maximum power point (MPP) through an MPPT algorithm. There is a wide variety of MPPTs, from the simplest to the most complex, and all of them have the same goal--searching for the MPP. Usually, the MPPT algorithms obtain the voltage that provides the MPP and the system works at that voltage, controlling the DC/DC converter duty cycle. The most used MPPT is the perturb and observe (P&O) algorithm [3], which is very simple and easy to implement. Other simple and linear MPPT algorithms are the incremental conductance [3], or the ripple correlation control [4]. When there are perturbations, the response of the linear systems can be slower or commit the stability of the system. Then, other MPPT algorithms are used, such as the sliding mode control [5], the fuzzy logic [6], neural networks [7], particle swarm optimization [8], etc. [9]. The non-linear backstepping control is another algorithm used as MPPT [10]. The controller provides the reference voltage to be achieved to work at the MPP by means of the regulation of the duty cycle. This type of control is robust and guarantees global stability. In this study, the adaptive Lyapunov control is used to control the boost converter. The adaptive Lyapunov control is similar to the backstepping control, the difference being that the former takes into consideration the degradation of the components of the DC/DC converter, such as the inductor and the capacitor, to make the system work more efficiently and robustly. Then, the DC/AC converter is connected at the output of the DC/DC converter when the PV system is grid-connected. The inverter is responsible for converting the DC voltage into AC voltage. Moreover, the DC/AC converter injects the energy from the PV system into the power grid.