# Centralized MPPT Control Architecture for Photovoltaic Systems Using LoRa Technology
## 1 Introduction  
As reported by the International Energy Agency (IEA) [1], a record solar photovoltaic (PV) capacity of 425 GW was installed in 2023. The current share of solar PV in the global electricity mix is just over 5%, but it is expected to increase to 17% in 2030. In this scenario, it is crucial to adequately control the operation of PV systems in order to maximize their energy output, especially by taking into account the intermittency of the primary energy source and the highly non-linear behavior of the process of converting sunlight into electricity. PV systems consist of PV cells that are integrated into modules arranged in series/parallel configurations, which are usually connected to the grid through one or more power electronic interfaces. The voltage/current curve of PV modules has an operating point that optimizes its output power, i.e., the Maximum Power Point (MPP). This curvechanges with varying environmental conditions, particularly with respect to irradiance and cell temperature, but also with partial shading, unclean PV panels, and PV cell degradation [2]. Thus, MPP tracking (MPPT) controllers are used to continuously deliver the best PV system performance, even though conditions evolve during the day and over its lifetime [3]. Usually, the output of the MPPT controllers is the duty cycle of a Pulse Width Modulated (PWM) signal, which governs the gate of the power switches in DC-DC power electronic converters [4]. As described in the literature, there exist several MPPT algorithms [5; 6; 7; 8]. In addition, the DC-DC power converters that determine the MPP can be organized in several ways. There may be one converter per module, or there may be one converter for several modules that share a uniform location [9]. This article focuses on an approach for executing different MPPT algorithms in a centralized way. In particular, the authors propose an architecture in which a central node executes the MPPT algorithms that calculate the duty ratios for the DC-DC converters of each PV subsytem based on irradiance, cell temperature, voltage, and current signals. The proposed architecture allows for implementing complex MPPT techniques like fuzzy logic control, particle swarm optimization, genetic algorithms, model predictive control, or AI-based methods (such as reinforcement learning) [7; 10]. However, for validation purposes, two algorithms were selected: the Perturb and Observe (P&O) and Sliding Mode Control (SMC) techniques. P&O is a simple, widely used MPPT algorithm that requires a low computational cost. Unfortunately, it performs poorly in partially shaded PV modules and during abrupt irradiance variations. SMC techniques are robust and provide the capability to overcome possible lost or wrong messages, which is especially relevant when using wireless communications [11]. Typically, the communications between sensors, controllers, and power converters are wired, but, in the context of the rapid advancement of Industry 4.0, Wireless Sensor and Actuator Networks (WSANs) are being increasingly accepted in numerous industrial applications [12; 13; 14; 15; 16]. Thus, we propose LoRa/LoRaWAN, a Low-Power Wide-Area Network (LPWAN) technology, to implement the centralized MPPT control of PV systems located far away. LoRa's physical layer modulates the signals by means of a spread spectrum technique based on Chirp Spread Spectrum (CSS) technology [17]. Although LoRa has a low data transfer rate, it features low-cost, low-power, and long-range connectivity. In actuality, LoRa can be used over long distances, i.e., up to 5 km in urban environments and 15 km in open areas, which can be extended with high-gain antennas if needed. In addition, it has an excellent immunity to interference and none-line-of-sight conditions [18]. LoRa/LoRaWAN has already been used for different applications in the electrical domain, which involve the monitoring of energy distribution networks and Smart Grids (SGs).