## 1 Introduction  
The high volatility of oil prices, coupled with increasing worldwide concerns over CO\({}_{2}\) emissions, has led to the evolution of renewable energy concepts over the past few years. Among others the use of solar photovoltaic (PV), has emerged as the most appropriate solution and has continuously been gaining considerable attention among industry players all around the globe. With the growing demand for clean energy sources, the manufacture and deployment of solar PV cells and photovoltaic arrays have expanded dramatically in the recent years.  
Monitoring of photovoltaic plants and optimization of the energy they produce is a key issue in order to guarantee this type of plants can serve to their goal of significantly contributing to supply the ever increasing demand of electrical power. Monitoring systems currently available on the market are limited to the evaluation of the average power produced in a given time interval, as a function of several parameters coming from the inverter [1; 2; 3; 4; 5; 6]. Even though relevant, knowing the average power is not enough to either globally evaluate the overall performance of the PV plant or to identify potential failures affecting some plant components (such as single cells or clusters of cells). Instead, it would be very interesting to have information related to how much energy each of the PV panels in the plant is producing. Thus, it would be possible to easily identify the elements that are not operating properly and repair or replace them. Obviously, this would require that each of these PV panels be individually monitored and that the data obtained be communicated to some kind of control system, and here is where wireless sensor networks come into play.  
A wireless sensor network (WSN) consists of several small, inexpensive sensor nodes that communicate detected events wirelessly [7; 8; 9]. Quite often, WSNs are used to monitor certain delicate situations as those indicated in [10]: floods [11], volcanoes [12], radioactive materials [13], wildfire [14], ethylene [15], methane [16], _etc._ However, they can also be used in other less critical cases, like the one covered in this work, where the information to be gathered is so exhaustive that several simple sensors (from a few tens to some hundreds) are needed. In these cases, it is the information flow that becomes critical, and several studies have been carried out covering this topic [17; 18; 19]. Smart sensor nodes with at least two sensors will be attached to each PV panel in order to monitor its performance. As well as the sensors, these nodes include a processor, a radio system and a power supply that provides the energy required by the node. This latter element is an important component in the correct operation of any smart wireless node.  
Through the development of a WSN, the work presented in this paper supports deeper monitoring of relevant parameters to identify efficiency features, failures and weaknesses of the whole PV infrastructure. Data coming from the sensor network will be elaborated in order to simplify the decision making process and to help reducing failures, waste and, consequently, costs.  
The paper is organized as follows: Section 2 summarizes the current state of the art and presents an overview of the system proposed in the paper. Section 3 describes the implementation of the system, paying special attention to the power supply developed and the communication protocol. Section 4 describes how the overall system operates and explains the algorithm of network routine. Experimental results are presented in Section 5 and final conclusions are provided in Section 6.