1. Introduction
Most developed countries have promoted policies and initiatives to achieve sustainability by reducing energy dependence and emissions. These initiatives aim to limit climate change and lead to a decarbonized energy system [
1]. Indeed, the deployment of renewables and energy efficiency are considered key agents to fulfilling emission reductions and conforming to the Paris Agreement objectives [
2]. In addition, this general situation, combined with the rapid cost decrease of renewable technologies (mainly photovoltaic (PV) installations—the price of solar PV modules was reduced by around 85% from 2010 to 2015 [
3]), has promoted the rise of renewable-solution deployment and investment. As an example, the renewable sector globally added 167 GW of new generation capacity in 2017. This accounts for a growth of 8.3% over the previous year, maintaining similar rates since 2010, with 8–9% on average per year. This target has been mainly achieved as a result of new PV solar installations and wind power plants connected to the grid. In 2017, 94 GW were added from PV power plants and 47 GW from wind power plants, including 4 GW from offshore wind power plants [
4]. Best et al. [
5] affirms that solar and wind resources are on the upper rungs of the energy ladder, their integration being predominant in higher-income countries. Recent contributions, focused on future electricity systems, also assume that renewable assets can be considered a mix between wind- and solar-power generation [
6]. In [
7], and apart from wind and PV solar deployment, a slight increase has been estimated during the past few years for other renewable energy sources for electricity. In addition, Ellabban et al. [
8] establishes a direct connection between technological maturity and economic barriers, mainly when the cost of a technology is above the cost of other competing alternatives. Therefore, wind and PV solar resources are currently the most integrated renewable energy sources into power systems, excluding hydropower-generation units. Nevertheless, there are no large-area power systems in the world where wind and solar power generate more than 50% of electricity [
9].
The integration of wind and PV power plants into power systems involves certain technical problems, mainly focused on reliability, power quality, and stability [
10]. The intermittent nature of such sources may increase grid stress, mainly due to undesirable oscillations on the supply side [
11] that may affect voltage regulation of transmission systems [
12]. At a low/medium-voltage level, different reactive power control strategies have also been proposed to facilitate renewables integration [
13], including active power curtailment [
14]. As an additional solution to guarantee a balance between generation and demand, with reduced capacity and costs of operating reserves [
15], short-term forecasting of PV production emerges as a relevant topic of interest. In fact, several methods for forecasting PV power over a short-term horizon can be found in the specific literature [
16,
17,
18]. These methods depend on weather conditions and previous PV power-production data. Therefore, updated weather and electric values would allow us to more accurately forecast short-term PV power production. Moreover, real-time monitoring technologies can provide relevant local and accurate information to ensure the control and reliability of the grid [
19]. To achieve these goals, and according to Colak et al. [
20], current power systems should be modernized in terms of sensing, communication, measurement, and automation technologies.
With regard to PV monitoring systems, prior efforts can be found in the specific literature. Low-cost solutions have been considered as a priority during the last decade, proposing different monitoring and communication systems. In [
21], a low-cost microcontroller-based data-acquisition system (DAQS) for remote PV water-pumping systems is proposed. Communications are based on the GSM network and, in particular, on the Short text-Message Service (SMS). Contributions that focused on power-line communication (PLC) modules can be also found in the specific literature. In [
22], a PLC compliant with HomePlug is proposed to monitor each PV module. Another example based on a PLC module is evaluated in [
23], where four PV panels are simultaneously monitored. Nevertheless, recent contributions affirm that the level of noise in a power-line network is considered much higher than any other type of communication network [
24]. A semiautomated solution for testing and monitoring PV-module performances is described in [
25]. A modified rheostat is used to estimate the I-V characteristics of a PV module. Communication between nodes is carried out through a wired RS485 communication protocol, and a solution is built around wired/wireless devices and the Internet of Things (IoT), a concept that is described in [
26]. PV installation is monitored at the inverter level. An extensive comparison of monitoring and transmission systems is also included in this contribution. Another solution based on wired/wireless sensor-network technologies for in situ solar-panel monitoring is discussed in [
27]. The proposed architecture used low-cost open-source tools based on an Arduino platform, including wireless ZigBee connectivity. ZigBee-based wireless technology is also proposed in [
28] to provide online monitoring systems for PV power plants connected to the grid. An overview of ZigBee devices and modules is described in [
29], including a PV energy system belonging to a water treatment and distribution company. Evaluation of measurement accuracy is discussed in [
30]. A recent review of PV monitoring systems can be found in [
31], mainly focused on low-cost monitoring proposals. A detailed overview of PV monitoring-system components, such as sensors, controllers, data transmission, and storage solutions, is also included in this work.
According to previous works and contributions of the authors in PV monitoring [
32], this paper proposes a flexible, low-cost, and user-friendly monitoring system based on open-source prototyping boards for PV power plants according to the IEC-61724 standard requirements. The main contributions of this paper are summarized as follows:
PV installations are monitored at the PV-module level according to the current IEC-61724 standard, estimating PV-module performances and providing predictive maintenance.
Low-cost and open-source wireless solutions are used to facilitate the integration of the proposed system in PV power plants.
The wireless solution is flexible and can be adapted according to the layout and configuration of the PV modules.
The rest of the paper is structured as follows:
Section 2 gives a detailed description about the proposed low-cost monitoring solution.
Section 3 describes experimental field tests carried out in a Spanish PV installation connected to the grid. Extensive results and assessment of the proposed solution are also included in this section. Finally, the conclusion is given in
Section 4.
3. Results and Solution Assessment
From the calibrated hardware low-cost solution (
Section 2.3) and the web-application described in
Section 2.4, the proposed system has been tested and assessed in a Spanish PV power plant under real conditions. With this aim, PV Soltec Solar-trakers 250 Wp modules connected to the grid were monitored in the CETENMA SOLAR installations for several months [
83]. To assess the proposed solution, all variables were also measured with standard equipment. Both sets of data were then compared to evaluate the suitability of the proposed low-cost solution. Indeed, solar irradiance was monitored by the Kipp and Zonen CM21 standard pyranometer, also used for calibration purposes in the specific literature [
84]. Meteorogical data, including temperature, relative humidity, and wind speed, were collected using data-acquisition system NI PCI 6221. This data-acquisition card has recently been used for monitoring PV electrical-power generation [
85] and for relative humidity measurement [
86]. Finally, electrical parameters were collected through a HAMEG HM8115-2 wattmeter and Fluke 434 Power grid analyzer. All variables were monitored and managed under an application developed by the authors under a
LabView environment.
Figure 8 depicts the monitored PV installation and the equipment used to assess the proposed low-cost solution.
As was previously mentioned, the proposed low-cost system was assessed for several months to provide the suitability of this solution under real PV-installation conditions. From the monitored variables, the proposed low-cost system was also able to detect possible PV solar-panel abnormalities in line with other contributions [
87].
Figure 9 compares temperature and solar-irradiance data collected by the proposed low-cost solution and standard equipment. In addition,
Figure 10 shows the PV-generated power data from the low-cost solution and the commercial data-logger system, as well as the AC grid voltage. Differences between both collected results have been determined and compared under IEC-61724 requirements.
Table 6 summarizes these differences, including limits of IEC-61724 permissible errors and providing the suitability of the present solution.
The proposed system was also implemented in a real PV solar installation (5 kWp) to monitor and collect electrical and meteorological data during different weeks. This PV power plant is an over-roof installation connected to the grid and located in the Universidad Politécnica de Cartagena, southeast Spain. It involves 18 PV modules Saclima AMS 310 Wp comprising two strings connected in parallel. The selected inverter was Ingeteam 4.6 TL 5 kW. The power demand of this building is always considerably higher than the maximum active power supplied by this PV power plant. Therefore, the generated active power is totally used to reduce the active power demanded by the building.
By considering meteorological and electrical collected data,
Figure 11 summarizes some details of the proposed solution implementation in this real PV installation connected to the grid. Nodes for electric and meteorological monitored data are included in the figure according to the isolation levels required by the nodes under outdoor conditions. PV-module variables are also monitored. As an example of the PV module collected data,
Figure 12 shows electrical data corresponding to both DC and AC variables. PV-module DC current and global DC current provided by the PV installation are also shown.
Figure 13 compares irradiance levels and the active power generated by the PV installations, which are also monitored by the proposed solution. The collected PV-module and ambient-temperature data are also included in the figure. According to these results, the suitability and flexibility of this solution is shown to be able to be applied not only in new installations, but also in PV power plants currently in force.
4. Conclusions
An alternative monitoring system for PV installations is described and assessed. The solution is based on a low-cost and open-source system according to IEC-61724 requirements. The proposed monitoring system collects both meteorological and electrical data at the PV-module level, providing a flexible and wireless architecture capable of being implemented in most PV installations. Sensors have been calibrated in a laboratory environment and the results fulfill the IEC-61724 minimum-accuracy values in terms of current, voltage, and power. PV-module temperature is also available from the proposed solution, with an average error lower than 4%. With regard to economic impact, the proposed monitoring solution cost is lower than current commercial solutions. Indeed, detailed cost information is given in the paper, including sensors and hardware requirements for the gateway and the corresponding nodes.
Different field-test campaigns have been carried out in Spanish PV installations connected to the grid. To assess the proposed solution, monitored data have been compared to data collected from commercial data-logger equipment, obtaining errors lower than 2% for meteorological and electrical variables. Extensive results are also included in the paper. Finally, a web-server interface has also been included to provide external client connection and monitoring. It is based on emoncms, an open-source web application for processing, logging, and visualizing energy and other environmental data.