## 4 Conclusions  
The increasing number of PV installations connected to the grid requires that their operation be perfectly characterised in order to improve their efficiency and control their impact on the electricity grid. For this to be possible, the plants must be monitored and generate data that, after processing, can be converted into useful information to help in the O&M of these renewable sources and the management of their injection into the grid. However, the large amount of data generated in the monitoring of even small plants makes it essential to use tools that help in the management and processing of all this data. For this purpose, in this work, firstly, an RDBMS was implemented to store in an orderly manner all the information corresponding to the technical specifications of the plants to be analysed, and a process was developed to automatically load all the data measured in them into the database tables created. A web application was also developed, which, when connected to the databases, allows us to have selective access to the stored information. The system makes it possible to homogenise the data recorded in different plants, which, as mentioned above, have different specifications, recorded parameters, nomenclature, units of measurement, or format of the recorded data. This makes it possible to treat data from different types of plants together and to perform the same type of analysis in order to compare results. The system was developed with open-source software tools, which avoids the payment of software licenses, making the system much more affordable. Although the manufacturers of equipment for PV installations have applications to visualise recorded parameters, the system developed in this work allows access to the data in a much more broadly and aggregated form, in order to perform more comprehensive and varied analyses than the limitation presented to users by other applications. As an example, this work includes the analysis, using the developed tools, of some of the parameters recorded in two PV plants during a period of 20 months. The system allows access to the temporal variation of each parameter in order to obtain information on deviations that allow maintenance actions to be improved, to avoid reaching the point of corrective maintenance. For example, a mechanism is presented that allows us to make a daily comparison of the power generated by the different inverters of the same plant such that a deviation in the production of one or more inverters can be detected. Colour maps with the Pearson correlation indexes corresponding to the linear dependence relationships of the production of all the inverters of the plant, easily generated with the use of Python, allow us to visualise these possible deviations. As a further example, in the analysis of the grid voltage values measured by the inverters of the plants, the increase in grid voltage that occurs due to the production and injection into the grid of the power generated in the plants was easily seen. The developed system is flexible and scalable, such that the type and number of PV plants analysed with it can be increased. Although the system does not work in real-time, it allows the data monitored in the plants to be uploaded daily, so that production can be analysed in the shortest possible time in order to detect possible deviations from correct operation as soon as possible. There are several aspects in which this line of work could be continued. On the one hand, although the user interface of the application has been designed to be easy to use, it is always possible to improve it in order to make it more attractive to the user. Also, the system has been optimised compared to previous versions in order to make it more flexible and optimal so that the loading time of the data is lower, but this is always an aspect that can be improved, especially for loading data from PV plants with a large number of inverters.