 Good afternoon. Thank you all for your presentation, for your assistance at the presentation. I am Gavinal Monafib from the University of Haeng. Let me present to you the Proposal Opera, a digital transformation journey to the best operation and maintenance in photovoltaic solar energy system. Renewable energy in general and photovoltaics in particular are growing and expanding exponentially due to the fact that they are reaching, first, competitive cost with conventional electricity power and second, technological maturity and reliability as well as other well-known relevant advantages such as scalability, environmental benefits, etc. As an example of this, I highlight here some phrases from the global market outlook for PV by solar power Europe for the period 2016-2020. Between many other things, they say the cost of utility-scale solar increasingly beats conventional power plants today. For example, the bidding price in a recent solar tender in Dubai was 2.99 cents of dollar per kilowatt hour. It is really cheaper than many conventional sources of energy, electrical energy. They say also distributed solar is cheaper than retail electricity in many countries. For example, in many places of south of Europe, the price of solar electricity is around or below 10 cents of euro per kilowatt hour. It is cheaper also than the retail price of electricity. In the world, the PV energy are going toward 700 kilowatt worldwide install on 2020. To emphasize all of these, I show in this slide several recent news about renewables. You can see a lot of them every day in newspaper, in TV or any other media. Anyway, I would like to note the special interest to apply data technologies in energy sector. The capacity for renewables has overtaken fossil fuels in great retailing. It is another relevant example of the growth of renewable energies today. It is also important to note that investment in PV is most of the made in renewables. And also the one made in energy smart technology is very important as well, as you can see in this slide. From the report of the National Renewable Energy Laboratory, one of the most relevant institution in the world, regarding renewables and mainly in photovoltaics, we can set the present market value of operational maintenance in PV. It is around 10,000 million euros worldwide. In Europe, it is about 1.7 million euros. And in Spain, only in Spain, it is around 85 million euros. I would like to point out that the first suggestion of this report to cost reduction in PV operation and maintenance is to develop and implement management software. Our business proposal is to provide services on management for operation and maintenance in renewable energy installation. Only PV at the beginning, enhancing the performance of the system, the asset management, and with a significant cost reduction in both operation and maintenance and in the service provided. It will be possible with the Opera Digital Platform and also with a new data collection system. Opera is a low-cost digital platform based on big data and business intelligence tools. And the second is a low-cost data collection system. It is a low-cost and real-time data collection system based on Internet of Things sensors. Both have been developed by an interdisciplinary team led by the University of Hein. Finally, it is important to highlight that this proposal is focused on one of the present-day issues in the energy sector. Who are we? We came from the Solar Energy Research Group of the University of Hein, who have been working on PV technology and engineering for the last 30 years. This photo and the other one shown in the next slide has some view of the Universe PV generator, a PV system reconnected in our University campus. The photo was taken around 1995 when the Universe project was being installed. Our most relevant milestone are shown in this slide. Between them, I would like to point out the Universe project, a very relevant project in this time. This work provides relevant contribution to grid-connected technology. But mainly, I would like to say now to emphasize the worthwhile knowledge and experience that are usually at the University. And in my opinion, the business sector should make the most of it. Let me know to present you a general overview of the Opera Digital Platform. This is a general view of the system based on the Opera platform, data science, data infrastructure, data collection and the dashboard reports and Alan outputs. Opera is coming to follow the idea expressed in the figure of Gardner. Show in this picture. From descriptive to prescriptive analysis. From what happened to how can we make it happen. Regarding the data infrastructure, Opera is a distributed big data platform based on an under-architecture with an string processing platform to publish, store and subscribe to string of data, a distributed computing framework for near real-time processing of the string data, a search engine for the string in this sheet plus visualization, plugging for near real-time monitoring, a machine learning framework for predictive analytics of batch data, and also a distributed file system for a scalar storage of big data. Well, now I must tell you that really I am not the specialist of this area of the proposal, and I am afraid I will not be able to say much more about data infrastructure. Anyway, go on. Regarding the data processing, we walk away starting from the input data that is to say the specification of the manufacturer, the meteorological databases and the real-time collected data from our system. We go on calculating the different performance indices and actual behaviors from the actual operation data in parallel with the simulated ones to compare also in near real-time the actual and simulated data, generating the corresponding alarms when there is no conversion. Lastly, the corresponding reports on operating results and operating maintenance as shown are prepared. This result feedback the process to optimize the system model and the operation and maintenance recommendation. Now, I would like to show you the most important aspects of opera data collection system. In this slide, we can see the block diagram of the data collection system. On the left side, there are several sensors to collect the data of the actual operation of the system, current intensity, voltage, and power meter and grid analyzer if necessary. And also, the radiation and temperature data sensors. The walking data sensors usually are wire-connected due to they are close to the central unit, and the two ambient sensors, temperature and radiation, usually are wire-connected via radio interface or similar due they are often away from the central unit. Everything else in the model is a microprocessor based central unit to send the collected data to the internet. Now, we are using opera prototype to monitoring operation and maintenance the Univer PV generator. In this slide, we can see the microprocessor unit, the white block, and the voltage sensors of data collection system, the black ones. There are two voltage sensors because there are two sub-generators to monitoring. And now, we can see the irradiation and temperature sensors together with the autonomous power supply device. This is a block diagram and picture with a detail of the device that make up the standalone power supplies. A PV micromodule, a lithium battery, and charge controller. They power the wireless interface. Finally, regarding the data collection system prototype implemented in the Univer generator, we can see in this picture the two sensors to monitoring the current intensity of the two sub-generators. There is a very, usually in the PV generator, there is a very high current intensity DC current. Let me show now a few slides related to result, an interesting, some interesting sample of the opera prototype working on the Univer generator. This is an illustrative picture of a possible dashboard with an information of the place and working parameter of the system and their analysis. Now, we can see a picture of the actual working data of the Univer generator 1 in a recent past week. We see the plot of the current intensity at left, the voltage at right, the simulated and measured power generated in the middle left and also the temperature, the room temperature, the simulated cell temperature and the measured cell temperature in the corner left down. I would like to note several matters in this picture. It's the same than the first but with more detail. First of all, the good matching between radiation and current, the simulated and measured cell temperature and even the shape of the voltage set the good accuracy of the PV model. However, the plot of the generated power shows that the simulated power is overestimated and the cell temperature is high. This should make us question the model for high cell temperature. In this slide, we can see a detectable malfunction because the simulated power is matching the radiation but the actual one not. Besides, we can see up to three tries to automatically go up power but pull down again. So it was necessary to send a service technician to turn on the inverter. It had been go down due to an electric insulating fault. I would like to show now a connection, an impression connection with the opera in this moment. We can see, I think in this moment, this is the actual operation of the universe project just in this moment. It's a similar plot that we show in the previous slide but now it's real. In this moment, we are looking what are happening in the universe project and we can release the directive, the recommendation for operation and maintenance. We can see not only today but yesterday or last week or last 15 minutes. This very flat in only 15 minutes or this week. Really, this week the radiation was go down day to day and so the energy. This shape of the voltage is in congruence with this fault because here the voltage is high because there is no generating any power. Well, going to end, in the next future we need to develop dependent matters. That is to say, mainly all topics regarding machine learning and distributed file system and also the dashboard and the reports according to the standard EIC 61724. To do it, it would be very welcome early adopter to be able to run opera in new PV facilities. Also, research and developing collaborator to help developing dependent meters and also stakeholder to help us in financial matter. Finally, as a conclusion, I would like to voice again here the two takeaway ideas of the proposal. New data technologies provide an opportunity for business in renewable energy sector and opera digital platform, a digital transformation toward to the best performance and profit of PV technologies. Thank you for your attendance. Any question? It's impossible to see nothing with this light. Well, thank you very much.