At the end of 2020, Instra Ingenieros began with the commercialization of a new product for photovoltaic parks. The goal is to promote new digital services focused on the management of solar plants, and specifically on asset performance management.
After a few months of contacts and demonstrations, we show you a little more of this solution that we hope will have a great impact in 2021 and subsequent years.
Interface:
What's a good software application without a state-of-the-art, responsive, and easy-to-use interface?
Solar Plant APM, has been thoroughly designed to make the user experience the best possible. Smooth navigation, simple menus and clear information all the time is what Planta Solar's APM interface presents to our customers and end users. In addition, all graphics are interactive, so everything the user sees has a purpose and actions around it.
Modular and flexible:
Solar Plant APM has been designed to be flexible and adapt to different use cases and plant configuration. All menus and views can be configured and with a certain level of customization without changing the installation. Furthermore, the functionality is modular and different modules can be activated or deactivated for the different user profiles defined for the customer's organization.
ML algorithms:
Most companies today talk about Machine Learning and Artificial Intelligence. But only some of them implement algorithms based on those concepts. Solar Plant APM is one of the few products on the market designed for photovoltaic plants that does. How? Obviously, a learning algorithm cannot be efficient or work properly without previous data. Solar Plant APM will collect the historical operation data of the assets, performance and behavior of the facilities and, through the application of machine learning models, created based on historical data, it will extract relevant information about the operation of the assets including the prediction of future failure modes. For the best results, it is desirable to have data from at least 6 months to feed the predictive algorithm. These models generate alerts when a component failure is anticipated in the future, as well as recommendations for problem resolution.
Insurance:
The data is obtained in a secure way, either directly from the photovoltaic plant or from a centralized data server, and is sent to the cloud environment, where secure and independent areas are created for each client where the analytics are executed. The results of the same are shown through graphic representations or through alerts through a secure connection.
Get in touch with us, to carry out a demonstration and a tour of the product as well as to know the cost of the same for an average installation.