Ingeteam will optimize the maximum performance of several renewable energy facilities in  Central America and the Caribbean

Ingeteam will optimize the maximum performance of several renewable energy facilities in Central America and the Caribbean

Ingeteam has signed an agreement to market the services of its application with the energy unit of the Multi-Investment Corporation (CMI) located in Central America and the Caribbean.

It is a web application that provides Business Intelligence tools with the aim of improving the efficiency of the management of the life cycle of the assets. It allows reducing the operation and maintenance costs of any renewable installation, based mainly on:

  • Maintenance analysis with specific indicators such as MTBF, MTTR, monitoring of spare parts consumption, failure rates, troubleshooting, etc.
  • Operational analysis through events tracking
  • Economic analysis by monitoring budgets, market conditions, availability, etc.

INGEBOARDS is completely modular and configurable according to the needs and requirements of the customer. It allows integrating any source of information (SCADA, SAP, CMMS (CMMS), maintenance reports, etc.) with the aim of reusing tools already implemented in the management of the installation.

The company (CMI) has a renewable energy generation business unit with a total installed capacity of 741 MW, divided into 317 MW of hydroelectric energy, 324 MW of wind energy and 100 MW of photovoltaic energy, located in Central America and the Caribbean.

All this power will be integrated into the INGEBOARDS application, allowing the monitoring, analysis and automatic generation of reports and status tracking meters of wind, photovoltaic and hydro assets.

It has different sources of information, like:

  • SCADA data (energy storage systems and solutions), which can also be supplied by Ingeteam.
  • Data from CMMS (maintenance management software), in particular from SAP and Infor EAM.
  • Predictive data, including the integration of data from the vibration equipment they have in their wind turbines.

The implementation phase of the application is already underway and it will be fully operational in less than six months. By then, they will be able to begin optimizing the performance and costs associated with these renewable energy facilities.

Progresses in both technology and current processors make it possible to work with data in previously unproductive or directly unfeasible ways. Taking this into account, Ingeteam's R&D department is developing machine learning models in order to make data much more useful and in order to extract much more value from them.

Ingeteam is currently focusing this development on several projects in which the lines of research range from automatic process optimisation, error classification, image processing to natural language processing in operations, predictive detection of anomalies and component life estimation; the last two being the ones in which the greatest depth and development has been achieved.

Once the models have been developed for each of the problems that arise, the Ingeboards platform allows them to be integrated into the processes so that they are useful on a day-to-day basis, as well as allowing the models to be retrained automatically to obtain a constant improvement in them.