We refer to spaces dedicated to the generation and production of energy or raw materials for its production as Energy Parks. These may include various sources such as solar, wind, hydroelectric, thermal energy, or fuel production for later use in energy production. The complexity of data in an energy park is associated with the diversity of technologies and systems interacting to manage the complete cycle of production and generation. Among the aspects that contribute to this data complexity, we can highlight:

• Variety of Processes: Each process generates specific data that must be monitored and managed to ensure an efficient and safe operation.
• Sensors and Monitoring: Plants are equipped with a wide range of sensors that collect real-time data on variables such as temperature, pressure, flow rate, energy consumption, etc. The amount of data generated by these sensors can be vast, and its precise interpretation is crucial for process control.
• Prevention and Maintenance: Managing data related to equipment integrity, preventive maintenance, and failure prediction is essential.
• System Integration: Production or power generation plants often have a variety of information systems, such as distributed control systems (DCS), asset management systems, laboratory information systems, among others. Integrating these systems to achieve a cohesive view can be a major challenge.
• Real-Time Analysis: Decision-making in industrial processes often requires real-time analysis of large volumes of data. Advanced analysis systems are essential for optimizing operational efficiency and responding quickly to changes in process conditions.

Capitalizing on the sea of data generated in this type of industry is crucial for maintaining competitiveness and productivity. Therefore, the design and creation of data platforms that orchestrate and make sense of this information are essential for maximizing the information generated in the complex industrial environment. A good data platform facilitates decision-making, optimizes operations, improves efficiency, and helps comply with regulatory and safety requirements, thus contributing to the efficient and safe operation of the Energy Park.

Data is the new oil, but if it’s not refined, it can’t really be used.

Some of the world’s leading oil companies have entrusted Galeo with the task of helping them design architectures to build data platforms that extract, sort, and exploit the millions of data points accumulated in their distributed control systems; from the data ingestion through industrial protocol connectors like OPCUA, to their selection and upload to the company’s data lakes for business monitoring, including real-time control of process data and device statuses. 

Thus, a well-designed bottom-up architecture enables the construction of digital twins fed with data extracted as close to the process as possible, at the Edge. This allows for the creation of real-time digital representations of physical objects or systems using data collected directly at the site of the events. These are then sent to a remote processing center, where their full potential is unlocked through the application of modern Machine Learning and Artificial Intelligence techniques. This is especially relevant in the context of the Internet of Things (IoT) and edge computing.