The Industrial Internet of Things (IIoT) is proliferating at a rapid pace - while many industries are quick to implement cloud computing and machine learning solutions, the electric power industry has lagged behind.
In five years, the number of devices connected to the Internet will reach 50 billion - doubling the current number of connected devices; over 40% of all data created will be generated by sensors.
Renewable assets and distributed energy resources are playing an important role for utilities as they seek to meet increased demand; however, leveraging IIoT data and analytics is an equally important, critical component of grid modernization. Security concerns, the diversity of systems and devices, and unique operational technology environments are major challenges that must be addressed by any utility seeking to integrate leading edge technologies into the grid.
LiveData Utilities is capable of working with virtually any Common Information Model (CIM) to help utilities create more robust data and enable distributed computing. In the era of grid edge technology employing a CIM is critical in establishing:
Utilize RTI Server middleware as a real-time dataflow engine that manages interconnection of systems and devices, bridges the gap between HMIs (SCADA and others), and embeds business/operational logic. Handling data in real-time with the correct throughput and necessary transformations will allow your data network to function at peak capacity and ultimately allow for greater use of predictive analytics and other IIoT tools.
Open source tools have traditionally occupied lower tiers of OT and IT software offerings, however, as the Internet of Things has become embedded in more places, open source tools have caught up to off-the-shelf offerings. Today, cloud computing infrastructure allows utilities to leverage predictive analytics, advanced pattern recognition, enhanced system management, and many other capabilities that single-source data libraries and engines are incapable of analyzing. By adopting cloud computing infrastructure, rich data analysis can be performed on Operational Technology data – delivering actionable insights without the need for an in-house data scientist. The richest source of actionable insight is via these cloud computing platforms, which have been developed to recognize deeply entrenched patterns that would not be detected by human analysis. Operational Technology data with a Common Information Model applied can be queried with the depth and specificity needed to derive actionable intelligence from pattern recognition and other machine-based data analysis.
When working to establish a real-time analytics program, an existing “real-world” physical connection, frequently referred to as a “Y gateway,” must be exploited to create an exposed model. A Y gateway creates a defined pathway for systems and devices to bi-directionally share or consume system information. In addition to being a high performance configuration tool capable of establishing these Y gateways, OTMB acts as a real-time utility protocol-aware dataflow engine – providing SCADA-class in-memory processing, configuration and manipulation of dataflows at run time, and seamless integrations to IT and OT systems.