As the market leader in excitation systems, ABB intends to leverage its installed base in this area to provide sensory data and data-driven intelligent insights to help power utilities enhance the availability of power generating units. To accomplish this, the company envisions an innovative digital solution that brings AI-driven decision making to the edge, thus ensuring unmanned, efficient, and resilient power generation with real-time monitoring, predictive analytics, autonomous troubleshooting, asset monitoring and self-optimizing controls to assist operators in various decision-making processes. In striving for this goal, ABB intends to decrease the costs of ownership for electrical equipment within power plants while maximizing units’ availability and reliability, thus providing a key enabler for autonomous, unmanned power plants.

The first step in bringing this vision to reality will be the development of a software solution that leverages live data produced by excitation systems with a view to increasing the mean time between failures of power generating assets. In essence, the software should eventually provide an innovative real-time remote monitoring solution that enables secure, live access to excitation system data through a cyber-secure outbound-only connection. Once fully deployed, the solution will provide plant operators and ABB engineers with a shared, real-time view of system performance, alarms, and diagnostic information that turn operational data into actionable insights to reduce downtime, increase reliability, and support compliance.

Excitation systems are a key component in many power generating units used by plant owners and operators to achieve reliability of operations, stability and fast transient response of their assets, as required by grids¹. ABB’s envisioned solution will glean time-series and event-based data from devices such as its UNITROL® line to which IoT devices are connected. Collected data will include information on excitation voltages and currents, converter status, thermal readings, alarms, trip signals, and firmware versions. In addition, electrical measurements performed through the excitation system — such as generator stator and rotor voltages, currents, and power values — will also be available. The data will not be limited to these parameters: the data collection solution will provide a scalable foundation to acquire information from surrounding equipment as well, enhancing overall data availability, system readiness, and enabling the development of more complete intelligent algorithms.

Data will be streamed to a cloud platform — either ABB- or customer-hosted. For ABB-hosted solutions, Microsoft Azure Cloud will be used. As such, the data’s geographical storage location can be easily configured based on customer preferences in available MS Azure datacenters.

Although designed around excitation systems, ABB does not envision its solution as being limited to this area. The company sees it as also being capable of collecting data from adjacent assets such as turbine control systems (TCS), disturbance recorders, or hyperspectral imaging (HSI). Integrating such data will enhance system-wide situational awareness, root-cause diagnostics, and fleet coordination.

Building on this cloud-based foundation, ABB’s next step will be to extend the solution’s capabilities to the edge. By deploying AI and analytics closer to the source of data — directly within a plant’s network — ABB will enable real-time decision-making even in environments with limited or intermittent connectivity. This edge-based deployment will ensure minimal latency, faster responses to anomalies, and improved data sovereignty, as sensitive operational data can be processed locally. Moreover, by integrating edge intelligence with the cloud infrastructure, the system will combine the scalability and collaborative insights of the cloud with the immediacy and autonomy of local control. This hybrid architecture will create a resilient, secure, and future-ready ecosystem that maximizes operational continuity, reduces data transfer costs, and further enhances the availability and reliability of power generation assets.

Footnotes:

1. ABB. UNITROL Excitation Systems. UNITROL^® Excitation Systems | ABB