Fingrid Enhances Load Frequency Control with GE vernova's GridOS

Author Sticky

Dr. Andrew Gillies

Chief Technology Officer, BSc., MSc., PhD

Grid Software, GE Vernova

Dr. Andrew Gillies leads the GridOS® architecture and technology strategy for Grid Software. Since 2015, he led the early validation of the modern transformative technologies that now form the core of the GE Vernova GridOS® strategy. In 2019, bringing together orchestrated microservice architectures, containers, Kubernetes, Kafka, and other cloud-native technologies, he and his team operationally demonstrated a full suite of real-time Wide Area Monitoring System (WAMS) analytics and successfully delivered one of the world’s largest WAMS using this technology. Andrew played a key role in the Inertia innovation project, contributing to machine learning architecture and successful deployment on private cloud infrastructure. Together with teams in Edinburgh and Massy, he has been instrumental in the development of Load Frequency Control applications, expanding the modular portfolio into grid automation. Prior to GE Vernova, Andrew led global operations for Psymetrix, a startup focused on WAMS synchrophasor-based solutions. Additionally, he co-authored "Principles of Computational Modelling in Neuroscience" by Sterratt, D., Graham, B., Gillies, A., Willshaw, D., published by Cambridge University Press in 2011.

Mar 27, 2025 Last Updated
3 Minute read

One of the toughest challenges transmission grid operators face today is the integration of renewables as part of the wider energy transition. As renewables penetration amplifies, so do the challenges associated with intermittent power generation. That’s because intermittency introduces variability that makes it incredibly hard for transmission grid operators to guarantee a reliable flow of power for their customers.

The European Network of Transmission Operators (ENTSO-e) has been driving automation and optimization efforts to help manage this balance across Europe, and this is very important in the Nordics, where power grids are coupled and balance is key. Coordination of load frequency control (LFC) is an important part of the solution, and Fingrid joined forces with GE Vernova's grid software team to develop LFC in a modular and expandable way that addresses requirements mandated for electricity balancing.

Today, Fingrid uses GE Vernova's Advanced Energy Management System (AEMS) software to help enable orchestration of renewables at scale. The AEMS is compatible with GridOS® – the first software portfolio designed specifically for grid orchestration – which means it integrates with AI-driven GridOS applications across the grid to better support and/or leverage an evolving ecosystem of grid orchestration solutions. This gives Fingrid access to modern, more flexible capabilities that help automate grid balancing and control processes and led to the rapid development of a new GridOS LFC module.

Here is a look at three GridOS benefits Fingrid is realizing today as it leans into LFC:

Better Grid Automation

European utilities, who must comply with ENTSO-e’s network codes, are working quickly to optimize utilization of secondary reserves. Modular GridOS applications like Load Frequency Control, which can deploy quickly to serve a specific use case, are helping utilities manage the complexity of these fast-changing regulations.

The GridOS LFC module continually monitors frequency changes caused by various types of power fluctuations. When the solution detects a fluctuation, it quickly determines how to best respond and automatically adjusts generator frequency back to its nominal value. GridOS LFC fully meets the requirements established by ENTSO-e System Operation Guideline (SOGL) and market guidelines like the Electricity Balancing Guideline (EBGL). It can also be integrated with the Platform for the International Coordination of Automated Frequency Restoration and Stable System Operation (PICASSO) platform.

By automating the control process with GridOS LFC, Fingrid is working to better protect its transmission grid and ensure a steady flow of power to customers.

Improved Data Availability

Orchestrating the modern grid with all its complexities requires an enormous amount of data. However, much of that information has traditionally been hard to access because outdated point solutions typically hold data within silos.

The GridOS portfolio provides a better way forward. Applications that run on the GridOS platform are able to leverage a federated grid data fabric designed to break down data silos, improving visibility and access to energy information. Having easier access to a variety of relevant, important energy data unlocks the use of digital twins – empowering utilities to not just enable automated grid control, but also model the grid for simulations and predictive operations. The modern grid cannot afford to have crucial data within a tight silo. Data must be in an open, accessible platform to reap its full benefits.

Microservices-Based Architecture

GridOS Load Frequency Control benefits from a microservices-based architecture. In contrast to traditional monolithic architectures, a microservices-based architecture structures an application or module as a collection of services that are:
  • Independently deployable and scalable to meet a specific business use case
  • Loosely coupled
  • Able to operate collectively to achieve a common outcome
Because of this architecture, Fingrid was able to more quickly and easily deploy GridOS Load Frequency Control and will be able to adapt the software to accommodate changing market rules as they evolve. Such updates may even be done in real time, with little to no disruption to power flow.

Fingrid leverages GridOS LFC every day to meet its ENTSO-e requirements and satisfy the demands of a grid powered by more and more renewables. It is an important asset in Fingrid’s control room that helps ensure a steady and reliable flow of power as the utility navigates the variability of renewables

For more information on why Fingrid uses GridOS, watch “How GridOS helps Fingrid navigate the energy transition.”

Author Section

Author

Dr. Andrew Gillies

Chief Technology Officer, BSc., MSc., PhD
Grid Software, GE Vernova

Dr. Andrew Gillies leads the GridOS® architecture and technology strategy for Grid Software. Since 2015, he led the early validation of the modern transformative technologies that now form the core of the GE Vernova GridOS® strategy. In 2019, bringing together orchestrated microservice architectures, containers, Kubernetes, Kafka, and other cloud-native technologies, he and his team operationally demonstrated a full suite of real-time Wide Area Monitoring System (WAMS) analytics and successfully delivered one of the world’s largest WAMS using this technology. Andrew played a key role in the Inertia innovation project, contributing to machine learning architecture and successful deployment on private cloud infrastructure. Together with teams in Edinburgh and Massy, he has been instrumental in the development of Load Frequency Control applications, expanding the modular portfolio into grid automation. Prior to GE Vernova, Andrew led global operations for Psymetrix, a startup focused on WAMS synchrophasor-based solutions. Additionally, he co-authored "Principles of Computational Modelling in Neuroscience" by Sterratt, D., Graham, B., Gillies, A., Willshaw, D., published by Cambridge University Press in 2011.