Balancing energy demand and supply is increasingly challenging in today’s evolving energy landscape. New technology approaches are required to address these challenges. A key element is merging information technology (IT) with operational technology (OT). Grid operators are starting to leverage cloud- and edge-based solutions to enhance smart grid management, optimizing performance and ensuring resilience.
Many network operators are hesitant to migrate OT control systems entirely to the cloud. However, the key challenge is not complete migration, but finding solutions where cloud-assisted systems enhance and complement traditional OT environments. This “softwarization” approach boosts the capabilities of OT by adding cloud-powered analytics, predictive maintenance, and near-real-time decision-making without fully replacing the existing infrastructure. By creating a multi-tiered approach to systems control, OT systems gain from the efficiency, scalability, and reliability of cloud/edge-based analytics and control, helping grids respond proactively to demand fluctuations and operational shifts, thereby improving both performance and stability.
Aging grid infrastructure faces challenges as the energy transition puts more demands on grid reliability that’s crucial for uninterrupted energy distribution. Achieving this requires IoT and AI cloud systems for self-maintenance and bidirectional power flow enablement. This supports renewable energy expansion, including infrastructure upgrades and advanced storage systems such as batteries, thermal storage, and flywheels for managing power fluctuations. AI-powered cloud analytics optimizes operations, addressing energy imbalances and enhancing demand-side management. Integrated with an edge-cloud infrastructure, these technologies improve flexibility, predictability, and control. We envision a three-tier approach, combining locally autonomous SCADA-based real-time monitoring with OT edge cloud systems, and cloud analytics for a resilient, future-ready grid with full business control.
Core control systems will remain critical to manage the power grid. In the future, these can be augmented with edge devices already in the substations. These devices can process information from sensors and interfaces locally, adding intelligence to the grid and providing local autonomy while minimizing data flows. This will increase control while also providing redundancy against severe outages. Individual sectors can run on their own with basic operations in case central control is interrupted.
In the second tier, OT data can be aggregated in an OT (edge) cloud. Whilst still being part of the secure OT environment, this layer can be built and run according to cloud and software design and operational principles, thus bringing the rewards of that approach to the OT domain. Benefits of this softwarization and virtualization approach will be greater flexibility, increased scalability, faster development and rollout cycles, lower costs, better control, faster speed of reaction, and a significantly improved robustness of the smart grids.
Cloud solutions at this layer can locally automate energy dispatch and resource allocation, ensuring that the grid responds seamlessly to fluctuations, maximizing resilience. In this tier, raw data can be aggregated into relevant information using AI and machine learning technologies, thus facilitating use cases both in energy management and maintenance. As the grid evolves from a distribution grid to a collection grid (integrating the various decentralized renewable energy sources), the functionality of this layer can easily adapt as the physical infrastructure changes.
Further, more long-term-oriented cloud-based analytics will then be implemented on the IT side where traditional processes such as asset management, HSSE, warehousing and sourcing, and finance/controlling will be supported. Data can be stored in data lakes for archiving and long-term trend analyses. Powerful, cloud-based AI capabilities will be available in this tier for, e.g., agentic process automation, bringing in even more efficiency to utility operations. With this last stack, the vision of a fully data-centric utility is close to completion. Tier 3 applications improve the operating efficiency of Tiers 1 and 2. Real-time data provides deep insights into grid performance, enabling energy providers to make data-driven decisions.
As the transition to renewable energy accelerates, Transmission System Operators (TSOs) and Distribution System Operators (DSOs) must match volatile supply and demand in real time. As the demands on the networks grow, network costs become a significant part of consumers’ and businesses’ energy bills. Smart IT, communications, and cloud technologies can play a significant role in reducing the investment demands for new and upgraded physical infrastructures. Our three-tier architecture provides a conceptual framework towards this solution by combining real-time monitoring, OT/IT integration, and cloud analytics. Predictive analytics based on data from weather forecasts and predictive consumption forecasts, for example, allow energy providers to adjust supply in advance. This prevents disruptions, ensures reliability, and maintains efficient grid operations.
T-Systems brings deep experience in telecom network stability and IT/OT convergence, making it uniquely suited to support energy grids. T-Systems’ expertise in telecom OSS/BSS convergence can be leveraged for energy grids. Combining its connectivity knowhow with its AI and cloud expertise based on own platforms and hyperscaler partnerships, T-Systems can play a key role in the smart grid and IT/OT transformation.
By integrating OT systems with IT architectures, energy providers can create a flexible, scalable environment that adapts to changing demands, paving the way for a more resilient and future-proof smart grid. By leveraging its telecom experience, T-Systems helps energy providers to adopt cloud-enabled architectures that improve grid reliability, flexibility, and security. This convergence enhances decision-making with advanced analytics and predictive capabilities, ensuring that energy grids are not only stable, but also future-ready.
Cloud technology is central to building resilient, adaptive smart grids. By integrating the OT cloud, energy providers streamline real-time operations such as load balancing and energy distribution without overhauling hardware. This strengthens traditional OT systems while ensuring infrastructure security. The analytics cloud adds value by providing predictive insights, enabling data-driven decision-making to optimize grid performance and prevent disruptions, ensuring the grid is ready for future challenges.
Building and operating a smart grid is an ongoing process requiring continuous optimization and stability. By embracing the cloud approach to OT, energy providers can revolutionize their grid operations through a strategic three-tier approach:
Embracing the cloud approach to OT doesn’t just support smart grid operations – it revolutionizes them. With cloud-powered real-time monitoring, enhanced analytics, and a robust IT/OT convergence, energy providers can build grids that are not only resilient, but also ready for the future. T-Systems' expertise in bridging OT and IT ensures your organization is well-positioned for success in this growing, complex market. The future of energy is smart and limitless – with cloud technology empowering it every step of the way.
