The metaverse and energy transition are both evolving on a continuum, rapidly but incrementally changing the way we produce, distribute and consume power, and how the industry engages with its customers. The world of high-performance computing is on a similar evolutionary curve, which will soon reset the boundaries of utility operations as we begin Computing the Impossible.
of utilities executives agree that their organization is pivoting in response to the unprecedented computational power that is becoming available.
The extent to which network management can be automated is limited by what is computationally possible. A new generation of machines will enable network utilities to tackle the challenges at the core of their business models. Problems that are currently considered impossible will become solvable, forcing business leaders to reimagine the most basic assumptions about their enterprise processe
Next generation computing will redefine the art of the possible
In the future, the volume of data created across the energy value chain will be orders of magnitude greater than today. Billions of sensors will create time series data, all of which has potential value to a grid operator. Arguably, the biggest challenge facing the industry in the energy transition is how to make sense of this data, and create value for all stakeholders. All new business models will rely on this data.
94% of utilities executives agree that their organization’s long-term success will depend on the next generation computing they leverage to solve the seemingly unsolvable problems not addressable by classical computing.
However, no single system currently exists that can make real-time sense out of the sheer volume of this time series data. Using today’s computing systems, a grid operator can only analyze a subset of this data in real time, and use estimates and assumptions in grid management. While this approach may work today, it will not in the future. Power quality and outage management will have millisecond requirements, even in low voltage distribution networks.
of utilities executives say quantum computing will have a breakthrough or transformational positive impact on their organizations in the future.
of utilities executives say the same for high performance computing (HPC).
of utilities executives say the same for bio-inspired computing.
A combination of sensor data and digital twins with high-performance, neuromorphic and quantum computing will create a new system of systems for grid management. The time taken to perform calculations will fall from days to seconds to milliseconds, enabling processes that were previously thought impossible. Advances in computing power will allow us to make advanced, sophisticated predictions of anything from climate change to real-time micro transactions across the grid.
AI-based control loops automate network operations
The next generation of high-performance computing will address a fundamental question: who balances the network in a world of inertia-based grid management? Software or humans? Humans cannot make real-time decisions using the sheer volume of data the future grid will create. Human operators will gradually be replaced by AI-based control loops, which will automate network management closest to the point of use.
of utilities executives believe that next generation computing has the potential to destroy their organization’s current business model.
They will help address the capacity challenges caused by ubiquitous EV charging and the intermittency of renewables. Grid operators will use pricing incentives based on real-time insights to balance supply and demand, maximizing the efficiency of existing network capacity.
New technology will enable business models that we can only dream of today. Imagine a world where all assets are connected and controllable – thermostats, EVs, charging stations, solar panels, storage, heat pumps and household appliances. Billions of sensors creating data huge volumes that can be processed in milliseconds – that’s the role these control loops will eventually play. And if a grid operator constantly estimates the network state and correlates it with historic information and external factors, they can make accurate predictions by minutes, hours and days. Once we know that, we can fully automate.
In normal operations, the control loop will automatically send pricing signals to assets across the grid that encourage specific actions. However, when this pricing is insufficient to address the needs of the network, some assets will be temporarily shut off. Human operators will monitor grid and intervene only when required. Importantly, customers will rarely, if ever, notice. For example, a homeowner will not know if their freezer has been told not to turn on its compressor in a two-hour period.
New partnerships. New ecosystems. New processes
By 2037, all the technology required for this new model – distributed energy resources, sensors, and processing power – will be available. The biggest barrier will be the willingness to take humans out of the day-to-day decision-making process. This presents a leapfrog moment for grid operators to redefine the way low voltage networks are managed. However, they will not achieve all these goals on their own. A recent announcement1 from grid edge software vendor Utilidata points to how the industry is changing. It has formed an advisory board with chip manufacturer NVIDIA and executives from American Electric Power, Duquesne Light Company, Holy Cross Energy, PPL, Silicon Valley Clean Energy, and Sunrun. The advisory board will collaborate on the development of AI and advanced computing for grid management.
of utilities executives are planning to partner with others in the next three years to address previously unsolvable problems using next generation computing.
of utilities executives plan to invest in technology or startups to address previously unsolvable problems using next generation computing.
A shortage of skills and the rapid speed of change creates another barrier – the ability to automate at the pace and scale the grid will require. The standardization and modularization of assets across the value chain will accelerate adoption and rapidly change the grid’s needs. The transformational changes in computing will force system operators to seek a collaborative approach to ensure they apply the latest technologies to grid management.
Aggregators, technology vendors, system integrators, and third-party analytics providers will become part of a new ecosystem for inertia-based grid management. Combined, they will help compute the impossible and automate the grid.
1 Utilidata Launches Grid Edge Advisory Board with NVIDIA, Cision PR Newswire, April 2022