I’ve come to depend on the navigation system in my car. It predicts traffic jams, gives me the fastest route, informs me of store hours, and even tells me where to get a burger. To give me this experience, the navigation system draws on multiple data sources, puts it into context, and presents it through a single interface.
In order to efficiently navigate the energy transition, operators in power and utilities must reach the same level of maturity with their data. With multiple sources of data from sensors, to outage logs, to images—all stored in various enterprise systems—this industry won’t be able to unlock the full value of its data until it’s combined, contextualized, and available with less effort. Only then can we use it for a reliable, resilient, green energy future.
Getting to this point will require power and utilities companies to conquer the first challenge: bringing all their data together. Data and information are still extremely siloed in this industry; tucked away in legacy systems, deliberately locked in vendor point solutions, or stored inside the minds of domain experts. In an extremely connected industry, our data continues to remain disconnected in this sense. Additionally, we see all too many isolated digitalization projects that start with high expectations but don’t quite get to scale. We need to change this if we want to start using the data in a way that makes a difference for the industry.
Once the data is combined, power and utilities companies will face the next challenge: creating meaning from all of that data in order to empower the expanding chain of data stakeholders—domain experts, analysts, data engineers, and data scientists. The idea is that once the data is contextualized and understandable, it can be put to use in broader workflows at lower marginal costs while also being easier to quality check and maintain. When the data is connected and meaningful, players can get a birds-eye view of entire workflows and processes such as approving new grid connections or optimizing the performance of a fleet of assets. Data in context is what enables this unique vantage point.
Data made available and meaningful creates the foundation for living digital twins that bring operations to life in a viewable and easily accessible way. The concept of the digital twin has been around for a while now, but they’ve advanced from simply being a virtual model of an asset to now representing systems and processes, so you can simulate and test ideas and scenarios before you actually take action. This is a huge step forward toward identifying potential cost savings and efficiency gains, and hinges on being able to leverage all your data more efficiently with industrial data operations. Adopting and delivering digital twins into your operations creates new opportunities for cost reduction and efficiency. Here’s a breakdown of the greatest potential gains when you leverage a digital twin–based digitization strategy.
Getting ahead of risks will forever be a prime objective across the value chain. With new risk emerging from the intermittency of renewables, to increasing outage risk from aging assets, to capacity risk in the current grid, organizations who master data can observe, simulate, and predict these risks ahead of time. With digital twins at both the system level and the asset level, companies can clearly identify risk patterns across the grid and be better prepared with action.
This data-driven knowledge and awareness is what enables smarter grid planning, more efficient use of existing infrastructure, and predictive maintenance routines, all delivering a clear path toward the more reliable grid of the future.
For power and utilities players to stay profitable and keep up with the evolving (and increasingly renewable) energy sources, they must maximize the performance of their assets. As portfolios expand to include wind and solar alongside traditional generation assets, it becomes more difficult to understand the performance site-to-site.
Improving performance first starts with gaining broader operational visibility of these sites to compare and benchmark expected performance. Then, different operations and maintenance tactics can be applied to deliver more performance at an individual asset level through preventive maintenance and smarter operational workflows. Digital twins can be used as a powerful way to develop the operational understanding needed to maximize performance across distributed asset portfolios. This happens by being able to abstract the inherent data complexity from many different asset original equipment manufacturers, data standards, and sources.
The pace of the energy transition continues to accelerate, and organizations must use their data more efficiently in order to adapt to these new realities. Today, getting data in the right format to answer business-critical questions continues to take significant time and effort. The request may pass through many hands or be put into a project that can take days, weeks, or months.
Digital twins centralize this data in context so that it can be accessed from one place with much less overhead. Not only is this invaluable for ad-hoc questions and analysis, but by having one single source of truth, entire workflows such as connection analysis or predictive maintenance and root cause analysis can be transformed with all information available in one place. While bringing the data together and building powerful digital twins used to take time and effort, automation available with industrial data operations continues to improve the economics of digital twins as a single source of truth.
Evolve the Workforce
In addition to macro workforce changes, there’s no denying that a digital transformation on this scale also creates an enormous cultural shift for any power and utilities company. The workforce will need to adapt to the digital future, both from a skillset point of view as well as in terms of how they collaborate across units. Suddenly, the language of data is an opportunity to bring teams and information together in new ways, sparking new ideas and evolving processes.
Digitalization and automation also marks the end of some of the higher risk and more repetitive manual tasks. It leaves the humans for the more creative work, but it also can create disruptions to the status quo. Humans must learn to speak data, but data is also quickly becoming able to speak “human.”
Untangling Digital Systems with Industrial Data Operations
Power and utility operations are increasingly connected, especially as the industry transitions to the smart grid. Today, there are systems within systems, some of which have been around for decades and each with their own set of unique complexities.
With digital twins and industrial data operations, this complexity can be abstracted away and minimized using new tools and automation that drive efficiency in data process all while empowering new data consumers. This isn’t a vision of the future; this is happening now across heavy-asset industries.
Our energy system is changing, and with it, our power grids must evolve. Just like the navigation system on which I so depend, we must make power and utilities data just as contextual, useful, and reliable, because the journey ahead depends on it.
—Andrzej Golebiowski is senior vice president of Power & Utilities at Cognite AS.