Xcel Energy’s digital twin – created in collaboration with EY US – integrates fully with the utility’s core systems. It allows for rapid, detailed data mining and enhanced understanding of energy consumption and system operations while increasing real-time transparency and improving regulatory reporting.
Through the digital twin, the utility is evolving its systems and business processes to enhance customer satisfaction, lower operating costs and create new value streams.
For example, distribution operators use the tool for visualizing, planning and managing assets, including advanced meters, transformers and feeders.
That enables the utility’s engineers to identify overloaded transformers, reduce blackouts and monitor voltage irregularities proactively to advance the promise of a highly available, reliable and resilient grid. By proactively using these tools, the utility can save significant dollars compared to the cost of rolling trucks to manage incidents.
By leveraging high-volume AMI data, the grid visibility tool (GVT) supports efficient capital deployment for asset upgrades and addresses grid reliability challenges, particularly rising demand from increased electric vehicle adoption. While similar systems have existed, the digital twin is an unprecedented productivity enhancer, especially in proactive diagnosis.
Increased insights into momentary, sustained and nested outages allows for more rapid response. And maintenance and equipment replacement can be managed more efficiently. For example, Xcel Energy now can quickly identify faulty residential or commercial meters so they can be replaced quickly – helping protect revenue. The ability to send crews to the right place at the right time enhances service and saves significant costs .
Energy demand forecasting is built on this data platform, too, which makes use of statistical modeling to create load forecasts to be used by the utility in its rate cases in regulatory proceedings, leading to the decommissioning of legacy tools that did not perform such analysis with high accuracy .
The initial success of the digital twin – wrangling AMI data into a value-generating tool – is inspiring its use on a broader scale. Today, the enterprise is increasingly becoming stakeholders in its broader implementation.
For example, a regulatory support team used insights to better support regulators in making well-informed decisions. Demand planners now size up the right demand-side management programs and incentives to reduce peak load. Operators can tell when asset thresholds aren’t bypassed. And integrated capital planners can identify assets to improve based on recommendations derived from real data.