Beyond SCADA: Why Digital Twins Are the Future of Urban Grid Management

As the urban grid becomes increasingly sophisticated with thousands of renewable microgrids, bidirectional electric vehicle charging and IoT sensors, grid operators are discovering a harsh reality: traditional Supervisory Control and Data Acquisition (SCADA) systems cannot cope with the modern grid's demands.  

Supervisory control and data acquisition systems for centralized, unidirectional power flows now struggle to keep pace with the dynamic, bidirectional energy networks that define modern urban infrastructure. The solution is not more monitoring, but rather intelligent virtual replicas that forecast, simulate and optimize in real time. Digital twin technology is the natural evolution from SCADA, creating complex virtual models of whole city energy grids that both monitor and predict. 

The Critical Shortcomings of Traditional Grid Control

City power grids are confronting significant operational intricacies as grid infrastructures modernize. The underlying issue is that traditional grid technology simply was not designed for two-way power flows and distributed energy resources (DERs). The incompatibility has taken on real-world significance, as evidenced by Australia’s storage curtailment, which is driving minimum demand to critically low levels and sometimes forcing rooftop solar shutdowns or the activation of emergency grid measures.

Data fragmentation compounds these challenges. Even as data volumes balloon exponentially, information remains fragmented in siloed systems. Grid operations teams, Advanced Metering Infrastructure (AMI) departments and other utility departments operate independently of one another, rendering the creation of complete network models a virtual (no pun intended) impossibility. Fragmentation has utilities operating with partial visibility at the very moment they need end-to-end visibility.

Climate resilience contributes to these operational complexities. Aging grids are increasingly vulnerable to weather outages and extended downtime, yet utilities face mounting pressure to do more with less. Capital constraints require targeted infrastructure investments, but in the absence of clear ROI metrics, priorities become a shot in the dark. Most acutely, workforce issues cause risky reliance on institutional memory. When veteran staff retire, utilities lose decades of “tribal knowledge” – operating experience that was never formally documented. Constrained situational awareness and automation capabilities leave operators reactive instead of proactive in overseeing increasingly complicated networks. 

Digital Twins: The Journey Beyond SCADA

Digital twins address these incumbent limitations by building on SCADA's monitoring capabilities while adding core competencies that traditional control systems cannot provide. Where SCADA offers real-time control and reporting, digital twins create dynamic virtual copies that accurately reflect current states and relationships between all the elements of a network.

The technology enables sophisticated scenario simulations that are not feasible or hard to realize with traditional systems. Operators can try "what-if" scenarios in real time, modeling the impact of equipment failure, load shifting or insertion of new renewable resources without physically touching the grid. 

Enhanced visualization is provided by tight Geographic Information Systems (GIS) integration and interactive interfaces. Rather than with canned maps and reports, operators work with real-time, detailed representations of the network showing not just current state, but also future predicted states.

Predictive analytics combined with real-time alerting enable grid operations to be rendered proactive instead of reactive. Rather than responding to issues after they have occurred, operators can diagnose and repair possible issues before they impact customers.

Proven Results from Early Adopter Implementations

Several major cities are leading the way in digital twin implementations: 

• San Diego Gas & Electric has embraced digital twins to model DER simulations and wildfire risk scenarios, addressing California's need for wildfire mitigation directly. They have a platform that enables real-time assessment of fire risk conditions and optimum load rerouting opportunities in emergency situations.
• Austin Energy is employing digital twin technology for real-time grid visualization, asset performance monitoring and customer load modeling as part of their overall smart grid and distributed energy integration programs. The deployment helps support their overall sustainability goals while improving operational efficiency.
• Los Angeles Department of Water and Power worked with universities to model integrated water and energy systems, driving their LA Sustainable City Plan objectives forward using whole infrastructure simulation.

Quantified Performance Improvements

Implementation results have shown considerable operational improvement at several utilities:

• Singapore Power Group implemented the country’s first digital twin to enhance grid resilience, ensure grid reliability and support the integration of cleaner energy sources.
• Tampa Electric's feeder and substation-level deployment supports faster outage restoration and diagnostics, improved accuracy of load forecasting and reduction of peak demand through the optimized dispatch of electricity.
• SP Energy Networks created the UK’s first digital twin to model and test solutions for managing rising electrical demand on the real-life system.  

Although results vary by utility and implementation, digital twins are rapidly transforming the energy sector—delivering measurable benefits such as reduced maintenance costs, faster outage recovery and more accurate demand forecasting.

Changing Operational Strategies

Digital twins fundamentally change the way city energy systems operate on several levels.

System modeling has evolved from ad hoc forecasting runs to real-time simulation capability for immediate scenario testing. Operators can test the impact of maintenance schedules, load transfers or equipment upgrades without disrupting actual operations. Cross-domain integration expands system scope from isolated departmental silos to enterprise-wide network visibility. Rather than managing generation, transmission and distribution in isolation, operators gain integrated views that reveal interdependencies and optimization opportunities. 

Maintenance strategies shift from reactive and preventative frameworks to predictive analytics that anticipate issues before they occur. The shift reduces costs while improving reliability by addressing issues during planned maintenance windows rather than emergency callbacks.

Priority Applications Driving Adoption

DER planning and integration are the most viable near-term use cases. Digital twins enable utilities to consider where to site solar facilities, battery storage, microgrids and EV infrastructure in concert with identifying necessary grid reinforcements. This capability addresses mandated renewable expansion while ensuring adequate hosting capacity directly. 

EV infrastructure planning allows for the simulation of charging load impacts and strategic placement of charging points. Digital twins simulate EV charger roll-out scenarios in cities like Los Angeles and Austin because electric vehicle adoption comes before infrastructure development.

Disaster resilience solutions, including wildfire risk management, allow utilities to model emergency scenarios and optimize response plans. This capability is increasingly valuable as climate change drives more frequent and severe extreme weather events. Predictive maintenance and asset management tools help utilities shift from reactive to proactive maintenance strategies, reducing costs while improving reliability.

Overcoming Implementation Challenges

Digital twins are commonly misinterpreted as simple visualization tools or static models. In reality, they are dynamic, real-time simulations that mirror the state and behavior of physical assets. Every digital instance corresponds to a physical infrastructure component, providing real-time operational status and predictive analytics with increasing AI infusion.

This technology is highly scalable, supporting everything from pilot projects to full enterprise-wide deployments. Such scalability enables incremental adoption, allowing organizations to start with targeted use cases and expand based on demonstrated value.

Deployment does not require significant up-front investment or lengthy timelines. Like many other emerging technologies, successful deployment often begins with small, well-defined projects that build credibility through early wins before scaling to broader applications.  

While technical expertise is needed for initial setup and configuration, the end-user experience remains accessible. Interfaces are designed with operational staff in mind, supporting—not replacing—human decision-making.  

Strategic Implementation Framework

Successful deployment of digital twin technology requires the launch of focused use cases with measurable return on investment. Businesses must establish clear performance metrics and goals before scaling up, allowing the confirmation of technology efficacy in parallel with building internal competency.

Core competency sets are data science competencies for obtaining, cleansing and analyzing complex data sets. Systems integration and systems engineering competencies ensure appropriate real-time streaming of data and system interoperability. Utility operations subject matter expertise ensures that solutions address actual operational issues rather than hypothetical possibilities.

Given the critical nature of infrastructure applications, cybersecurity is a top priority. Implementation teams must integrate security requirements from the design phase through ongoing operations, ensuring protection is built in by design—not added as an afterthought.

Equally important is change management. Adopting digital twin technology and other advanced tools requires not just technical installation, but cultural adaption to predictive, simulation based ways of working. The success of this evolution hinges on both leadership buy-in and active engagement from operations teams. 

The Competitive Advantage

As aging grid assets and accelerating clean energy transitions introduce unprecedented complexity, digital twins are the vital technological bridge between today's SCADA-controlled grids and tomorrow's fully autonomous energy networks.

Utilities that implement digital twin technology now stand ahead of others that depend on traditional grid control systems alone. The technology provides the capabilities needed to solve modern grid challenges: DER integration, climate resilience, predictive maintenance and optimization of operations.

As urban energy systems become more complex, the question is not whether utilities will adopt digital twin technology - it is whether they will do so before competitive pressure and operational stress necessitate it. The most effective utilities are those tackling digital twins not as a future-facing theory, but as a solution for immediate operational challenges.

The evolution beyond SCADA has begun. Digital twins deliver the end-to-end visibility, predictive capabilities and operational insights that modern urban grids need. For forward-thinking utilities, the future of grid operations is here.