Across the United States, utilities are facing a convergence of pressures: rapid load growth from data centers and electrification, rising volumes of distributed energy resources (DERs), and aging infrastructure that was never designed for this level of complexity.
By the end of 2023, more than 2,600 gigawatts of new generation and storage projects were waiting in U.S. interconnection queues – over twice the country’s existing generation capacity. These backlogs increase cost, risk, and stakeholder frustration, and they clearly show that traditional, manual processes cannot keep pace. (Source: Energy Technologies Area, Berkeley Lab)
At the same time, federal programs such as the DOE Smart Grid Grants, which provide up to $3 billion to support grid modernization and resilience, are pushing utilities to accelerate digitalization and data-driven planning. (Source: US Department of Energy)
In this context, Smart Grid Technology is not just a buzzword. It is the digital layer that allows utilities to:
- Understand what is happening across the distribution system in near real time
- Automate interconnection and grid planning workflows
- Use network models and data to prioritize investments
What We Mean by Smart Grid Technology
In this article, “Smart Grid Technology” describes a combination of:
- Digital network models and advanced analytics
- Secure communications and data integration across systems
- Automation of operational and planning workflows
Together, these capabilities help utilities move from static, paper-based processes to dynamic, data-driven decision-making.
Smart Grid Technology connects data, devices, and network models to give utilities greater visibility, automation, and planning capability across the distribution system.
Key Components
1. Grid Data Management and Digital Twins
High-quality, computable grid models are the foundation of any smart grid initiative. A modern grid data layer should:
- Aggregate topology, asset, and customer data from GIS, CIS, AMI/MDM, DMS, and planning tools
- Continuously validate and correct data quality issues
- Provide a “single source of truth” that downstream applications can use for studies and automation
Utilities can support this foundation with solutions such as Operational Data Analysis, Grid Transparency, and Data Manager, which bring scattered datasets into one consistent model and keep them up to date.
2. Communication Infrastructure
Smart grid use cases rely on timely, secure data exchange between:
- Substations and field devices
- Smart meters and back-end systems
- Planning tools, outage systems, and interconnection portals
Whether utilities rely on fiber, RF mesh, cellular, or mixed architectures, Smart Grid Technology needs stable interfaces and APIs that can move data between systems without manual export–import work.
3. Smart Devices and Sensors
Smart meters, voltage and current sensors, and remotely controlled switches create the granularity and visibility that planners and operators need:
- Real-time or near–real-time feedback on load, voltage, and power quality
- Faster fault localization and restoration
- Better state estimation to support advanced grid operations and hosting capacity analysis
4. DER Integration and Interconnection Automation
Smart Grid Technology enables utilities to integrate rooftop solar, battery storage, EV charging, and flexible loads without compromising reliability. Here, three capabilities are especially critical:
- Hosting capacity analysis to understand where additional DERs can be safely connected
- Digital queue management for DER interconnections
- Automated technical screening for standard projects
This is where applications in the Interconnections & Customer Solutions portfolio, such as Grid Connection Study, Online Connection Check, and Grid Connection Navigator, play a central role.
Typical Challenges for U.S. Utilities
Despite heavy investment in systems over the past decades, many utilities still experience:
- Fragmented IT landscapes: separate GIS, OMS, CIS, AMI/MDM, planning tools, and spreadsheets with limited integration
- Manual interconnection workflows: engineering studies prepared feeder by feeder, often with outdated models
- Limited visibility in low-voltage distribution systems: especially where EV charging and rooftop solar adoption is accelerating
- Queue management pain points: difficulty tracking status, impacts, and dependencies between projects
- Aging infrastructure and growing investment needs: planning teams must balance short-term reliability with long-term modernization
Smart Grid Technology directly addresses these pain points by connecting data, models, and processes.
From Concept to Practice: How Smart Grid Technology Delivers Value
The following examples are based on real utilities that have implemented the Intelligent Grid Platform in Europe. The technical challenges they solved – data quality, interconnection automation, system planning – are the same ones U.S. utilities are facing today.
1. Improving Grid Transparency and Data Quality
A German distribution utility, FairNetz, used a smart grid platform to build a digital model of its entire primary and secondary network. By combining network information, metering data, and asset data, the utility was able to:
- Detect missing or inconsistent information (for example, heat pumps that existed in one system but not in another)
- Enrich its network models with corrected and newly discovered customer assets
- Remove 25 MW of obsolete storage heater capacity from the model – about 6% of substation capacity – after cross-checking calculated loads with actual measurements
For U.S. utilities, a similar approach can support:
- More accurate hosting capacity results
- Better prioritization of grid reinforcement projects
- A reliable foundation for DER planning and non-wires alternatives
A natural internal link here is to Grid Transparency and Data Manager, which together provide the tooling needed to continuously improve data quality.
2. Scaling the Interconnection Process
The volume and complexity of interconnection requests is one of the clearest stress tests for Smart Grid Technology.
At E.DIS, a large regional utility, the interconnection evaluation process was previously highly manual. Engineers had to:
- Pull data from multiple systems
- Build or update models for each request
- Run power-flow studies and document results manually
After deploying Smart Grid Technology via the Intelligent Grid Platform, E.DIS:
- Created a fully computable network model fed by automated interfaces to GIS, planning tools, and request management systems
- Implemented an internal workflow to automate the technical review of new DER interconnection requests
- Launched an Online Connection Check on its website, enabling customers and installers to perform a self-service, non-binding hosting capacity check and identify technically feasible points of interconnection on their own
The impact:
- Significant reduction in manual engineering effort
- Faster turnaround times for interconnection studies
- Fewer speculative requests entering the queue
For U.S. utilities dealing with long DER queues and regulatory scrutiny, similar capabilities can be delivered with:
- Grid Connection Study for automated technical studies
- Online Connection Check for self-service hosting capacity insights
- Grid Connection Navigator for structured queue management and decision support
3. Speeding Up Engineering Studies
Another utility, Syna, operates close to one million points of interconnection. Historically, grid compatibility studies for larger projects could take up to eight hours of engineering time per request. After implementing a digital twin and automated study workflows:
- Grid compatibility checks that once took a full working day can now be completed in about 15 minutes
- A dynamic network model is updated daily, ensuring that queued projects and network changes are reflected in the analyses
- The utility can reserve capacity for approved-but-not-yet-built projects directly in the model, improving accuracy for subsequent studies
For U.S. utilities, this kind of automation not only improves customer service and stakeholder relationships, it also helps:
- Free up engineers for complex cases and long-term planning
- Reduce rework caused by outdated models
- Improve compliance with interconnection timelines set by commissions and tariffs
4. Scenario-Based Planning for Urban Growth
Helsinki’s municipal utility, Helen Electricity Network, faces rapid urbanization and aggressive climate targets. To ensure its system can support future load and DER patterns, the utility:
- Developed multiple long-term scenarios (5, 10, and 15 years) for heat pump adoption, EV charging, and rooftop solar
- Integrated building data, smart meter time series, and network topology into a unified digital twin
- Used the Grid Study application (aligned in the U.S. with Grid Scenario Simulator) to identify future bottlenecks and prioritize reinforcement investments
Equivalent capabilities for U.S. utilities are available through the Planning & Grid Modernization portfolio, including Grid Upgrade Designer and Grid Scenario Simulator, which support scenario-based analyses and investment planning.
How Smart Grid Technology Changes Day-to-Day Work
Smart Grid Technology is ultimately about enabling teams – planners, interconnection engineers, operations, regulatory staff – to work with better information and more automation.
For Interconnection Teams
- Automated screening of standard residential and small commercial projects
- Consistent technical rules applied system-wide
- Traceable decisions that can be reported to regulators and customers
For Planning and Engineering
- Access to up-to-date network models that reflect current assets, switching states, and queued projects
- Ability to run “what-if” analyses across multiple feeders and voltage levels
- Better alignment between near-term reinforcement work and long-term modernization strategies
For Customer and Regulatory Stakeholders
- Transparent, predictable interconnection timelines
- Data to support customer communication around hosting capacity and constraints
- Evidence of prudent, data-driven investment decisions
Where to Start: A Practical Path for U.S. Utilities
Many utilities hesitate because Smart Grid Technology can sound like a multi-year transformation program. In practice, most successful utilities follow a phased approach:
- Establish a digital grid model and data governance
- Consolidate data into a central grid model with Grid Data Management and Grid Transparency.
- Identify and fix critical data gaps that block automation.
- Automate high-volume DER interconnection steps
- Use Grid Connection Study to standardize and automate screening and detailed studies for common project types.
- Offer Online Connection Check for non-binding self-service hosting capacity checks.
- Expand into advanced planning and grid modernization
- Introduce Grid Upgrade Designer and Grid Scenario Simulator to align investments, DER strategies, and reliability targets.
- Iterate based on measurable outcomes
- Track cycle times for interconnection requests, the share of automatically processed projects, and the accuracy of planning studies.
Conclusion: Smart Grid Technology as a Strategic Asset
For U.S. distribution utilities, Smart Grid Technology has moved from “nice to have” to “essential infrastructure.” It is the key enabler for:
- Managing rapid load and DER growth without compromising reliability
- Reducing interconnection backlogs and queue management complexity
- Making better, data-backed decisions on where and when to invest
By combining high-quality data, digital twins, automated workflows, and scenario-based planning, utilities can operate more efficiently today while preparing the distribution system for the demands of the coming decades.
If you’d like to go deeper, the next logical step is to explore:
These Smart Grid Technology building blocks give utilities the tools and transparency they need to modernize the system – step by step, with a measurable impact.