A Step Beyond Traditional Ratings
Historically, System Operators have relied on static or seasonal line ratings, which assume fixed weather conditions (e.g., worst-case temperature and wind scenarios) across large areas. Ambient Adjusted Ratings (AAR) improved this by incorporating a few temperature points, but they still lack spatial precision. DLR, by contrast, is a function of highly accurate, localized weather forecasts, using the same standard rating calculation formulas but with real-time or forecasted data on ambient temperature, wind speed, and other factors. This precision unlocks significant grid capacity, reduces curtailment of renewables, and enhances operational flexibility. DLR has two primary applications for System Operators: Planning and Operations. Below, we outline how DLR can be integrated into these processes, along with a proposed solution for seamless adoption.
Planning: Optimize Scenarios from Week Ahead to Intraday
The Planning phase is to play out a number of scenarios to find optimal operating plans for the grid. System Operator needs to optimize between asset maintenance, maximum capacities to market and stable/secure operations of the grid. The grid needs continuous maintenance, but that can't have too big of an impact on the markets and can't hinder the security of supply. For the greatest social benefit maximum capacity should be given to markets, but the network must remain secure and it needs to be maintained. This is why System Operators try to collect the best available data and run through different simulations to find the best balance.
DLR and AAR bring better spatial resolution data to the mix allowing more accurate/detailed modelling of the asset ratings. Assets in the energy sector have big price tags and long life span, so the common approach is to protect the whole grid, but also assets, because loss of an asset can be costly and will take a long time to replace/fix, impacting the whole grid operations. If no accurate data is available, normal engineering approach is to take reasonably worst-case data as basis of analyses, but now as DLR and AAR have become available System Operators can incorporate this data to their existing processes.
In the planning phase, System Operators can use DLR/AAR forecasts to enhance grid models for up to 10 days ahead, enabling smarter outage optimization, capacity calculations, and security analyses. What would it mean in practical terms:
1. Access Forecasted DLR Data: Use APIs to retrieve probabilistic DLR values, AAR and static ratings. These forecasts incorporate hyper-local weather models and line-specific parameters.
2. Update Grid Models: Update planning models/scenarios with forecasted ratings. This ensures planning reflects real-world conditions. This enables the creation of max min scenarios also based on different ratings.
3. Run Simulations: Incorporate created Scenarios to capacity and contingency analyses to optimize outage scheduling and capacity planning.
4. Increase the Available Grid Capacity for Energy Markets: as a result of more accurate models and simulations, more capacity can usually be made available to intraday and day-ahead markets.
By using DLR in planning, System Operators can make data-driven decisions that maximize grid capacity while maintaining safety and reliability.
Operations: Real-Time Grid Optimization
In Operational phase System Operators need to actually operate the grid, very minimal or no time to plan and analyse, the green scenario is nothing deviates from the prepared plans and nothing needs to be done. Thus Operators need to monitor the system and identify deviations from the plan that could lead to issues, react fast to issues that relay protection can't handle and restore stable operations.
DLR brings more information to the Control Room, giving information if planned assumptions on whether parameters align with reality and give indications of potentially overloaded lines, before they are tripped by automation. Also DLR gives information on lines or equipment that has more free capacity, giving the Operator information from which regions they can use reserves in case of an emergency without causing overloading to the grid.
DLR enables control room engineers to monitor line ratings in real-time via SCADA systems, allowing dynamic adjustments to power flows:
1. Real-Time Monitoring: Display DLR values alongside static and AAR ratings in SCADA, providing operators with a clear view of line capacity under current weather conditions. For instance, on a cool, windy day, operators can safely increase line loading to reduce renewable curtailment.
2. Proactive Alerts: Set up automated alarms in SCADA when DLR or AAR approaches safety limits or when power flows exceed forecasted ratings. This enables operators to take preemptive action, such as rerouting power or adjusting generation.
3. Reserve Optimization: Identify opportunities to utilize additional grid capacity when DLR indicates higher-than-expected ratings, or take corrective measures if ratings fall below planned levels.
Integrating DLR into SCADA is straightforward:
1. API Setup: Establish a secure connection (e.g., IPsec tunnel) and IEC 104 protocol for data exchange.
2. Data Points: Agree on data points (e.g., real-time DLR, static ratings) and update frequency.
This setup empowers operators to optimize grid performance during normal operations or contingencies, unlocking capacity that static ratings often leave untapped.
Hybrid AAR and DLR
There are different ways to incorporate DLR to day to day operations, a practical approach could be to adopt a hybrid approach:
1. Use AAR for Week-Ahead Planning: Leverage hyper local Ambient Adjusted Ratings for week-ahead planning, as they provide a steady baseline for longer periods.
2. Use DLR for Two Days Ahead and Intraday Planning and Operations: Deploy DLR in two days ahead, day-ahead, intra day and real-time operations to capitalize on hyper-local weather conditions (wind), enabling precise control over line loading.
3. Set SCADA Alarms for Safety: Configure SCADA alarms to trigger when DLR or AAR falls below static/seasonal ratings or when power flows exceed forecasted ratings. This ensures Operators are alerted to potential risks in real-time.
An example from one of Gridraven's ongoing projects
This approach balances the stability of AAR for medium-term planning with the flexibility of DLR for short-term planning and real-time operations, using the same standard rating formulas but with increasingly accurate weather data.
Practical Implementation Steps
To integrate DLR effectively, System Operators should:
1. Allocate Resources:
- Assign a Network Administrator and SCADA Administrator for integration, similar to integrating Balancing Service Providers (BSPs).
- For planning, involve an Operational Planning engineer to update grid models.
2. Set Business Objectives: Identify critical lines for a pilot, define quality criteria (e.g., accuracy of DLR forecasts), and establish timelines. Compare capacity calculations using static, AAR, and DLR to quantify benefits.
3. Plan for Fallbacks: In case of service outages, use the last available 10-day DLR forecast for up to two days, then revert to static ratings.
Our team provides integration guides, sample code, and support to streamline deployment, ensuring System Operators can test and scale DLR with confidence.
To conclude
DLR is not a new concept, but its practicality has surged with advancements in weather forecasting and data integration. Static and seasonal ratings, while reliable, are engineering simplifications that sacrifice capacity for safety. AAR and DLR with hyper-local weather data unlock the full potential of standardized rating calculations. By integrating DLR into both planning and operations, System Operators can enhance grid efficiency, reduce renewable curtailment, and improve resilience, while maintaining safety.
