Dynamic Line Rating (DLR) Intelligence for Asset and Planning Teams

There was a time when transmission grid operations were relatively straightforward. Loads were fairly predictable, and so was the dispatch of the mostly fossil fuel-based generation fleet. The flow through the transmission network therefore was also generally predictable, and planning the network to be capable of such flows was well understood.

How times have changed. Extreme weather patterns like storms, floods, heat waves, and cold snap all exert a certain influence on transmission behaviors, making them highly dynamic. Renewables generation creates immense difficulty in predicting supply, and load patterns are constantly changing, driven by electrification and data centers.

These challenges put a massive amount of strain on grids. It is thus essential for grid planners and asset managers to closely monitor how their grids are coping with the strain and factor their condition and performance into real-time and future-looking decisions. Line ratings data is a particularly rich source of helpful insights for asset managers and planners.

But too often, transmission utilities must rely on static, inexact line ratings data, despite capacity being anything but static. Static ratings are of little help when trying to maximize capacity, since they may not reflect real-time conditions. Only dynamic line ratings provide sufficiently detailed insights for asset managers and planners to prepare the grid for the future and maximize their existing infrastructure.

Two departments in utility organizations are particularly affected by a lack of dynamic line rating (DLR) data.

One is the Planning team, the professionals tasked with preparing their utility for the future. Many of their responsibilities, including load forecasting, DER integration, resilience simulations, and resource planning, are dependent on accurate DLR data. A planner can neither predict nor prepare for the future without a real-time picture of capacity changes under specific scenarios, which conservative ratings cannot provide. Only DLR data can provide the precise insights planners need to do their jobs.

Another team affected by conservative line ratings is the Assets team, which focuses on the physical health and lifecycle of their grid hardware. They are deeply concerned about how capacity and congestion affect their power assets. The last scenario they want is for one of their precious transformers or conductors to fry or critical lines to melt, all because they didn’t have a clear understanding of line conditions.

Dynamic line rating (DLR) is a data-driven approach to calculating transmission line capacity in real time. It is the antithesis of static ratings, which use fixed, conservative assumptions that don't reflect real-time conditions.

By extension, DLR intelligence, or the insights that reveal line ratings, brings next-level accuracy and precision to line ratings. DLR accounts for factors such as weather observations and forecasts, conductor physics models, and historical weather patterns in calculating line ratings and capacity. With this advanced, data-driven analysis, utilities can analyze line performance under:

The insights from this analysis go well beyond the control room. Planning teams gain better visibility into corridor utilization and upgrade deferral opportunities. This critical intelligence enables utilities to face increasing pressure to transmit more power across aging infrastructure without costly new construction. Additionally, asset teams gain greater visibility into conductor loading and thermal risk across the network.

These capabilities turn transmission capacity from a vague, assumed figure into a dynamic one that utilities can analyze, simulate, and act on, while staying compliant with FERC Order 881.

Even a planner’s best efforts will amount to little if they are not working with precise line ratings data, powered by DLR intelligence. With DLR intelligence available, planners will find it much easier and faster to:

Consider, for example, the scenario tests that planners conduct to test their grids’ performance under certain operating conditions or risk factors. Without DLR intelligence, these tests will often utilize presumptive data based on worst-case scenarios. While this may help utilities plan for the worst, there are plenty of scenarios that may not truly be “the worst,” but still must be tested and planned for. DLR intelligence makes that possible, by providing dynamic data reflecting real-world operating conditions and unlocking precise outcomes and insights.

In addition to helping planners understand how their grid will perform under given scenarios, DLR intelligence can also help them develop countermeasures for any capacity shortfalls. Its precise, hourly insights help planners to separate constraints into two categories, namely those that can be managed operationally and those that truly cannot be resolved without new infrastructure. None of the above can be accomplished when relying on conservative assumptions. With DLR intelligence, planning decisions become less conservative and more data driven.

With DLR intelligence, asset teams gain new visibility into when and how their assets are impacted by thermal stress, i.e., the abrasive effects of heat produced by weather conditions and power flow. Such insights are exceedingly difficult to attain with assumed or worst-case data, as the data seldom reflects day-to-day thermal stress. In addition, imprecise data makes it almost impossible to tell whether underperforming assets are truly being worn down by thermal stress and need replacing or are simply underutilized due to the limitations of static ratings.

DLR intelligence provides more precise insights into thermal stress’ impact on various assets. By analyzing line ratings data, asset teams can:

This intelligence helps asset teams determine when to replace assets or even defer replacements for assets proven to be in better condition than suspected. Every dollar deferred can be re-invested in other areas of higher impact.

As the grid becomes more variable and complex, utilities need planning and asset management approaches that reflect real environmental conditions rather than static assumptions. DLR intelligence provides the analytical foundation to support these workflows for utilities into the future.

For more information on DLR intelligence, check out our solution paper on GridOS® Digital Dynamic Line Rating (DDLR).