The key criteria used for choosing the optimal location of sensors are:
• Conductor type – if the line is made up of different conductor sections, each section should have at least one sensor on it.
• Ambient temperature – ambient temperature doesn’t typically change significantly over distance. It is considered adequate to put a sensor every 10 km to cater for these changes.
• Wind speed/direction – this is the most constraining factor since wind is very locational in nature. For this we consider the wind direction and speed from historic weather over at least one year. In addition to this, we would consider any significant changes in the orientation of the line (for example a 15 degree orientation change is considered enough to require another sensor). This means that straight lines will typically require less sensors than ones that change orientation many times.
• Clearance issues – spans which have known clearance issues should be monitored directly. This could be because of low clearance head room or different conductor spans.
• Other – Some utilities many include sensors for other reasons, for example for ice or galloping detection.
The average age of conductors globally is greater than 40 years. This means that conductors are often well past their designed lifespan, and little is known about their true health. In many cases, conductor samples from high-risk lines are taken and studied in a lab to asset the state of the conductor for physical damage such as corrosion. Annealing can measured with topographic measurements assisted with conductor measurements such as conductor temperature and load current. However, there is a desire to monitor some high risk lines in a more continuous manner to assess risk and mitigate outages. This monitoring can be divided into two main categories which can be measured with line sensors:
1. Thermal Stress
2. Mechanical Stress
In the case of thermal stress, reasons to monitor this are led by changes in climate, e.g. hotter summers and or wildfire damage or higher currents on lines driven by congestion from more renewables or slower grid expansion lead times.
For mechanical stress, these are typically caused by external factors such as:
• Ice
• Storms/high winds
• Galloping
The Return of Investment (ROI) can be divided into two scenarios:
1. Where congestion reduction is incentivised
2. Where congestion reduction is not of financial concern to the transmission asset owner
In the case of the first option, this means that improvements to congestion can be used in the ROI calculation. Here, the repayment period is often very short like a matter of months, because congestion costs are often very expensive. As an example, when PPL in USA installed DLR on a single congested line, the congestion costs between 2022 and 2023 decreased by $64 million whilst the cost of the DLR system was less than $1 Million.
In the second scenario, where congestion relief is not directly used in the ROI, the benefits are significantly smaller but benefits can still be considered along the following lines:
• Significantly lower cost than traditional rebuild or reconductor
• Improved outage windows for build works
• Deferral of asset build
• Quantified risk on pushing assets/improved operation and maintenance
• Reducing renewable curtailment/increasing renewable capacity
In this case, the ROI is typically closer to 2-3 years unless the cost of outages is prohibitive and DLR can be installed on live line.
Some considerations for weather parameter accuracy
• Wind has the highest impact on DLR – this means small errors lead to big errors
• Wind is locational in nature – utilizing a weather station measurement miles away will not typically yield accurate results. Even weather stations along the same span have shown different results.
• Low wind speeds are turbulent in nature and difficult to measure accurately with anemometers
• When conductor temperature is low (low current through the line), doesn’t reflect the measurement well when current is high
As per the figure above, it is noted that when the current is low (typical for low risk DLR pilots) the different wind speeds yield similar conductor temperatures. However when the current is increased (where DLR matters most), different wind speeds produce significantly different maximum current values (ampacity). When assessing the accuracy of wind speed measurements, researchers are encouraged to examine high current loadings so the inaccuracy in wind measurements can be adequately examined.
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