IEEE Power & Energy Magazine - March/April 2020 - 45

A specific use case has been identified for a strategic
400-kV OHL that supplies the southwest of France. A failure
on another 400-kV line may cause an overload and lead to
a supply interruption for the whole area. Under those conditions, operators must start local thermal power plants to
avoid the potential for a blackout. Since the costs associated
with this action can add up quickly, DLR implementation was
used to prevent them. The strategic line is often exposed to
high and steady wind speeds, offering a better ampacity than
its standard static rating. Within two years, the money saved
from redispatching the thermal power plants covered the cost
of the DLR system.

Determining Critical Spans
and Identifying Future DLR Benefits
The process of deciding to equip an OHL with DLRs can be
divided into two steps. First, it is necessary to evaluate the
benefits offered by DLRs compared to static ratings. Second, the cost of the project can be estimated after choosing the location of the spans to equip with sensors, enabling
a cost-benefit assessment. Software has been developed
to perform these actions. The inputs consist of historical
weather data with high spatial resolution and the characteristics of the line (the type of conductor, maximum conductor
temperature, line profile, and so on). The outputs are DLR
values for each span of the line as a function of time for all
of the historical data. This facilitates the evaluation of DLR
benefits for given spans.
From these outputs, the line's ampacity for each time
period can be deduced as the minimal value of all of the
spans. The benefits of increasing the dynamic ampacity are
analyzed using statistical studies compared to the cost of the
equipment to decide if DLRs should be installed. Moreover,
critical spans, which are shielded from the prevailing wind

or parallel to the wind direction, are highlighted through
these outputs.

Research Project on a Weather-Based Model
Figure 1 shows weather-data acquisition equipment and line
sensors that were fitted to an OHL test installation. The
measurements provided data on
✔✔ the ambient temperature, wind speed and direction,
and solar radiation
✔✔ the span's sag, or ground clearance
✔✔ conductor temperatures.
The project's main objectives are to develop a weatherbased DLR using accurate parameters. The model computes
the transient capacity by analyzing the conductor's dynamic
thermal behavior. It also creates a forecast model that meets
operators' needs by calculating the ratings as a function of
time. The calculation provides a comparison of the DLR
and static ratings based on the conductor's temperature,
which is determined from ambient conditions using IEEE
and International Council on Large Electric Systems methods, with a focus on high-wind conditions. The project will
compare the calculations with actual line measurements.
The first results from the test installation were expected by
the beginning of 2020.

Digitizing OLs: Specific Challenges
The previously described DLR use cases suggest that two
specific technical limitations should be overcome to enable
the scaling-up of smart solutions.
Wireless Telecommunications

Until approximately 2016, the only available technologies to
set up monitoring experiments that required wireless communication were 2G (machine-to-machine solutions) or 3G and

figure 1. The sensor installation on the OHL for the DLR laboratory. (Source: RTE; used with permission.)
march/april 2020	

ieee power & energy magazine 	

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IEEE Power & Energy Magazine - March/April 2020

Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - March/April 2020

Contents
IEEE Power & Energy Magazine - March/April 2020 - Contents
IEEE Power & Energy Magazine - March/April 2020 - Cover2
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IEEE Power & Energy Magazine - March/April 2020 - Cover3
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