Difference between revisions of "Projects:2021s1-13005 Determining Dynamic Line Ratings of Over-Head Transmission Conductors based on Line Tension"

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The ratings  of power  line  overhead  conductors  are  dependent  on the actual  current  flow,  ambient  weather  conditions  and  conductor  type. Thermal  ratings  have  historically  been  calculated  using  a  weather-based model, however, other technologies such as tension monitors to measure phase conductor tension can be utilised to derive ratings. ElectraNet  installed  several  tension  monitors  in  the  Riverland  region  to support power flows over the DC interconnector to Victoria. These tension monitors can independently calculate dynamic line ratings and also verify the results produced using the existing weather based rating method. This project continues work commenced in 2020 to develop a method to convert  tension  measurements  into  ratings  (in  Amps  and  MVA)  and to determine when tension delivers a superior rating outcome to weather.
+
The 2021 iteration of this project continues on from the work completed in the [https://projectswiki.eleceng.adelaide.edu.au/projects/index.php/Projects:2020s1-1540_Determining_Transmission_Overhead_Conductor_Ratings_based_on_Line_Tension project of the same name]<ref name="Proj">[https://projectswiki.eleceng.adelaide.edu.au/projects/index.php/Projects:2020s1-1540_Determining_Transmission_Overhead_Conductor_Ratings_based_on_Line_Tension 2020 Determining Transmission Overhead Conductor Ratings based on Line Tension]</ref> in 2020 by Adrian Barone and James Smithson.
  
 
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* To validate the modelling results against historical line rating data supplied by ElectraNet to confirm that this economic approach is reasonable and feasible.
 
* To validate the modelling results against historical line rating data supplied by ElectraNet to confirm that this economic approach is reasonable and feasible.
  
 +
==Method==
 +
'''Weather-based modelling''' uses thermodynamic principles and relies on measured ambient temperature, wind speed and wind direction.
 +
* Heat generated from solar radiation and from current flow resistive loss is balanced by cooling from thermal radiation and convection from air movement.
 +
* The balance of heating and cooling determines the allowable current, based on a maximum defined operating temperature.
 +
* Natural variation of weather over long distances makes it difficult to determine the weakest line section.
  
 +
'''Tension-based modelling''' uses the relationship between conductor temperature and tension and provides information on the line’s physical state.
 +
* Conductors are typically continuous over multiple spans (Fig.1), therefore tension modelling can capture the average line condition over long distances.
 +
* The weather-based model is still required to determine a line rating from tension-calculated conductor temperature.
  
 +
==Results==
 +
*The tension-based model provides more reliable results during low tension and high temperature conditions, making it ideal for critical operational periods.
 +
*The weather-based model can alternately be used for determining a line rating, with conductor sag and clearance still available from tension-based modelling.
 +
*The tension-based model performs better for line segments with longer spans, where the low point of the conductor falls below the lowest support elevation.
  
 
+
==Conclusion==
 
+
* A combined modelling approach provides a more robust line rating that simultaneously considers the line’s thermal capacity and sag over time.
 
+
* It is also able to capture non-conservative line ratings and sag that is non-compliant with regulations.
 
+
* Tension-based modelling does require a favourable line geometry that contains flatter and longer spans.
 
 
 
 
 
 
 
 
== Introduction ==
 
 
 
Constraints on existing transmission infrastructure is occurring due to the addition of renewable energy generation to energy networks. Operation at the maximum capacity of the conductors is an option to support additional generation on existing transmission infrastructure. The maximum current capacity, or ampacity, of overhead conductors is traditionally kept at a static, conservative level. This is done to maintain clearance levels under the conductors and prevent permanent damage. To fully utilise this infrastructure a Dynamic Line Rating, or DLR, can be used. 
 
 
 
A form of indirect DLR finds an appropriate ampacity through a weather-based model, where weather station data is used to determine the external heating and cooling effects on the conductor. Equalising this with the temperature generated by current flow in the conductor, the ampacity is found.
 
 
 
This project aims to apply a direct DLR method using measured tension in conductors. The measured tension will be used to find the temperature of conductors and determine a suitable ampacity. The models will be compared, and it will be determined as to which provides a superior rating. Work will be done in reference to the ElectraNet owned and operated Robertstown-Morgan transmission line across the Mid-North and Riverland regions of South Australia. This 60km line is pertinent due to its pathing towards the MurrayLink Interconnecter, which connects the South Australian and Victorian energy grids.
 
 
 
The 2021 iteration of this project continues on from the work completed in the [https://projectswiki.eleceng.adelaide.edu.au/projects/index.php/Projects:2020s1-1540_Determining_Transmission_Overhead_Conductor_Ratings_based_on_Line_Tension project of the same name]<ref name="Proj">[https://projectswiki.eleceng.adelaide.edu.au/projects/index.php/Projects:2020s1-1540_Determining_Transmission_Overhead_Conductor_Ratings_based_on_Line_Tension 2020 Determining Transmission Overhead Conductor Ratings based on Line Tension]</ref> in 2020 by Adrian Barone and James Smithson.
 
 
 
== Thermal Factors ==
 
[[File:Overhead Conductor Heat Balance ENetProj2021.png|frame|left|baseline|upright|The various effects of heating and cooling on an overhead conductor.]]
 
There are four main factors when considering the various thermal effects on an overhead conductor. These are:<br>
 
* [https://en.wikipedia.org/wiki/Joule_heating Current Heating](Joule Heating) - Due to resistive and magnetic losses of the conductor material while it is conducting current.  The resistive losses are due to both the conducting material and the increase in the resistance of the conductive material as its temperature increases.
 
* [https://en.wikipedia.org/wiki/Solar_energy Solar Heating] - This is heating due to direct radiation from the sun. Typically, direct solar radiation is difficult to calculate as direct and diffuse solar radiation has various challenges in measuring it (expensive for sensors, need regular attention). In some cases where this data isn’t available, global solar radiation is used.
 
* [https://en.wikipedia.org/wiki/Convective_heat_transfer Convective Cooling] - Convective Cooling occurs per the effect of the air surrounding the conductor heating, reducing the density of the air around the conductor causing cooler air replaces it.  
 
* [https://en.wikipedia.org/wiki/Radiative_cooling#:~:text=Radiative%20cooling%20is%20the%20process,and%20continuously%20emits%20electromagnetic%20radiation. Radiative Cooling] - This is the effect of the material emitting thermal radiation, losing heat in the process. A simplified equation is used as the radiation loss is a small fraction of the total cooling.
 
We do not consider [https://en.wikipedia.org/wiki/Corona_discharge#:~:text=A%20corona%20discharge%20is%20a,of%20plasma%20around%20the%20electrode. Corona Heating] as it is unlikely to occur under typical operation of the conductor, nor [https://en.wikipedia.org/wiki/Evaporation Evaporative Cooling] as while it has a significant effect on cooling, it is challenging to assess along the whole conductor and separated from wind effects, so is ignored.
 
<br>
 
== Useful Links ==
 
[https://en.wikipedia.org/wiki/Help:Cheatsheet Formatting]<br>
 
[https://projectswiki.eleceng.adelaide.edu.au/projects/index.php/Projects:2018s1-101_Classification_of_Network_Traffic_Flows_using_Deep_and_Transfer_Learning Winner 1 2018]<br>
 
[https://projectswiki.eleceng.adelaide.edu.au/projects/index.php/Projects:2018s1-192_Karplus-Strong_Synthesis_of_Sound Winner 2 2018]
 
 
 
{{reflist}}
 

Revision as of 16:10, 23 October 2021

The 2021 iteration of this project continues on from the work completed in the project of the same name[1] in 2020 by Adrian Barone and James Smithson.

Project Team

Team Members

  • Andrew Gross
  • Michael Iuliano
  • Taimur Abdullah Said Al-Sanaidi

Supervisors

Principal Supervisor: Wen Soong
Co-Supervisor: David Vowles

ElectraNet Sponsors

  • Josh Smith
  • Ellen Power

Background

Problem Statement

Transmission lines are traditionally operated conservatively and often below their full capacity. Maximum current flows, termed line ratings, are limited by the maximum allowable temperature of the conductor. This rating depends on the conductor material and is calculated from predetermined, static, worst-case ambient weather conditions. As power generation transitions to renewable energy sources, an outdated line rating method limits the utilisation of renewables, increases the likelihood of line congestion, and necessitates costly infrastructure upgrades or expansion. However, simply increasing current flow causes the line to run hotter, increasing the risk of permanent physical damage from overheating. A hotter line also stretches more, causing more sag and potentially violating regulated safety clearance limits.

A better line rating method is needed.

Problem Aim

South Australia’s transmission network service provider, ElectraNet, is investigating the use of Dynamic Line Ratings (DLR) as part of their risk mitigation strategy. The project aim is therefore:

  • To calculate a DLR using a combination of thermal, weather-based modelling and mechanical, tension-based modelling.
  • To validate the modelling results against historical line rating data supplied by ElectraNet to confirm that this economic approach is reasonable and feasible.

Method

Weather-based modelling uses thermodynamic principles and relies on measured ambient temperature, wind speed and wind direction.

  • Heat generated from solar radiation and from current flow resistive loss is balanced by cooling from thermal radiation and convection from air movement.
  • The balance of heating and cooling determines the allowable current, based on a maximum defined operating temperature.
  • Natural variation of weather over long distances makes it difficult to determine the weakest line section.

Tension-based modelling uses the relationship between conductor temperature and tension and provides information on the line’s physical state.

  • Conductors are typically continuous over multiple spans (Fig.1), therefore tension modelling can capture the average line condition over long distances.
  • The weather-based model is still required to determine a line rating from tension-calculated conductor temperature.

Results

  • The tension-based model provides more reliable results during low tension and high temperature conditions, making it ideal for critical operational periods.
  • The weather-based model can alternately be used for determining a line rating, with conductor sag and clearance still available from tension-based modelling.
  • The tension-based model performs better for line segments with longer spans, where the low point of the conductor falls below the lowest support elevation.

Conclusion

  • A combined modelling approach provides a more robust line rating that simultaneously considers the line’s thermal capacity and sag over time.
  • It is also able to capture non-conservative line ratings and sag that is non-compliant with regulations.
  • Tension-based modelling does require a favourable line geometry that contains flatter and longer spans.
  • 2020 Determining Transmission Overhead Conductor Ratings based on Line Tension