Dynamic Thermal Ratings for Overhead Lines

1
Dynamic Thermal Ratings for Overhead Lines

• Philip Taylor, Irina Makhkamova, Andrea Michiorri
• Energy Group, School of Engineering
• Durham University

2
Overview

• Research Overview
• Overhead Line Thermal Modelling
• Lumped Parameter
• Computational Fluid Dynamics
• Comparisons
• Thermal State Estimation
• Further work

3
Research Aims

• The use of dynamic thermal ratings to
• Increase utilisation of existing power system
  assets.
• Facilitate increased capacities and energy yields
  for DG
• Develop a real time controller

4
Project Consortium

• Part funded by DIUS

5
Project Phases

• Thermal Modelling (OHL, UGC and TFMR)
• Thermal State Estimation
• DG constrained connection techniques
• System Simulation
• Network and Meteorological Instrumentation
• Open Loop Trials
• Closed Loop Trials

6
What Do We Mean By Dynamic Thermal Ratings?

• Aim
• To increase the energy transferred through the
  network under normal operating conditions
• Without reducing component lifetime or network
  security

• Measurements
• Availability of a limited number of environmental
  measurements
• Electrical measurements available from SCADA

• How
• Exploit headroom which is available for a
  reasonable amount of time
• Never exceed the standard component continuous
  operation design temperature

7
Lumped Parameter Modelling of the Thermal State
of OHL Conductors
8
Lumped Parameter Model Standard comparison

• IEC TR 61597
• IEEE 738
• CIGRE WG 22.12 in ELECTRA 144 1992
• The IEC model has been selected

C
B
A
Maximum current carrying capacity models
comparison Conductor ACSR 175mm2 LYNX Wd90º,
Ta25 ºC, Sr0 W/m2
9
Lumped Parameter Model Simulation
The network and its geographical location Costal
area, west coast, subject to sea breeze Three
directions for the line, the smallest rating has
to be considered
Network diagram and line characteristics Voltage
132kV, line length 7km, conductor ACSR 175mm2
LYNX
10
Lumped Parameter Model Simulation results
The simulations suggest that consistent headroom
is available when using daily or hourly ratings
GWh/year
Yearly (summer) rating 762
Seasonal ratings 879
Daily ratings 1393
Hourly ratings 1696
Minimum daily rating compared with seasonal
ratings Weather data from Valley (Anglesey)
Comparison of energy transfer capacity for
different rating period
11
CFD Modelling of the Thermal State of OHL
Conductors
12
Modelling the thermal state of ACSR 410
conductor exposed to cross wind
ASCR410 7 steel strands surrounded by 27
aluminium strands.
Simplified geometry
The outer diameter is 28.5mm
M. Isozaki and N. Iwama. Verification of forced
convective cooling from conductors in breeze
wind by wind tunnel testing. (0-7803-7525-4/02,
2002 IEEE).
2-D calculation scheme
13
Modelling thermal state of ACSR 410 conductor
exposed to cross wind
14
Modelling the thermal state of LYNX conductor
exposed to cross wind
Real geometry
Simplified geometry
Computational grid
Lynx consists of 30 strands of an aluminium wire
and 7 strands of a steel wire. Outer diameter
is 19.5 mm
15
Modelling the thermal state of Lynx conductor
exposed to cross wind
The ambient temperature is 293 K I 433A.
CFD predicts 16 K headroom existence
16
Impact of solar radiation on the conductor
temperature
Initial conditions Cross wind 2 m/s, Current
433A, T ambient 293 K

• Additional source of heat emanates from solar
  radiation
• q a d s
• a solar absorption coefficient, this
• varies from 0.3 to 0.9
• d diameter of conductor (m)
• s intensity of solar radiation (W/m2),
• a typical value being 800 (W/m2)

1 Ambient temperature
2 Temperature of the conductor taking into account convection and radiation losses
3 Temperature of the conductor taking into account convection and radiation losses and temperature dependent resistivity
4, 5, 6 Temperature of the conductor taking into account convection and radiation losses, temperature dependent resistivity and solar radiation with insolation of 240W/m2, 400 W/m2, and 720 W/m2, respectively.
17
Lynx conductor exposed to cross wind - comparison
with measured data on distribution network
Date Time Ambient Temperature (deg. C) Wind Speed (m/s) Wind speed Avg (m/s) Wind Direction (deg.) Solar Radiation (W/m2) Line temperature (deg C) I (A)
Case 1 27/03/2008 1250 8.4 (0.4) 1.3 189 232 15.5 30.59
Case 2 27/03/2008 2015 7.6 (2.2) 3.5 86 0 10.0 83.13
18
CFD Model the Lynx conductor exposed to cross
wind - comparison with real data
data (deg C) CFD (deg C) Difference (deg C)
Case 1 15.5 9.9 5.6
Case 2 10.0 7.8 2.2
19
Lynx conductor exposed to parallel wind
Temperature of the conductor vs. velocity for
cross and parallel wind conditions
Calculation scheme
Outlet
Conductor
Temperature, K
Inlet
Air domain
Conductor
Aluminium
Wind velocity, m/s
Steel core
The ambient temperature is 293 K I 433A
20
Comparison Between CFD and Lumped Parameter
Modelling of the Thermal State of OHL Conductors
21
CFD / Lumped comparisonCross wind, temperature
Conductor temperature. CFD/Lumped parameter
comparison Conductor ACSR 175mm2 LYNX, Ta20'C,
I433A, Wd90'
22
CFD / Lumped comparisonParallel wind, temperature
Conductor temperature. CFD/Lumped parameter
comparison Conductor ACSR 175mm2 LYNX, Ta20'C,
I433A, Wd0'
23
Thermal State Estimation
24
State Estimation - Objectives

• Produce reliable estimates of maximum current
  carrying capacity of power system components
• Identify minimum and most probable value
• Possibility to calculate a rating for a given
  probability/risk

25
State Estimation Simulation results
Minimum, mean and maximum hourly rating
26
Conclusions

• Encouraging results regarding potential headroom
• Lumped parameter models more conservative than
  CFD
• Initial comparisons to real data encouraging
• Need to further validate models with real data
• Need to validate state estimation with real data
• Site installation
• Trials (open and closed loop)