Dynamic Thermal Ratings for Overhead Lines Philip Taylor, Irina Makhkamova, Andrea Michiorri Energy Group, School of Engineering Durham University

Energy Group School of Engineering Overview Research Overview Overhead Line Thermal Modelling –Lumped Parameter –Computational Fluid Dynamics –Comparisons Thermal State Estimation Further work

Energy Group School of Engineering 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

Energy Group School of Engineering Project Consortium Part funded by DIUS

Energy Group School of Engineering 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

Energy Group School of Engineering 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

Lumped Parameter Modelling of the Thermal State of OHL Conductors

Energy Group School of Engineering Lumped Parameter Model – Standard comparison  IEC TR  IEEE 738  CIGRE WG in ELECTRA 144 – 1992  The IEC model has been selected Maximum current carrying capacity – models comparison Conductor ACSR 175mm 2 LYNX Wd=90º, Ta=25 [ºC], Sr=0 [W/m 2 ] A B C

Energy Group School of Engineering Lumped Parameter Model – Simulation Network diagram and line characteristics Voltage: 132kV, line length: 7km, conductor: ACSR 175mm 2 LYNX 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

Energy Group School of Engineering Lumped Parameter Model – Simulation results GWh/year Yearly (summer) rating762 Seasonal ratings879 Daily ratings1393 Hourly ratings1696 Minimum daily rating compared with seasonal ratings Weather data from Valley (Anglesey) Comparison of energy transfer capacity for different rating period The simulations suggest that consistent headroom is available when using daily or hourly ratings

CFD Modelling of the Thermal State of OHL Conductors

Energy Group School of Engineering Modelling the thermal state of ACSR 410 conductor exposed to cross wind The outer diameter is 28.5mm ASCR410: 7 steel strands surrounded by 27 aluminium strands. Simplified geometry M. Isozaki and N. Iwama. Verification of forced convective cooling from conductors in breeze wind by wind tunnel testing. ( /02, 2002 IEEE). Outlet Conductor Inlet Air domain 2-D calculation scheme

Energy Group School of Engineering Modelling thermal state of ACSR 410 conductor exposed to cross wind

Energy Group School of Engineering Modelling the thermal state of LYNX conductor exposed to cross wind Lynx consists of 30 strands of an aluminium wire and 7 strands of a steel wire. Outer diameter is 19.5 mm Real geometrySimplified geometryComputational grid

Energy Group School of Engineering M odelling the thermal state of Lynx conductor exposed to cross wind The ambient temperature is 293 K; I = 433A. CFD predicts 16 K headroom existence

Energy Group School of Engineering Impact of solar radiation on the conductor temperature Additional source of heat emanates from solar radiation q = α · d · s α = solar absorption coefficient, this varies from 0.3 to 0.9 d = diameter of conductor (m) s = intensity of solar radiation (W/m 2 ), a typical value being 800 (W/m 2 ) 1Ambient temperature 2Temperature of the conductor taking into account convection and radiation losses 3Temperature of the conductor taking into account convection and radiation losses and temperature – dependent resistivity 4, 5, 6Temperature of the conductor taking into account convection and radiation losses, temperature – dependent resistivity and solar radiation with insolation of 240W/m 2, 400 W/m 2, and 720 W/m 2, respectively. Initial conditions: Cross wind = 2 m/s, Current = 433A, T ambient = 293 K

Energy Group School of Engineering Lynx conductor exposed to cross wind - comparison with measured data on distribution network DateTimeAmbient Temperature (deg. C) Wind Speed (m/s) Wind speed Avg (m/s) Wind Direction (deg.) Solar Radiation (W/m 2 ) Line temperature (deg C) I (A) Case 1: 27/03/200812:508.4(0.4) Case 2: 27/03/ :157.6(2.2)

Energy Group School of Engineering CFD Model: the Lynx conductor exposed to cross wind - comparison with real data data (deg C) CFD (deg C) Difference (deg C) Case Case

Energy Group School of Engineering Lynx conductor exposed to parallel wind The ambient temperature is 293 K; I = 433A Calculation scheme Conductor Outlet Inlet Air domain Temperature of the conductor vs. velocity for cross and parallel wind conditions Wind velocity, m/s Temperature, K Aluminium Steel core Conductor

Comparison Between CFD and Lumped Parameter Modelling of the Thermal State of OHL Conductors

Energy Group School of Engineering CFD / Lumped comparison Cross wind, temperature Conductor temperature. CFD/Lumped parameter comparison Conductor: ACSR 175mm2 LYNX, Ta=20'C, I=433A, Wd=90'

Energy Group School of Engineering CFD / Lumped comparison Parallel wind, temperature Conductor temperature. CFD/Lumped parameter comparison Conductor: ACSR 175mm2 LYNX, Ta=20'C, I=433A, Wd=0'

Thermal State Estimation

Energy Group School of Engineering 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

Energy Group School of Engineering State Estimation – Simulation results Minimum, mean and maximum hourly rating

Energy Group School of Engineering 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)