TY - JOUR
T1 - Unlocking the benefits of real-time thermal ratings through probabilistic power network planning
AU - Greenwood, David Michael
AU - Taylor, Philip Charles
PY - 2014/12/1
Y1 - 2014/12/1
N2 - Real-time thermal ratings (RTTRs) is an emerging technique used to calculate the rating of electrical conductors based on local, real-time weather conditions; this leads to an increased rating with respect to conventional approaches the majority of the time, and can be used to increase the energy yield of distributed generators, support the network during outages and defer network reinforcement. Unfortunately it is not presently recognised in network planning, design and security of supply standards. This represents a barrier to utilising RTTRs in power networks, and must be addressed. This study presents a new, probabilistic method for accounting for the variable ratings during network planning. This is coupled with an analysis of the risk of being unable to supply customers in a network adopting variable ratings, compared with the risk in the same network using conventional ratings; hence the method proposed in this study allows additional load to be connected to the network at a quantified level of risk. Finally, this method could be applied to other emerging network technologies and techniques such as demand side management or energy storage.
AB - Real-time thermal ratings (RTTRs) is an emerging technique used to calculate the rating of electrical conductors based on local, real-time weather conditions; this leads to an increased rating with respect to conventional approaches the majority of the time, and can be used to increase the energy yield of distributed generators, support the network during outages and defer network reinforcement. Unfortunately it is not presently recognised in network planning, design and security of supply standards. This represents a barrier to utilising RTTRs in power networks, and must be addressed. This study presents a new, probabilistic method for accounting for the variable ratings during network planning. This is coupled with an analysis of the risk of being unable to supply customers in a network adopting variable ratings, compared with the risk in the same network using conventional ratings; hence the method proposed in this study allows additional load to be connected to the network at a quantified level of risk. Finally, this method could be applied to other emerging network technologies and techniques such as demand side management or energy storage.
U2 - 10.1049/iet-gtd.2014.0043
DO - 10.1049/iet-gtd.2014.0043
M3 - Article
SN - 1751-8687
VL - 8
SP - 2055
EP - 2064
JO - IET Generation, Transmission and Distribution
JF - IET Generation, Transmission and Distribution
IS - 12
ER -