TY - GEN
T1 - Minimizing heat loss in DC networks using batteries
AU - Zocca, Alessandro
AU - Zwart, Bert
PY - 2017/2/10
Y1 - 2017/2/10
N2 - Electricity transmission networks dissipate a non-negligible fraction of the power they transport due to the heat loss in the transmission lines. In this work we explore how the transport of energy can be more efficient by adding to the network multiple batteries that can coordinate their operations. Such batteries can both charge using the current excess in the network or discharge to meet the network current demand. Either way, the presence of batteries in the network can be leveraged to mitigate the intrinsic uncertainty in the power generation and demand and, hence, transport the energy more efficiently through the network. We consider a resistive DC network with stochastic external current injections or consumptions and show how the expected total heat loss depends on the network structure and on the batteries operations. Furthermore, in the case where the external currents are modeled by Ornstein-Uhlenbeck processes, we derive the dynamical optimal control for the batteries over a finite time interval.
AB - Electricity transmission networks dissipate a non-negligible fraction of the power they transport due to the heat loss in the transmission lines. In this work we explore how the transport of energy can be more efficient by adding to the network multiple batteries that can coordinate their operations. Such batteries can both charge using the current excess in the network or discharge to meet the network current demand. Either way, the presence of batteries in the network can be leveraged to mitigate the intrinsic uncertainty in the power generation and demand and, hence, transport the energy more efficiently through the network. We consider a resistive DC network with stochastic external current injections or consumptions and show how the expected total heat loss depends on the network structure and on the batteries operations. Furthermore, in the case where the external currents are modeled by Ornstein-Uhlenbeck processes, we derive the dynamical optimal control for the batteries over a finite time interval.
UR - http://www.scopus.com/inward/record.url?scp=85015178815&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85015178815&partnerID=8YFLogxK
U2 - 10.1109/ALLERTON.2016.7852385
DO - 10.1109/ALLERTON.2016.7852385
M3 - Conference contribution
AN - SCOPUS:85015178815
T3 - 54th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2016
SP - 1306
EP - 1313
BT - 54th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 54th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2016
Y2 - 27 September 2016 through 30 September 2016
ER -