TY - GEN
T1 - A Data-driven Voltage Control Framework for Power Distribution Systems
AU - Xu, Hanchen
AU - Dominguez-Garcia, Alejandro D.
AU - Sauer, Peter W.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/21
Y1 - 2018/12/21
N2 - In this paper, we address the problem of coordinating a set of distributed energy resources (DERs) to regulate voltage in power distribution systems to desired levels. To this end, we formulate the voltage control problem as an optimization problem, the objective of which is to determine the optimal DER power injections that minimize the voltage deviations from desirable voltage levels subject to a set of constraints. The nonlinear relationship between the voltage magnitudes and the nodal power injections is approximated by a linear model, the parameters of which can be estimated in real-time efficiently using measurements. In particular, the parameter estimation requires much fewer data by exploiting the structural characteristics of the power distribution system. As such, the voltage control framework is intrinsically adaptive to parameter changes. Numerical studies on the IEEE 37-bus power distribution test feeder validated the effectiveness of the propose framework.
AB - In this paper, we address the problem of coordinating a set of distributed energy resources (DERs) to regulate voltage in power distribution systems to desired levels. To this end, we formulate the voltage control problem as an optimization problem, the objective of which is to determine the optimal DER power injections that minimize the voltage deviations from desirable voltage levels subject to a set of constraints. The nonlinear relationship between the voltage magnitudes and the nodal power injections is approximated by a linear model, the parameters of which can be estimated in real-time efficiently using measurements. In particular, the parameter estimation requires much fewer data by exploiting the structural characteristics of the power distribution system. As such, the voltage control framework is intrinsically adaptive to parameter changes. Numerical studies on the IEEE 37-bus power distribution test feeder validated the effectiveness of the propose framework.
KW - Data-driven
KW - Distributed energy resource
KW - Parameter estimation
KW - Power distribution system.
KW - Voltage control
UR - http://www.scopus.com/inward/record.url?scp=85060823245&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060823245&partnerID=8YFLogxK
U2 - 10.1109/PESGM.2018.8586174
DO - 10.1109/PESGM.2018.8586174
M3 - Conference contribution
AN - SCOPUS:85060823245
T3 - IEEE Power and Energy Society General Meeting
BT - 2018 IEEE Power and Energy Society General Meeting, PESGM 2018
PB - IEEE Computer Society
T2 - 2018 IEEE Power and Energy Society General Meeting, PESGM 2018
Y2 - 5 August 2018 through 10 August 2018
ER -