On the trade-off between timeliness and accuracy for low voltage distribution system grid monitoring utilizing smart meter data

Abstract Due to limited bandwidth and high delays in access to Smart Meter measurements, it is not possible in most cases to access measurements from the complete set of smart meters in a low-voltage grid area for distribution grid monitoring. Distribution system state estimation can be performed based on measurements of voltage and active and reactive power from a subset of selected smart meters. Increasing the number of selected smart meters will, on the one hand, increase the accuracy of distribution system state estimation, while on the other hand, it will degrade timeliness of the monitoring data. This paper proposes to utilize part of the idle time of the legacy periodic smart meter data collection for access to measurements from the subset of selected smart meters for distribution system state estimation. It subsequently proposes a methodology on how to quantitatively analyze this trade-off. The methodology is applied to an example LV grid area with 20 customers using a weighted least square state estimation with support of pseudo-measurements obtained during the regular smart meter collection cycle.

[1]  J. Giri,et al.  PMU Impact on State Estimation Reliability for Improved Grid Security , 2006, 2005/2006 IEEE/PES Transmission and Distribution Conference and Exhibition.

[2]  Fan Zhang,et al.  Multiphase power flow and state estimation for power distribution systems , 1996 .

[3]  J.-H. Teng Using voltage measurements to improve the results of branch-current-based state estimators for distribution systems , 2002 .

[4]  Antonello Monti,et al.  Impact of Pseudo-Measurements From New Power Profiles on State Estimation in Low-Voltage Grids , 2016, IEEE Transactions on Instrumentation and Measurement.

[5]  R. M. Ciric,et al.  Power flow in four-wire distribution networks-general approach , 2003 .

[6]  Ronnie Belmans,et al.  Distributed generation: definition, benefits and issues , 2005 .

[7]  Fred C. Schweppe,et al.  Power System Static-State Estimation, Part I: Exact Model , 1970 .

[8]  Kaveh Dehghanpour,et al.  A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems , 2018, IEEE Transactions on Smart Grid.

[9]  A. G. Expósito,et al.  Power system state estimation : theory and implementation , 2004 .

[10]  Pierluigi Mancarella,et al.  Active Distribution System Management: A Dual-Horizon Scheduling Framework for DSO/TSO Interface Under Uncertainty , 2017, IEEE Transactions on Smart Grid.

[11]  R. Vinter,et al.  Measurement Placement in Distribution System State Estimation , 2009, IEEE Transactions on Power Systems.

[12]  Antonio Gómez Expósito,et al.  State estimation in two time scales for smart distribution systems , 2015, 2015 IEEE Power & Energy Society General Meeting.

[13]  J. Teng,et al.  Distribution system state estimation , 1995 .

[14]  Junqi Liu,et al.  Trade-Offs in PMU Deployment for State Estimation in Active Distribution Grids , 2012, IEEE Transactions on Smart Grid.

[15]  A. W. Kelley,et al.  State estimation for real-time monitoring of distribution systems , 1994 .

[16]  Jochen Markard,et al.  Smart meter communication standards in Europe – a comparison , 2015 .

[17]  Ke Li,et al.  State estimation for power distribution system and measurement impacts , 1996 .

[18]  M.E. Baran,et al.  A branch-current-based state estimation method for distribution systems , 1995 .

[19]  Jianzhong Wu,et al.  A robust state estimator for medium voltage distribution networks , 2013, IEEE Transactions on Power Systems.

[20]  Paolo Attilio Pegoraro,et al.  Efficient Branch-Current-Based Distribution System State Estimation Including Synchronized Measurements , 2013, IEEE Transactions on Instrumentation and Measurement.

[21]  Y. Deng,et al.  A Branch-Estimation-Based State Estimation Method for Radial Distribution Systems , 2002, IEEE Power Engineering Review.