Some Aspects of Static and Dynamic Distribution System State Estimation with Optimal Meter Placement Studies
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Date
2018-09-04
Authors
Kandenkavil, Sreedevi Valsan
Journal Title
Journal ISSN
Volume Title
Publisher
University of Waterloo
Abstract
In a power distribution system, due to the evolution of Active Distribution Networks
(ADNs), there is a possibility of violation of the system operational constraints. A state
estimator provides an approximate snapshot of the distribution system operation when the
bus voltages and power measurements are available. Thus it plays a key role in monitoring
the system, thereby ensuring a safe state of operation. According to the nature of the
system, Distribution System State Estimation (DSSE) can be classified in to static DSSE
and dynamic DSSE. Static DSSE is commonly designed as a Weighted Least Square (WLS)
estimator using either bus voltages or branch currents as system states. For dynamic DSSE,
the performance of static state estimators are limited. A Kalman filter based state estimator
can be used in such time varying systems. A study of the algorithms used for these two
DSSE methods is necessary in order to analyze the factors affecting the estimation accuracy.
In a power distribution system, with limited availability of measurements, and additional
measurements being expensive, careful selection of the location for the placement of meters
becomes important. The measurement meters typically considered are Phasor Measurement
Units (PMUs) and power (PQ) meters. The existing placement problems lay more emphasis
on minimizing the cost of installing such meters, while the quality of estimation remains
ignored. Thus there is a need to formulate methods for optimal allocation of meters in a
cost effective way without altering the accuracy of DSSE.
In this work, a detailed study is conducted on the two static DSSE algorithms, Node Voltage
based State Estimation (NVSE) and Branch Current based State Estimation (BCSE)
and the DSSE performance is compared based on Average Root Mean Square (ARMSE)
Value of state estimates. The thesis also analyzes the impact of the number of PMU measurements
available on DSSE performance. Several optimization based approaches are proposed
to address the optimal meter placement problem considering different objectives such
as minimization of cost, WLS residual estimate, a multi-objective function comprising cost
and WLS, and the ARMSE of the estimated bus voltage. An Iterative Extended Kalman
Filter (IEKF) is used for performing dynamic DSSE. The dependency of various parameters
such as selection of time frame, apriori estimate information length and PMU measurement
errors on the accuracy acquired by DSSE is also presented.
The studies and proposed models are simulated in a 33-bus distribution feeder. The
results illustrating the efficiency and speed of convergence of different static and dynamic
DSSE methods are discussed. The various optimization models for meter allocation are
formulated and compared based on meter placement cost and ARMSE of voltage estimates.
Description
Keywords
Distribution System, State Estimation, Optimal Meter Placement, Iterative Extended Kalman Filter