Marco Pignati

Real-time state estimation of the EPFL-campus medium-voltage grid by using PMUs

We describe the real-time monitoring infrastructure of the smart-grid pilot on the EPFL campus. We experimentally validate the concept of a real-time state-estimation for a 20 kV active distribution network. We designed and put into operation the whole infrastructure composed by the following main elements: (1) dedicated PMUs connected on the medium-voltage side of the network secondary substations by means of specific current/voltage transducers; (2) a dedicated communication network engineered to support stringent time limits and (3) an innovative state estimation process for real-time monitoring that incorporates phasor-data concentration and state estimation processes. Special care was taken to make the whole chain resilient to cyber-attacks, equipment failures and power outages. The achieved latency is within 65ms. The refresh rate of the estimated state is 20ms. The real-time visualization of the state estimator output is made publicly available, as well as the historical data (PMU measurements and estimated states). To the best of our knowledge, the work presented here is the first operational system that provides low-latency real-time state-estimation by using PMU measurements of a real active distribution network.

An Information-Centric Communication Infrastructure for Real-Time State Estimation of Active Distribution Networks

The evolution toward emerging active distribution networks (ADNs) can be realized via a real-time state estimation (RTSE) application facilitated by the use of phasor measurement units (PMUs). A critical challenge in deploying PMU-based RTSE applications at large scale is the lack of a scalable and flexible communication infrastructure for the timely (i.e., sub-second) delivery of the high volume of synchronized and continuous synchrophasor measurements. We address this challenge by introducing a communication platform called C-DAX based on the information-centric networking (ICN) concept. With a topic-based publish-subscribe engine that decouples data producers and consumers in time and space, C-DAX enables efficient synchrophasor measurement delivery, as well as flexible and scalable (re)configuration of PMU data communication for seamless full observability of power conditions in complex and dynamic scenarios. Based on the derived set of requirements for supporting PMU-based RTSE in ADNs, we design the ICN-based C-DAX communication platform, together with a joint optimized physical network resource provisioning strategy, in order to enable the agile PMU data communications in near real-time. In this paper, C-DAX is validated via a field trial implementation deployed over a sample feeder in a real-distribution network; it is also evaluated through simulation-based experiments using a large set of real medium voltage grid topologies currently operating live in The Netherlands. This is the first work that applies emerging communication paradigms, such as ICN, to smart grids while maintaining the required hard real-time data delivery as demonstrated through field trials at national scale. As such, it aims to become a blueprint for the application of ICN-based general purpose communication platforms to ADNs.

Probabilistic assessment of the process-noise covariance matrix of discrete Kalman filter state estimation of active distribution networks

The accuracy of state estimators using the Kalman Filter (KF) is largely influenced by the measurement and the process noise covariance matrices. The former can be directly inferred from the available measurement devices whilst the latter needs to be assessed, as a function of the process model, in order to maximize the KF performances. In this paper we present different approaches that allow assessing the optimal values of the elements composing the process noise covariance matrix within the context of the State Estimation (SE) of Active Distribution Networks (ADNs). In particular, the paper considers a linear SE process based on the availability of synchrophasors measurements. The assessment of the process noise covariance matrix, related to a process model represented by the ARIMA [0,1,0] one, is based either on the knowledge of the probabilistic behavior of nodal network injections/absorptions or on the a-posteriori knowledge of the estimated states and their accuracies. Numerical simulations demonstrating the improvements of the KF-SE accuracy achieved by using the calculated matrix Q are included in the paper. A comparison with the Weighted Least Squares (WLS) method is also given for validation purposes.

A pre-estimation filtering process of bad data for linear power systems state estimators using PMUs

The paper proposes a specific algorithm for the pre-estimation filtering of bad data (BD) in PMU-based power systems linear State Estimators (SEs). The approach is framed in the context of the so-called real-time SEs that take advantage of the high measurement frame rate made available by PMUs (i.e., 50-60 frames per second). In particular, the proposed algorithm examines PMU measurement innovations for each new received set of data in order to locate anomalies and apply countermeasures. The detection and identification scheme is based on: (i) the forecasted state of the network obtained by means of a linear Kalman filter, (ii) the current network topology, (iii) the accuracy of the measurement devices and (iv) their location. The incoming measurement from each PMU is considered reliable, or not, according to a dynamic threshold defined as a function of the confidence of the predicted state estimated by using an AutoRegressive Integrated Moving Average (ARIMA) process. The performances of the proposed algorithm are validated with respect to single and multiple bad data of different nature and magnitudes. Furthermore, the algorithm is also tested against faults occurring in the power system to show its robustness during these unexpected operating conditions.

Architecture and characterization of a calibrator for PMUs operating in power distribution systems

In recent years, the Phasor Measurement Unit (PMU) technology is rapidly evolving towards the potential deployment also in power distribution systems (DSs). In general, this specific field of applications requires PMUs whose accuracy levels are beyond those required by the IEEE Std. C37.118. Additionally, there is the need to define the architecture of an associated calibration system capable to assess the metrological performances of these devices. In this paper, we first analyse the impact of the uncertainties (in term of phase and magnitude) introduced by arbitrary PMUs on a state estimation (SE) process performed on the IEEE 13-bus distribution test feeder. The outcomes of this analysis are used to infer the most stringent steady-state performances of PMUs for DSs monitoring and, consequently, to define the requirements and the hardware architecture of a PMU calibrator presently developed at the Authors laboratories. A preliminary metrological characterization of the proposed calibrator is presented in the paper.

Fault Detection and Faulted Line Identification in Active Distribution Networks using Synchrophasors-based Real-Time State Estimation

We intend to prove that phasor-measurement-unit (PMU)-based state estimation processes for active distribution networks exhibit unique time determinism and a refresh rate that makes them suitable to satisfy the time-critical requirements of protections as well as the accuracy requirements dictated by faulted line identification. In this respect, we propose a real-time fault detection and faulted line identification functionality obtained by computing parallel synchrophasor-based state estimators. Each state estimator is characterized by a different and augmented topology in order to include a floating fault bus. The selection of the state estimator providing the correct solution is performed by a metric that computes the sum of the weighted measurement residuals. The proposed process scheme is validated by means of a real-time simulation platform where an existing active distribution network is simulated together with a PMU-based monitoring system. The proposed process is shown to be suitable for active and passive networks, with solid-earthed and unearthed neutral, for low- and high-impedance faults of any kind (symmetric and asymmetric) occurring at different locations.

Integration of an IEEE Std. C37.118 compliant PMU into a real-time simulator

The simulation of Phasor Measurement Units (PMUs) into real-time simulators (RTSs) is typically limited by the complexity of the synchrophasor estimation (SE) algorithm. This is especially true when dealing with distribution network PMUs due to the more demanding accuracy requirement and, for the case of class-P PMUs, for the limited latency. In this respect, if the SE algorithm is too simplistic, the performances of the simulated PMU might not match the specific application needs. On the other hand, when higher precision of the synchrophasors estimations is required, an increased computational complexity of the SE algorithm is obtained and, as a consequence, few devices can be simulated into a RTSs at the same time. The work presented in this paper illustrates the design and the deployment of a C37.118 class-P compliant PMU into the Opal-RT RTS. The RTS-deployed PMU has demonstrated to match the requirements of both transmission and distribution networks. The simulated PMU has been experimentally validated and demonstrated to be well suited for its integration into any RTS.

Fault detection and faulted line identification in active distribution networks using synchrophasors-based real-time state estimation

We intend to prove that phasor-measurement-unit (PMU)-based state estimation processes for active distribution networks exhibit unique time determinism and a refresh rate that makes them suitable to satisfy the time-critical requirements of protections as well as the accuracy requirements dictated by faulted line identification. In this respect, we propose a real-time fault detection and faulted line identification functionality obtained by computing parallel synchrophasor-based state estimators. Each state estimator is characterized by a different and augmented topology in order to include a floating fault bus. The selection of the state estimator providing the correct solution is performed by a metric that computes the sum of the weighted measurement residuals. The proposed process scheme is validated by means of a real-time simulation platform where an existing active distribution network is simulated together with a PMU-based monitoring system. The proposed process is shown to be suitable for active and passive networks, with solid-earthed and unearthed neutral, for low- and high-impedance faults of any kind (symmetric and asymmetric) occurring at different locations.

A Hardware-in-the-Loop test platform for the performance assessment of a PMU-based Real-Time State Estimator for Active Distribution Networks

The paper describes the development of a Hardware-in-the-Loop (HIL) test platform for the performance assessment of a PMU-based sub-second linear Real-Time State Estimator (RTSE) for Active Distribution Networks (ADNs). The estimator relies on the availability of data coming from Phasor Measurement Units (PMUs) and can be applied to both balanced and unbalanced ADNs. The paper first illustrates the architecture of the experimental HIL setup that has been fully designed by the Authors. It consists of a Real-Time Simulator (RTS) that models the electrical network model as well as the measurement infrastructure composed by virtual PMUs. These virtual devices stream their data to a real Phasor Data Concentrator (PDC) suitably coupled with a Discrete Kalman Filter State Estimator (DKF-SE). By using this experimental setup, the paper discusses the performance assessment of the whole process in terms of estimation accuracy and time latencies. In the RTS, a real ADN located in the Netherlands has been modeled together with the associated PMUs.

Definition of Accurate Reference Synchrophasors for Static and Dynamic Characterization of PMUs

The calibration of phasor measurement units (PMUs) consists of comparing coordinated universal time time-aligned phasors (synchrophasors) measured by the PMU under test, against reference synchrophasors generated through a PMU calibrator. The IEEE Standard C37.118–2011 and its latest amendment (IEEE Std) describe compliance tests for static and dynamic conditions, and indicate the relative limits in terms of accuracy. In this context, this paper focuses on the definition and accuracy assessment of the reference synchrophasors in the test conditions defined by the above IEEE Std. In the first part of this paper, we describe the characterization of a nonlinear least-squares fitting algorithm used to determine the parameters of these reference synchrophasors. For this analysis, we deploy the proposed algorithm in a PMU calibrator and characterize the algorithm performance within the actual hardware implementation for both static and dynamic test conditions. More specifically, we generate reference waveforms through a highly stable high-resolution digital-to-analog converter and evaluate how the algorithm parameters (observation interval length and sampling frequency) affect the solution accuracy. In the second part, we discuss on the appropriateness of the synchrophasor model in the evaluation of PMU performance under step test conditions. In this regard, we propose an alternative time-domain approach to assess the synchrophasor estimate during transient events.