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Personne# Styliani Sarri

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Filtre de Kalman

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Phasor measurement unit

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Publications associées (11)

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Jean-Yves Le Boudec, Mario Paolone, Miroslav Popovic, Styliani Sarri, Lorenzo Zanni

This paper aims to assess the performance of linear state estimation (SE) processes of power systems relying on synchrophasor measurements. The performance assessment is conducted with respect to two different families of SE algorithms, i.e., static ones represented by weighted least squares (WLS) and recursive ones represented by Kalman filter (KF). To this end, this paper firstly recalls the analytical formulation of linearWLS state estimator (LWLS-SE) and Discrete KF state estimator (DKF-SE). We formally quantify the differences in the performance of the two algorithms. The validation of this result, together with the comprehensive performance evaluation of the considered state estimators, is carried out using two case studies, representing distribution (IEEE 123-bus test feeder) and transmission (IEEE 39-bus test system) networks. As a further contribution, this paper validates the correctness of the most common process model adopted in DKF-SE of power systems.

Konstantina Christakou, Jean-Yves Le Boudec, Mario Paolone, Marco Pignati, Roman Rudnik, Styliani Sarri

The Grid Explicit Congestion Notification control mechanism (GECN) is a broadcast-based real-time demand- response mechanism designed for primary voltage control in Active Distribution Networks (ADNs) [1,2]. An extensive set of off-line simulations has indicated that GECN is a promising candidate for deployment in the real field. However, prior to the actual deployment of the control mechanism, it is crucial to validate its performance when controlling a real grid. For this purpose we design and develop a dedicated experimental Hardware-in-the-Loop (HIL) test platform for the real-time val- idation of GECN. The HIL architecture consists of a Real-Time Simulator (RTS) where a real distribution feeder is modeled, together with controllable loads and the associated measurement infrastructure composed by virtual PMUs. These virtual metering devices stream data, via Ethernet, to a local Phasor Data Con- centrator suitably coupled with a Discrete Kalman Filter State Estimator. The estimated network state is received by a GECN network controller. We close the control loop by transmitting the computed broadcast control signals back to the network buses in the RTS using a micro-controller. By using this experimental setup we are able to (i) assess the performance of the whole control process in terms of voltage optimality and time latencies in a realistic setting and (ii) implement the GECN controllers into dedicated equipment that with the proper ruggedization can be readily deployed in the real field.

The evolution from passive to Active Distribution Networks (ADNs) is producing large changes in the operation of these electrical systems. In particular, violations of grid operational constraints, higher dynamics and limited amount of controllable resources represent main limiting factors in the optimal operation of ADNs in presence of massive stochastic distributed generation. In order to deal with these issues, the emergence of ADNs requires the definition of suitable Energy Management Systems to achieve specific operation objectives (i.e., optimal voltage/congestion controls, updated protection schemes etc.). These functions are significantly improved if the system state is known with high accuracy, high refresh rates and low time latencies. Unfortunately, typical refresh rates of traditional State Estimation (SE) processes designed for transmission networks are in the order of few minutes, whereas the time frames of the above functionalities are between few milliseconds to few seconds. Hence, it becomes necessary to define, develop and validate the three-phase Real-Time State Estimation (RTSE) processes characterised by high refresh rates (i.e., in the range of several tens of estimation per second), small latencies (i.e., in the range of few tens of ms) and high accuracy. In this direction, the ADNs SE is facilitated by the emerging technology of Phasor Measurement Units (PMUs) which allow acquiring accurate, time-aligned phasors with typical streaming rates in the order of some tens of f.p.s. Additionally, PMUs measurements of synchrophasors allow formulating the SE problem in a linear way. PMU measurements can be acquired and stored in a real-time (RT) database, provided by Phasor Data Concentrators (PDCs) suitably coupled with the RTSE. This enables, in theory, the performance assessment of the whole RTSE chain. However, the assessment of the RTSE accuracy with real PMUs in a real grid is impossible since the true state is hidden. It is, yet, possible to overcome this limitation by using a Real Time Simulator (RTS) and design a RT setup that allows knowing the true state. This RT setup should be GPS-synchronized, to enable the RTSE accuracy and time latencies assessment. Within the above context, this thesis focuses on the definition of SE methods together with their formal and numerical performance assessment. In particular, the first part of the thesis discusses the formulation of static (e.g., weighted least squares - WLS) and recursive (e.g., Kalman Filter - KF) algorithms fed by synchronized phasors and/or other traditional measurements provided by remote terminal units. Then, the thesis discusses the formal comparison of the accuracy of KF vs. WLS and proves that the former behaves better if its process model is correct. For the case of linear SE, the thesis discusses the method for the verification of the exactness of the so-called measurement noise covariance matrix. The subsequent part of the thesis provides the numerical validation and performance assessment of the RTSE process via offline simulations. This analysis is conducted by using IEEE benchmark distribution and transmission networks as well as real distribution feeders. The last part of the thesis focuses on the experimental validation of the RTSE chain via an experimental RT setup. In this last part, the thesis describes the structure and the individual components simulated in the RT experimental setup as well as the whole validation procedure.