An efficient method to include equality constraints in branch current distribution system state estimation

Distribution system state estimation is a fundamental tool for the management and control functions envisaged for future distribution grids. The design of accurate and efficient algorithms is essential to provide estimates compliant with the needed accuracy requirements and to allow the real-time operation of the different applications. To achieve such requirements, peculiarities of the distribution systems have to be duly taken into account. Branch current-based estimators are an efficient solution for performing state estimation in radial or weakly meshed networks. In this paper, a simple technique, which exploits the particular formulation of the branch current estimators, is proposed to deal with zero injection and mesh constraints. Tests performed on an unbalanced IEEE 123-bus network show the capability of the proposed method to further improve efficiency performance of branch current estimators

Statistical Behavior of PMU Measurement Errors: An Experimental Characterization

Different power system applications based on synchrophasors measured in different nodes of the electric grid require information about the statistical distribution of the errors introduced by the phasor measurement units (PMUs). The performance of these applications can be significantly affected by possible incorrect assumptions. The Gaussian distribution has been historically assumed in most of the approaches, but some more recent studies suggest the possibility of considering different distributions for more accurate modeling of the actual situation. In this article, proper statistical tools applied to the results achieved through a high-performance experimental test system are proposed to assess the statistical distribution of PMU errors under controlled steady-state conditions, thus providing a basis for defining suitable models to be used in specific applications

Space Vector Taylor–Fourier Models for Synchrophasor, Frequency, and ROCOF Measurements in Three-Phase Systems

Taylor-Fourier (TF) filters represent a powerful tool to design phasor measurement unit (PMU) algorithms able to estimate synchrophasor, frequency, and rate of change of frequency (ROCOF). The resulting techniques are based on dynamic representations of the synchrophasor, and hence, they are particularly suitable to track the evolution of its parameters during time-varying conditions. Electrical quantities in power systems are typically three-phase and weakly unbalanced, but most PMU measurement techniques are developed by considering them as a set of three single-phase signals; on the contrary, this peculiarity can be favorably exploited to improve accuracy and reduce the computational cost. In this respect, this paper proposes to directly perform the TF expansion of the space vector (SV) samples obtained from three-phase measurements. A new paradigm allows to independently estimate positive and negative sequence synchrophasors along with system frequency and ROCOF, leveraging the three-phase characteristics. The performance of the proposed technique is assessed by using test signals inspired by the standard IEEE C37.118.1-2011, including noise as well as magnitude and phase unbalance. Achieved results highlight the flexibility of the enhanced SV-based approach, which is capable to combine excellent dynamic performance together with an accurate estimation of both positive and negative sequence components

Design of Compressive Sensing Adaptive Taylor-Fourier Comb Filters for Harmonic Synchrophasor Estimation

In modern power systems, phasor measurements are expected to deal with challenging conditions, e.g., fast dynamics and high distortion levels. Taylor-Fourier Multifrequency models represent a promising solution, but their performance is strongly related to the accurate extraction of the signal spectral support. In this context, this paper proposes an enhanced method for support recovery that exploits the inherent block-sparsity properties of electrical signals. The proposed method is fully characterized in diverse and distorted test conditions, inspired by reference standards and real-world scenarios. The comparison against another Compressive Sensing based approach confirms the significant improvement in terms of both recovered support exactness and synchrophasor measurement accuracy

Measurement Platform for Latency Characterization of Wide Area Monitoring, Protection and Control Systems

Wide area monitoring, protection and control (WAMPAC) systems have emerged as a critical technology to improve the reliability, resilience, and stability of modern power grids. They are based on phasor measurement unit (PMU) technology and synchronized monitoring on a wide area. Since these systems are required to make rapid decisions and control actions on the grid, they are characterized by stringent time constraints. For this reason, the latency of WAMPAC systems needs to be appropriately assessed. Following this necessity, this article presents the design and implementation of a measurement platform that allows latency characterization of different types of WAMPAC systems in several operating conditions. The proposed WAMPAC Characterizer has been metrologically characterized through a WAMPAC Emulator and then used to measure the latency of a WAMPAC system based on an open-source platform frequently used by transmission system operators (TSOs) for the implementation of their PMU-based wide area systems

PMU-based distribution system state estimation with adaptive accuracy exploiting local decision metrics and IoT paradigm

A novel adaptive distribution system state estimation (DSSE) solution is presented and discussed, which relies on distributed decision points and exploits the Cloud-based Internet of Things (IoT) paradigm. Up to now, DSSE procedures have been using fixed settings regardless of the actual values of measurement accuracy, which is instead affected by the actual operating conditions of the network. The proposed DSSE is innovative with respect to previous literature, because it is adaptive in the use of updated accuracies for the measurement devices. The information used in the estimation process along with the rate of the execution are updated, depending on the indications of appropriate local metrics aimed at detecting possible variations in the operating conditions of the distribution network. Specifically, the variations and the trend of variation of the rms voltage values obtained by phasor measurement units (PMUs) are used to trigger changes in the DSSE. In case dynamics are detected, the measurement data are sent to the DSSE at higher rates and the estimation process runs consequently, updating the accuracy values to be considered in the estimation. The proposed system relies on a Cloud-based IoT platform, which has been designed to incorporate heterogeneous measurement devices, such as PMUs and smart meters. The results obtained on a 13-bus system demonstrate the validity of the proposed methodology that is efficient both in the estimation process and in the use of the communication resources

Line Impedance Estimation Based on Synchrophasor Measurements for Power Distribution Systems

Effective monitoring and management applications on modern distribution networks (DNs) require a sound network model and the knowledge of line parameters. Network line impedances are used, among other things, for state estimation and protection relay setting. Phasor measurement units (PMUs) give synchronized voltage and current phasor measurements, referred to a common time reference (coordinated universal time). All synchrophasor measurements can thus be temporally aligned and coordinated across the network. This feature, along with high accuracy and reporting rates, could make PMUs useful for the evaluation of network parameters. However, instrument transformer behavior strongly affects the parameter estimation accuracy. In this paper, a new PMU-based iterative line parameter estimation algorithm for DNs, which includes in the estimation model systematic measurement errors, is presented. This method exploits the simultaneous measurements given by PMUs on different nodes and branches of the network. A complete analysis of uncertainty sources is also performed, allowing the evaluation of estimation uncertainty. Issues related to operating conditions, topology, and measurement uncertainty are thoroughly discussed and referenced to a realistic model of a DN to show how a full network estimator is possible

Effect of Unbalance on Positive-Sequence Synchrophasor, Frequency and ROCOF Estimations

Phasor measurement units (PMUs) are the measurement devices fostering the transformation of electric power networks towards the smart grid paradigm. They should accurately measure synchrophasors, frequency, and rate of change of frequency (ROCOF), so that the management and control applications relying on PMU-based distributed monitoring systems can operate effectively. Commercial PMUs performance is typically guaranteed by the compliance with the IEEE standard C37.118.1, which is focused on PMUs for power transmission systems and defines testing conditions and error limits. However, actual operating conditions are much more variable than those covered by the standard, especially when PMUs are used in distribution networks. In particular, the standard does not consider unbalance, which may be negligible neither in transmission nor in distribution grids. For the first time, this paper analyzes the impact of unbalance on the accuracy of four of the most significant classes of signal processing algorithms for PMU measurements. Synchrophasor, frequency, and ROCOF estimation performances under different unbalance conditions are investigated in the test cases suggested by the IEEE C37.242-2013 guide. Novel analytic expressions to predict the errors are derived and validated, and they are proved to be useful for an effective implementation of PMU algorithms intended for both distribution and transmission systems