Carlos Augusto Duque

With the increasing digitization of substations and the growing complexity of the global energy landscape, this study proposes an innovative architecture for a Substation Edge Device (SED). The architecture optimizes data distribution for various applications by leveraging containerization and a message broker. By consolidating the functionalities of multiple physical Intelligent Electronic Devices (IEDs) into a unified hardware platform, each function operates as a standalone software component. This approach is built upon a containerized infrastructure that ensures portability, scalability, and isolation. To facilitate efficient data distribution, a message broker is incorporated into the system, alongside a management container responsible for monitoring Key Performance Indicators (KPIs) and ensuring the proper operation of all applications. The proposed SED architecture is validated through performance results that include data acquisition, timestamp accuracy, broker propagation delay, and management functionality. Additionally, a novelty detection application is demonstrated, generating oscillographies using data from Real Time Digital Simulator (RTDS).

Transmission line parameter estimation is a critical issue for power system operation and planning studies.With the advent of synchrophasor technology, numerous newmethods have been developed using PMUs (Phasor Measurement Units) based on real-time measurements from the sending and receiving ends of a transmission line. Typically, the equivalent PI section of the line is determined for the fundamental frequency only. For other harmonic orders, impedances can be measured at specific points in the electric network using a frequency scan approach. However, few studies have focused on the separate estimation of all longitudinal resistances, reactances and shunt admittances for higher harmonic orders. This paper presents a novel approach to this long-standing issue by formulating an optimization problem, where the least squares equation is minimized, subject to inequality constraints associated with the harmonic impedances of a transmission line, modeled with a quadrupole representation. The proposed optimization method allows for the estimation of line impedance parameters with reduced errors for all harmonic orders considered in the analysis. Computational simulations are carried out to demonstrate the applicability of the method, using different line models including a real Brazilian transmission line, and the impact of instrument transformers on the estimated results is also assessed.

This paper presents a novel methodology to estimate the harmonic transfer impedances in electric power systems with multiple harmonic sources (HSs). The purpose is to determine the responsibility of each HS for the total harmonic distortion at a specific bus within the system, addressing a critical issue in the power quality field. To achieve this objective, it is necessary to estimate not only the individual HS, but also the transfer impedances between each source and the bus under analysis (BUA). Most methods for solving this problem are based on proper network modeling or restrict variations in harmonic sources to a single source at a time. The proposed methodology has overcome this limitation. For this, synchronized current and voltage phasors are measured at the BUA. Once the measurements are gathered, the Independent Component Analysis (ICA) method is applied to estimate the Norton equivalent. The harmonic transfer impedance (HTI) is then determined using the information provided by the ICA. To enhance the accuracy of HTI estimation, three procedures are employed for data mining the parameters provided by ICA over time to generate a well-conditioned system. Once the HTI is satisfactorily determined, the individual harmonic contributions (IHCs), i.e., the harmonic responsibility, can be estimated accurately. The effectiveness and performance of the method are demonstrated based on computational simulations using distribution and transmission systems. Additionally, the methodology is validated with real data collected from a Brazilian transmission system monitored by synchronized power quality measurement units. Simulated results show that the Total Vector Error (TVE) is less than 0.4%, and for the field data test, the TVE is less than 2%.

In real-world scenarios, deviations in the frequency response of instrumentation transformers can lead to distorted harmonic measurements, highlighting the critical role harmonic measurement plays in assessing power quality. The blind channel equalization technique offers a potential solution to improve the frequency response of a large number of instrumentation transformers already installed in substations. These transformers were designed to accurately measure only the fundamental phasor component. Therefore, in order to use them for harmonic phasor measurement, methodologies for reducing frequency distortion must be applied. In this work, we propose a novel approach to improve the frequency response of the instrument transformer using adaptive blind equalization. The blind technique can compensate for distortions caused by voltage and current transducers without requiring prior knowledge of input signals or circuit characteristics. The proposed methodology uses a Linear Prediction Filter to convert the colored noise present at the channel output into white noise. Furthermore, a genetic algorithm is used to find a pole to cancel possible zeroes present in the frequency response of some transducers. The main advantage of blind equalization with the genetic algorithm is its independence, operating without clear information about the channel or the input signal. Through extensive experimentation, we demonstrate the effectiveness of the proposed methodology in significantly reducing the absolute error in ratio and phase caused by current and voltage transformers. Simulated and laboratory experiments are presented in this paper.

The fundamental component synchrophasors are widely used nowadays, based on the use of phasor measurement units (PMUs), in several applications in electrical power systems. For the advancement of monitoring technology, harmonic synchrophasor estimation is still a challenge. To make it possible, it is necessary to correctly estimate the harmonic phasor (magnitude and phase of each harmonic component), mainly in scenarios with frequency deviations and noise. In this context, this present article proposes the use of B-spline-based interpolation as a preprocessing algorithm for the discrete Fourier transform (DFT). The performance is evaluated in terms of total vector error (TVE) considering the tests proposed by the IEEE C37.118.1 and IEC 60255-118-1 standards and compared with four different harmonic phasor estimation (HPE) methods, the HPE, sinc interpolation function-based estimator (SIFE), Taylor–Fourier transform (TFT), and flat-top finite impulse response (FT FIR). The proposed method can provide a TVE below 1% for all harmonic phasors, from the first to the fiftieth order, under significant frequency deviation. Also, for real-time validation, the proposed method was implemented in an industrial computer as a software routine capable of processing the signals in real time. The signals are acquired by a commercial merging unit (MU) and the samples are published using the IEC 61850 sampled values (SVs) protocol.

The increasing share of power electronic (PE) devices in public electricity networks has increased the chance of harmonic instabilities, which are caused by the interaction of the device control with the network impedance. Usually, the detailed internal design of PE devices is not available and only measurement-based black-box approaches are feasible for the analysis of harmonic instabilities. A major drawback of such black-box approaches is the need for expensive programmable grid simulators. To overcome that issue, this article proposes a new approach to identify the sensitivity of a PE device for harmonic instabilities, which solely requires two air coils and which can simply be connected to any available power supply including the low voltage (LV) network. By systematically increasing the resulting inductance of air coils, the proposed method is able to identify the frequency regions that are critical with regard to the harmonic stability of the PE device. Critical frequency regions are determined by analyzing the measurement results in time-frequency domain using the estimation of signal parameters via rotational invariance techniques (ESPRITs). The proposed method is applied to a commercially available single-phase photovoltaic (PV) inverter. The critical frequency region has been determined at around 500 Hz, which is confirmed by formal stability analysis.