Distributed adaptive signal processing for frequency estimation

It is widely recognised that future smart grids will heavily rely upon intelligent communication and signal processing as enabling technologies for their operation. Traditional tools for power system analysis, which have been built from a circuit theory perspective, are a good match for balanced system conditions. However, the unprecedented changes that are imposed by smart grid requirements, are pushing the limits of these old paradigms. To this end, we provide new signal processing perspectives to address some fundamental operations in power systems such as frequency estimation, regulation and fault detection. Firstly, motivated by our finding that any excursion from nominal power system conditions results in a degree of non-circularity in the measured variables, we cast the frequency estimation problem into a distributed estimation framework for noncircular complex random variables. Next, we derive the required next generation widely linear, frequency estimators which incorporate the so-called augmented data statistics and cater for the noncircularity and a widely linear nature of system functions. Uniquely, we also show that by virtue of augmented complex statistics, it is possible to treat frequency tracking and fault detection in a unified way. To address the ever shortening time-scales in future frequency regulation tasks, the developed distributed widely linear frequency estimators are equipped with the ability to compensate for the fewer available temporal voltage data by exploiting spatial diversity in wide area measurements. This contribution is further supported by new physically meaningful theoretical results on the statistical behavior of distributed adaptive filters. Our approach avoids the current restrictive assumptions routinely employed to simplify the analysis by making use of the collaborative learning strategies of distributed agents. The efficacy of the proposed distributed frequency estimators over standard strictly linear and stand-alone algorithms is illustrated in case studies over synthetic and real-world three-phase measurements. An overarching theme in this thesis is the elucidation of underlying commonalities between different methodologies employed in classical power engineering and signal processing. By revisiting fundamental power system ideas within the framework of augmented complex statistics, we provide a physically meaningful signal processing perspective of three-phase transforms and reveal their intimate connections with spatial discrete Fourier transform (DFT), optimal dimensionality reduction and frequency demodulation techniques. Moreover, under the widely linear framework, we also show that the two most widely used frequency estimators in the power grid are in fact special cases of frequency demodulation techniques. Finally, revisiting classic estimation problems in power engineering through the lens of non-circular complex estimation has made it possible to develop a new self-stabilising adaptive three-phase transformation which enables algorithms designed for balanced operating conditions to be straightforwardly implemented in a variety of real-world unbalanced operating conditions. This thesis therefore aims to help bridge the gap between signal processing and power communities by providing power system designers with advanced estimation algorithms and modern physically meaningful interpretations of key power engineering paradigms in order to match the dynamic and decentralised nature of the smart grid.Open Acces

Performance Improvement of Wide-Area-Monitoring-System (WAMS) and Applications Development

Wide area monitoring system (WAMS), as an application of situation awareness, provides essential information for power system monitoring, planning, operation, and control. To fully utilize WAMS in smart grid, it is important to investigate and improve its performance, and develop advanced applications based on the data from WAMS. In this dissertation, the work on improving the WAMS performance and developing advanced applications are introduced.To improve the performance of WAMS, the work includes investigation of the impacts of measurement error and the requirements of system based on WAMS, and the solutions. PMU is one of the main sensors for WAMS. The phasor and frequency estimation algorithms implemented highly influence the performance of PMUs, and therefore the WAMS. The algorithms of PMUs are reviewed in Chapter 2. To understand how the errors impact WAMS application, different applications are investigated in Chapter 3, and their requirements of accuracy are given. In chapter 4, the error model of PMUs are developed, regarding different parameters of input signals and PMU operation conditions. The factors influence of accuracy of PMUs are analyzed in Chapter 5, including both internal and external error sources. Specifically, the impacts of increase renewables are analyzed. Based on the analysis above, a novel PMU is developed in Chapter 6, including algorithm and realization. This PMU is able to provide high accurate and fast responding measurements during both steady and dynamic state. It is potential to improve the performance of WAMS. To improve the interoperability, the C37.118.2 based data communication protocol is curtailed and realized for single-phase distribution-level PMUs, which are presented in Chapter 7.WAMS-based applications are developed and introduced in Chapter 8-10. The first application is to use the spatial and temporal characterization of power system frequency for data authentication, location estimation and the detection of cyber-attack. The second application is to detect the GPS attack on the synchronized time interval. The third application is to detect the geomagnetically induced currents (GIC) resulted from GMD and EMP-E3. These applications, benefited from the novel PMU proposed in Chapter 6, can be used to enhance the security and robust of power system

Computationally-Efficient Synchrophasor Estimation: Delayed in-quadrature Interpolated DFT

The paper proposes a synchropahsor estimation (SE) algorithm that leverages the use of a delayed in-quadrature complex signal to mitigate the self-interference of the fundamental tone. The estimator, which uses a three-point IpDFT combined with a three-cycle Hanning window, incorporates a new detection mechanism to iteratively estimate and remove the effects caused by interfering tones within the out-of-band interference (OOBI) range. The main feature of the method is its ability to detect interfering tones with an amplitude lower than that adopted by the IEC/IEEE Std. 60255-118, this detection being notably challenging. Furthermore, it simultaneously satisfies all the accuracy requirements for the P and M phasor measurement unit (PMU) performance classes, while offering a reduction in the total computational cost compared to other state-of-the-art techniques. Despite an increase in total memory requirements, a preliminary analysis reveals its suitability for implementation on embedded devices.Comment: 15 pages, 15 figures. Article submitted for consideration to IEEE Transactions on Instrumentation and Measurement. (Non peer reviewed

Computationally Efficient Synchrophasor Estimation: Delayed In-Quadrature Interpolated DFT

This article proposes a synchrophasor estimation (SE) algorithm that leverages the use of a delayed in-quadrature complex signal to mitigate the self-interference of the fundamental tone. The estimator, which uses a three-point IpDFT combined with a three-cycle Hanning window, incorporates a new detection mechanism to iteratively estimate and remove the effects caused by interfering tones within the out-of-band interference (OOBI) range. The main feature of the method is its ability to detect interfering tones with an amplitude lower than that adopted by the IEC/IEEE Std. 60255-118, this detection being notably challenging. Furthermore, it simultaneously satisfies all the accuracy requirements for the P and M phasor measurement unit (PMU) performance classes while offering a reduction in the total computational cost compared with other state-of-the-art techniques

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

Control System Design, Analysis, and Simulation of a Photovoltaic Inverter for Unbalanced Load Compensation in a Microgrid

This thesis presents a control scheme for a single-stage three-phase Photovoltaic (PV) converter with negative sequence load current compensation. In this thesis a dual virtual impedance active damping technique for an LCL filter is proposed to address the issue of LCL filter resonance. Both inverter-side current and the capacitor current are used in the feedback loop. Using both signals provides higher DC rejection than using capacitor current alone. The proposed active damping scheme results in a faster transient response and higher damping ratio than can be obtained using inverter-side current alone. The feedback gains can be calculated to achieve a specified damping level. A method of determining the gains of the Proportional and Resonant current controller based on frequency response characteristics is presented. For a specified set of gain and phase margins, the controller gains can be calculated explicitly. Furthermore, a modification is proposed to prevent windup in the resonator. A numerically compensated Half-Cycle Discrete Fourier Transform (HCDFT) method is developed to calculate the negative sequence component of the load current. The numerical compensation allows the HCDFT to accurately estimate the fundamental component of the load current under off-nominal frequency conditions. The proposed HCDFT method is shown to have a quick settling time that is comparable to that obtained with conventional sequence compensation techniques as well as immunity to harmonics in the input signal. The effect of unbalance compensation on the PV power output depending on the irradiance and the operational region on the power-voltage curve is examined. Analysis of the DC link voltage ripple shows the region of operation on the P-V curve affects the amplitude of the DC link voltage ripple during negative sequence compensation. The proposed control scheme is validated by simulation in the Matlab/Simulink® environment. The proposed control scheme is tested in the presence of excessive current imbalance, unbalanced feeder impedances, and non-linear loads. The results have shown that the proposed control scheme can improve power quality in a hybrid PV-diesel microgrid by reducing both voltage and current imbalance while simultaneously converting real power from a PV array

On the importance of characterizing virtual pmus for hardware‐in‐the‐loop and digital twin applications

open5noThis research was funded by EdgeFLEX, grant number 883710. This project received funding from the European Union’s Horizon 2020 research and innovation program.In recent years, the introduction of real‐time simulators (RTS) has changed the way of researching the power network. In particular, researchers and system operators (SOs) are now ca-pable of simulating the complete network and of making it interact with the real world thanks to the hardware‐in‐the‐loop (HIL) and digital twin (DT) concepts. Such tools create infinite scenarios in which the network can be tested and virtually monitored to, for example, predict and avoid faults or energy shortages. Furthermore, the real‐time monitoring of the network allows estimating the status of the electrical assets and consequently undertake their predictive maintenance. The success of the HIL and DT application relies on the fact that the simulated network elements (cables, gener-ation, accessories, converters, etc.) are correctly modeled and characterized. This is particularly true if the RTS acquisition capabilities are used to enable the HIL and the DT. To this purpose, this work aims at emphasizing the role of a preliminary characterization of the virtual elements inside the RTS system, experimentally verifying how the overall performance is significantly affected by them. To this purpose, a virtual phasor measurement unit (PMU) is tested and characterized to understand its uncertainty contribution. To achieve that, firstly, the characterization of a virtual PMU calibrator is described. Afterward, the virtual PMU calibration is performed, and the results clearly highlight its key role in the overall uncertainty. It is then possible to conclude that the characterization of the virtual elements, or models, inside RTS systems (omitted most of the time) is fundamental to avoid wrong results. The same concepts can be extended to all those fields that exploit HIL and DT capa-bilities.openMingotti A.; Costa F.; Cavaliere D.; Peretto L.; Tinarelli R.Mingotti A.; Costa F.; Cavaliere D.; Peretto L.; Tinarelli R

Dealing with front-end white noise on differentiated measurements such as frequency and ROCOF in power systems

This paper describes the way that white noise (including quantised input section sampling) imparts errors onto frequency and rate-of-change-of-frequency (ROCOF) measurements. The main paper focus concerns the use of filtered heterodyned (i.e. Fourier) analyses for single-phase and 3-phase systems, and the filtered Clarke transform for 3-phase systems. The rules and equations governing the effect of white noise on frequency and ROCOF are formulated for these techniques, explaining the subtle effects of aliasing, splitting signals and noise into their positive and negative frequency components, and the correlation or de-correlation of noise. It is shown that - as expected - for 3-phase AC measurements, averaging 3 single-phase Fourier measurements produces the same performance against noise as using a method based on Clarke’s transform, if identical filtering is used. Furthermore, by understanding the theory behind the frequency and ROCOF measurement processes, it is shown that to achieve the lowest RMS errors, in the presence of front-end white noise (alone, ignoring other dynamic signal and power quality aspects), a filter which provides ~40 dB/decade attenuation (i.e. a 2-boxcar cascade) is recommended for a frequency measurement, but a filter which rolls off at ~60 dB/decade (i.e. a 3-boxcar cascade) is recommended for a ROCOF measurement

Gain Normalized Adaptive Observer For Three-Phase System

International audienceThis paper proposes the estimation of parameters and symmetrical components of unbalanced grid using adaptive observer framework. Recent adaptive observers proposed in the literature doesn’t employ any gain normalization in their frequency estimation loop. This can be problematic in the presence of large voltage dip. This paper proposes a solution to overcome this limitation using a novel gain normalized - frequency-locked loop (GN-FLL). Technical details of GN-FLL, stability analysis and tuning are provided in this paper. Comparative experimental results with adaptive Luenberger observer, second-order generalized integrator - phase-locked loop (SOGI-PLL) and enhanced PLL (EPLL) are provided to demonstrate the effectiveness the proposed technique in the single-phase case. Comparative experimental results with double SOGI-FLL (DSOGI-FLL) and adaptive notch filter (ANF) are provided to demonstrate the effectiveness the proposed technique in the three-phase case