Phasor Estimation for Grid Power Monitoring: Least Square vs. Linear Kalman Filter

International audienc

Shuttle Ku-band signal design study

Carrier synchronization and data demodulation of Unbalanced Quadriphase Shift Keyed (UQPSK) Shuttle communications' signals by optimum and suboptimum methods are discussed. The problem of analyzing carrier reconstruction techniques for unbalanced QPSK signal formats is addressed. An evaluation of the demodulation approach of the Ku-Band Shuttle return link for UQPSK when the I-Q channel power ratio is large is carried out. The effects that Shuttle rocket motor plumes have on the RF communications are determined also. The effect of data asymmetry on bit error probability is discussed

Maximum likelihood frequency estimation in smart grid applications

International audienceThis paper focuses on the estimation of the fundamental frequency in balanced three-phase power systems. Specifically, we propose a Maximum Likelihood Estimator (MLE) that exploits the multidimensional nature of electrical signals. For perfectly sinusoidal signals, we show that the MLE can be expressed according to the periodogram of the instantaneous positive component. For harmonic signals, we demonstrate that the MLE can be approximated by a cumulated periodogram of the zero, positive and negative sequence components. As compared to single-phase estimators, statistical analysis and simulation results prove that the proposed estimator decreases the Mean Square Error by a factor of three, whatever the Signal to Noise Ratio (SNR) or data length. Furthermore, simulations with experimental data show that the proposed technique outperforms classical spectral estimators such as MUSIC

Integrated source and channel encoded digital communication system design study

The particular Ku-band carrier, PN despreading, and symbol synchronization strategies, which were selected for implementation in the Ku-band transponder aboard the orbiter, were assessed and evaluated from a systems performance viewpoint, verifying that system specifications were met. A study was performed of the design and implementation of tracking techniques which are suitable for incorporation into the Orbiter Ku-band communication system. Emphasis was placed on maximizing tracking accuracy and communication system flexibility while minimizing cost, weight, and system complexity of Orbiter and ground systems hardware. The payload communication study assessed the design and performance of the forward link and return link bent-pipe relay modes for attached and detached payloads. As part of this study, a design for a forward link bent-pipe was proposed which employs a residual carrier but which is tracked by the existing Costas loop

Coherent Bayesian inference on compact binary inspirals using a network of interferometric gravitational wave detectors

Presented in this paper is a Markov chain Monte Carlo (MCMC) routine for conducting coherent parameter estimation for interferometric gravitational wave observations of an inspiral of binary compact objects using data from multiple detectors. The MCMC technique uses data from several interferometers and infers all nine of the parameters (ignoring spin) associated with the binary system, including the distance to the source, the masses, and the location on the sky. The Metropolis-algorithm utilises advanced MCMC techniques, such as importance resampling and parallel tempering. The data is compared with time-domain inspiral templates that are 2.5 post-Newtonian (PN) in phase and 2.0 PN in amplitude. Our routine could be implemented as part of an inspiral detection pipeline for a world wide network of detectors. Examples are given for simulated signals and data as seen by the LIGO and Virgo detectors operating at their design sensitivity.Comment: 10 pages, 4 figure

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

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