Advanced Techniques for Power System Identification from Measured Data

Time-synchronized measurements provide rich information for estimating a power-system's electromechanical modal properties via advanced signal processing. This information is becoming critical for the improved operational reliability of interconnected grids. A given mode's properties are described by its frequency, damping, and shape. Modal frequencies and damping are useful indicators of power-system stress, usually declining with increased load or reduced grid capacity. Mode shape provides critical information for operational control actions. This project investigated many advanced techniques for power system identification from measured data focusing on mode frequency and damping ratio estimation. Investigators from the three universities coordinated their effort with Pacific Northwest National Laboratory (PNNL). Significant progress was made on developing appropriate techniques for system identification with confidence intervals and testing those techniques on field measured data and through simulation. Experimental data from the western area power system was provided by PNNL and Bonneville Power Administration (BPA) for both ambient conditions and for signal injection tests. Three large-scale tests were conducted for the western area in 2005 and 2006. Measured field PMU (Phasor Measurement Unit) data was provided to the three universities. A 19-machine simulation model was enhanced for testing the system identification algorithms. Extensive simulations were run with this model to test the performance of the algorithms. University of Wyoming researchers participated in four primary activities: (1) Block and adaptive processing techniques for mode estimation from ambient signals and probing signals, (2) confidence interval estimation, (3) probing signal design and injection method analysis, and (4) performance assessment and validation from simulated and field measured data. Subspace based methods have been use to improve previous results from block processing techniques. Bootstrap techniques have been developed to estimate confidence intervals for the electromechanical modes from field measured data. Results were obtained using injected signal data provided by BPA. A new probing signal was designed that puts more strength into the signal for a given maximum peak to peak swing. Further simulations were conducted on a model based on measured data and with the modifications of the 19-machine simulation model. Montana Tech researchers participated in two primary activities: (1) continued development of the 19-machine simulation test system to include a DC line; and (2) extensive simulation analysis of the various system identification algorithms and bootstrap techniques using the 19 machine model. Researchers at the University of Alaska-Fairbanks focused on the development and testing of adaptive filter algorithms for mode estimation using data generated from simulation models and on data provided in collaboration with BPA and PNNL. There efforts consist of pre-processing field data, testing and refining adaptive filter techniques (specifically the Least Mean Squares (LMS), the Adaptive Step-size LMS (ASLMS), and Error Tracking (ET) algorithms). They also improved convergence of the adaptive algorithms by using an initial estimate from block processing AR method to initialize the weight vector for LMS. Extensive testing was performed on simulated data from the 19 machine model. This project was also extensively involved in the WECC (Western Electricity Coordinating Council) system wide tests carried out in 2005 and 2006. These tests involved injecting known probing signals into the western power grid. One of the primary goals of these tests was the reliable estimation of electromechanical mode properties from measured PMU data. Applied to the system were three types of probing inputs: (1) activation of the Chief Joseph Dynamic Brake, (2) mid-level probing at the Pacific DC Intertie (PDCI), and (3) low-level probing on the PDCI. The Chief Joseph Dynamic Brake is a 1400 MW disturbance to the system and is injected for a half of a second. For the mid and low-level probing, the Celilo terminal of the PDCI is modulated with a known probing signal. Similar but less extensive tests were conducted in June of 2000. The low-level probing signals were designed at the University of Wyoming. A number of important design factors are considered. The designed low-level probing signal used in the tests is a multi-sine signal. Its frequency content is focused in the range of the inter-area electromechanical modes. The most frequently used of these low-level multi-sine signals had a period of over two minutes, a root-mean-square (rms) value of 14 MW, and a peak magnitude of 20 MW. Up to 15 cycles of this probing signal were injected into the system resulting in a processing gain of 15. The resulting measured response at points throughout the system was not much larger than the ambient noise present in the measurements

Autonomous Demand Response for Primary Frequency Regulation

The research documented within this report examines the use of autonomous demand response to provide primary frequency response in an interconnected power grid. The work builds on previous studies in several key areas: it uses a large realistic model (i.e., the interconnection of the western United States and Canada); it establishes a set of metrics that can be used to assess the effectiveness of autonomous demand response; and it independently adjusts various parameters associated with using autonomous demand response to assess effectiveness and to examine possible threats or vulnerabilities associated with the technology

Real-time power system analysis: Feasibility and critical technologies

Modern electrical grids face increasing demands to serve new or unusual loads, to integrate unconventional new resources, and to transmit power in unforeseen ways. These expanding demands will require utilities to operate existing systems closer to steady-state limits, thus increasing the performance requirements of operation and control systems. In this paper we use the challenges posed by power system stability analysis to motivate a discussion of the technologies required to advance the state-of-the-art in real-time power system control. We consider the computational requirements of system stability analysis techniques (transient simulation, eigenanalysis, time-domain fitting, and frequency-response analysis). Additional requirements are imposed by the necessity that the computational results support either human or automated decision making. We then address the role that critical computer and information technologies must play in addressing these needs. Our emphasis is on high performance computing, where we consider both hardware issues and algorithmic requirements. Data management, user interface, visualization, and expert system technologies are also discussed. We conclude by suggesting elements of a strategic plan for creating the next generation of computer tools for power system analysis, and for their use in real-time control applications. 18 refs

Biomechanical Material Characterization of Stanford Type-B Dissected Porcine Aortas

Aortic dissection (AD) involves tearing of the medial layer, creating a blood-filled channel called false lumen (FL). To treat dissections, clinicians are using endovascular therapy using stent grafts to seal the FL. This procedure has been successful in reducing mortality but has failed in completely re-attaching the torn intimal layer. The use of computational analysis can predict the radial forces needed to devise stents that can treat ADs. To quantify the hyperelastic material behavior for therapy development, we harvested FL wall, true lumen (TL) wall, and intimal flap from the middle and distal part of five dissected aortas. Planar biaxial testing using multiple stretch protocols were conducted on tissue samples to quantify their deformation behavior. A novel non-linear regression model was used to fit data against Holzapfel–Gasser–Ogden hyperelastic strain energy function. The fitting analysis correlated the behavior of the FL and TL walls and the intimal flap to the stiffness observed during tensile loading. It was hypothesized that there is a variability in the stresses generated during loading among tissue specimens derived from different regions of the dissected aorta and hence, one should use region-specific material models when simulating type-B AD. From the data on material behavior analysis, the variability in the tissue specimens harvested from pigs was tabulated using stress and coefficient of variation (CV). The material response curves also compared the changes in compliance observed in the FL wall, TL wall, and intimal flap for middle and distal regions of the dissection. It was observed that for small stretch ratios, all the tissue specimens behaved isotropically with overlapping stress–stretch curves in both circumferential and axial directions. As the stretch ratios increased, we observed that most tissue specimens displayed different structural behaviors in axial and circumferential directions. This observation was very apparent in tissue specimens from mid FL region, less apparent in mid TL, distal FL, and distal flap tissues and least noticeable in tissue specimens harvested from mid flap. Lastly, using mixed model ANOVAS, it was concluded that there were significant differences between mid and distal regions along axial direction which were absent in the circumferential direction

Detection of Periodic Beacon Loads in Electrical Distribution Substation Data

This research explores methods for identifying a whether a load is sending a signal to the utility SCADA system. Such a system can identify whether various loads are signialing using existing SCADA infrastructure, that is, without added, high cost communications infrastructure

Modelling, Simulation and Fuzzy Self-Tuning Control of D-STATCOM in a Single Machine Infinite Bus Power System

© 2019 Bentham Science Publishers. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.2174/2352096511666180314141205In recent years, demand for electricity has increased considerably, while the expansion of generation and transmission has been very slow due to limited investment in resources and environmental restrictions. Methods: As a result, the power system becomes vulnerable to disturbances and instability. FACTS (Flexible AC Transmission Systems) technology has now been accepted as a potential solution to this problem. This paper deals with the modelling, simulation and fuzzy self-tuning control of a D-STATCOM to enhance the stability and improve the critical fault clearing time(CCT) in a single machine infinite bus (SMIB).A detailed modelling of the D-STATCOM and comprehensive derivation of the fuzzy logic self-tuning control is presented. Results: The dynamic performance of the power system with the proposed control scheme is validated through in a simulation study carried out under Matlab/Simulink and SimPowerSystems toolbox. Conclusion: The results demonstrate a significant enhancement of the power system stability under the simulated fault conditions considered.Peer reviewe

MANGO ? Modal Analysis for Grid Operation: A Method for Damping Improvement through Operating Point Adjustment

Small signal stability problems are one of the major threats to grid stability and reliability in the U.S. power grid. An undamped mode can cause large-amplitude oscillations and may result in system breakups and large-scale blackouts. There have been several incidents of system-wide oscillations. Of those incidents, the most notable is the August 10, 1996 western system breakup, a result of undamped system-wide oscillations. Significant efforts have been devoted to monitoring system oscillatory behaviors from measurements in the past 20 years. The deployment of phasor measurement units (PMU) provides high-precision, time-synchronized data needed for detecting oscillation modes. Measurement-based modal analysis, also known as ModeMeter, uses real-time phasor measurements to identify system oscillation modes and their damping. Low damping indicates potential system stability issues. Modal analysis has been demonstrated with phasor measurements to have the capability of estimating system modes from both oscillation signals and ambient data. With more and more phasor measurements available and ModeMeter techniques maturing, there is yet a need for methods to bring modal analysis from monitoring to actions. The methods should be able to associate low damping with grid operating conditions, so operators or automated operation schemes can respond when low damping is observed. The work presented in this report aims to develop such a method and establish a Modal Analysis for Grid Operation (MANGO) procedure to aid grid operation decision making to increase inter-area modal damping. The procedure can provide operation suggestions (such as increasing generation or decreasing load) for mitigating inter-area oscillations