As the power grid continues to evolve with advanced wide‐area monitoring, protection, and control (WAMPAC) algorithms, there is an increasing need for realistic testbed environments with ...industry‐grade software and hardware‐in‐the‐loop (HIL) to perform verification and validation studies. Such testbed environments serve as ideal platforms to perform WAMPAC prototyping, operator training, and also to study the impacts of different types of cyberattack scenarios on the operation of the grid. In this study, the authors introduce pacific northwest national laboratory(PNNL) cyber‐physical systems testbed (PRIME): the testbed that integrates real‐time transmission system simulator with commercial industry‐grade energy management system software and remote HIL (RHIL). PRIME is an end‐to‐end, modular testbed that allows high‐fidelity RHIL experimentation of a power system. We present two detailed case studies (fault location and clearing in the transmission system and operator training) to show the capabilities of their PRIME testbed. Finally, we briefly discuss some of the potential limitations of their testbed in terms of scalability and flexibility to set up larger test systems and identify directions for future work to address these limitations.
High-quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMUs, measurement-based approach for model validation has ...gained significant prominence. In this approach, the quality of a model is analyzed by visually comparing measured generator response with the model-based simulated response for large system disturbances. This paper proposes a new set of performance metrics to assess the model validation results to facilitate automation of the model validation process. In the proposed methodology, first, the slow governor response and comparatively faster oscillatory response are separated, and then a separate set of performance metrics is calculated for each of these two components. These proposed metrics quantify the mismatch between the actual and model-based response in a comprehensive manner without missing any information enabling automation of the process. Furthermore, in this paper, we are also proposing that the sensitivity analysis for model calibration be performed with respect to the proposed metrics for the systematic identification of key parameters. Results obtained using both simulated and real-world case-studies validate the effectiveness of the proposed performance metrics for model validation and their application to the sensitivity analysis for model calibration.
This paper derives an improved version of a periodogram detector for detecting forced oscillations (FOs) in power systems using synchrophasor measurements. FOs are usually periodic in nature and are ...often accompanied with multiple harmonic components. This harmonic information of FOs is incorporated into the proposed periodogram detector, which significantly improves its detection performance for a given probability of a false alarm. The original periodogram detector carries out detection of each component of FOs separately, even though they are related through their harmonics. In the proposed periodogram detector, the detection algorithm is re-derived by incorporating harmonic information such that the detector now looks for a combination of harmonic components of FOs for detection. This derivation shows a significant improvement in the detection performance of the proposed periodogram detector as compared to the original one. This is also illustrated by the results obtained by implementing the proposed periodogram detector on the simulated and real-world PMU measurements.
Electromechanical modes are inherent to any interconnected power systems which provide a measure of the small-signal stability margin of the system. A number of algorithms have been developed for the ...estimation of these modes using synchrophasor measurements. However, most of these algorithms are not designed to operate in the presence of forced oscillations (FO). These FOs are results of periodic rogue input driving the system. When FOs are present, estimates of system modes can be biased depending on the frequency and the amplitude of the FOs. To tackle this problem, a new algorithm is proposed in this paper to estimate system modes in the presence of FOs. In the proposed method, the over-determined modified Yule-Walker method which is used to estimate autoregressive coefficients of an autoregressive moving average (ARMA) signal model is extended to an ARMA with exogenous input (ARMAX) model that incorporates the presence of FOs. Two versions of the proposed method are included in this paper based on the requirement of the information of the duration of FOs in the signal. Results obtained by implementing the proposed algorithm on simulated data and real-world data validate the effectiveness of both versions of the proposed method.
High-quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMUs, measurement-based approach for model validation has ...gained significant prominence. In this approach, the quality of a model is analyzed by visually comparing measured generator response with the modelbased simulated response for large system disturbances. This paper proposes a new set of performance metrics to assess the model validation results to facilitate automation of the model validation process. In the proposed methodology, first, the slow governor response and comparatively faster oscillatory response are separated, and then a separate set of performance metrics is calculated for each of these two components. These proposed metrics quantify the mismatch between the actual and model-based response in a comprehensive manner without missing any information enabling automation of the process. Furthermore, in this paper, we are also proposing that the sensitivity analysis for model calibration be performed with respect to the proposed metrics for the systematic identification of key parameters. Results obtained using both simulated and real-world case-studies validate the effectiveness of the proposed performance metrics for model validation and their application to the sensitivity analysis for model calibration.
This paper provides an overview of hyperloop technologies, including a brief discussion of key components of a hyperloop system that determine the electric power requirements as a function of time. ...At-scale hyperloop systems do not yet exist, so a model was used to generate a set of load profiles for conceptual hyperloop realizations at four locations in the United States: two systems in California and one each in Colorado and Ohio. In all four cases, the modeled hyperloop load profiles included pulses in both active and reactive power. Grid modeling was performed to estimate the grid impacts and for discussing grid integration challenges. The paper discusses how energy storage systems might be used to eliminate the pulsating load characteristics or significantly reduce it to accommodate current grid planning guidelines.
This paper derives an improved version of a periodogram detector for detecting forced oscillations (FOs) in power systems using synchrophasor measurements. FOs are usually periodic in nature and are ...often accompanied with multiple harmonic components. This harmonic information of FOs is incorporated into the proposed periodogram detector, which significantly improves its detection performance for a given probability of a false alarm. The original periodogram detector carries out detection of each component of FOs separately, even though they are related through their harmonics. In the proposed periodogram detector, the detection algorithm is re-derived by incorporating harmonic information such that the detector now looks for a combination of harmonic components of FOs for detection. This derivation shows a significant improvement in the detection performance of the proposed periodogram detector as compared to the original one. This is also illustrated by the results obtained by implementing the proposed periodogramdetector on the simulated and real-world PMU measurements.
High quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMU measurements, measurement-based approach for model ...validation has gained significant prominence. Currently, the model validation results are analyzed by visually comparing real-world PMU measurements with the model-based simulated data. This paper proposes metrics to quantify the generator dynamic model validation results based on the response of generators to each system mode, which includes both local and inter-area, using modal analysis approach. The metrics provide information on the inaccuracy associated with the model in terms of the characteristics of each mode. Initial results obtained using the real-world data validates the effectiveness of the proposed metrics. In this paper, modal analysis was carried out using Prony method.
With an increase in the oscillation events observed in the U.S. Eastern Interconnection (EI), it has become increasingly important to have a good understanding of the EI system oscillatory behavior. ...However, as compared to the Western Interconnection system (WI), not much work has been done in this regard for the EI system. Therefore, in this paper, a thorough analysis is carried out to identify inter-area modes and their properties for the EI system using a 80000+ bus real EI model. Multi-channel Prony method is used in this paper for estimating system modes and mode-shapes.
Electromechanical modes are inherent to any interconnected power systems which provide a measure of the smallsignal stability margin of the system. A number of algorithms have been developed for the ...estimation of these modes using synchrophasor measurements. However, most of these algorithms are not designed to operate in the presence of forced oscillations (FO). These FOs are results of periodic rogue input driving the system. When FOs are present, estimates of system modes can be biased depending on the frequency and the amplitude of the FOs. To tackle this problem, a new algorithm is proposed in this paper to estimate system modes in the presence of FOs. In the proposed method, the over-determined modified Yule-Walker method which is used to estimate autoregressive coefficients of an autoregressive moving average (ARMA) signal model is extended to an ARMA with exogenous input (ARMAX) model that incorporates the presence of FOs. Two versions of the proposed method are included in this paper based on the requirement of the information of the duration of FOs in the signal. Results obtained by implementing the proposed algorithm on simulated data and real-world data validate the effectiveness of both versions of the proposed method.
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