Engineering topics

Ahmad, Tawsif

Publications and source records attributed to Ahmad, Tawsif.

6 records

DOE OSTI2026

Cloud-Based Demonstration of the Eastern Interconnection Situational Awareness Monitoring System (ESAMS)

This report describes a cloud-based implementation and field demonstration of the Eastern Interconnection Situational Awareness and Monitoring System (ESAMS). ESAMS was developed to support the detection and source localization of forced oscillations using synchrophasor measurements from tie-lines connecting areas served by different reliability coordinators (RCs), so that RCs could better coordinate their response to wide-area events. A previous effort had identified deployment barriers associated with hosting shared situational awareness tools at a single RC. To address these barriers, ESAMS was migrated to Amazon Web Services and evaluated in a six-month field demonstration. ISO New England (ISO-NE) and PJM streamed data to the platform using AWS Direct Connect and a site-to-site VPN, respectively. The resulting multi-utility measurement footprint enabled regional source localization across major portions of the U.S. Eastern Interconnection and supported routine identification of oscillation events. During the final three months of the trial, 24 events above 2 MW/MVAR were detected. The largest detected oscillation approached a 25 MW peak-to-peak amplitude, and the longest persisted intermittently for more than 11 hours. The demonstration also assessed operational considerations—including data transfer volumes, end-to-end latency, and cloud computing costs—and found that network and compute requirements were modest relative to typical cloud capabilities while providing performance comparable to prior on-premises deployments. Overall, the results indicate that cloud hosting can provide a practical path to shared interconnection-wide oscillation monitoring. The cloud ESAMS demonstration establishes a foundation for broader utility participation and for building future wide-area analytics that leverage measurements across organizational boundaries.

Follum, James D.↗

DOE OSTI2026

Western Interconnect Transmission Line Wildfire Risk

The datasets contain wildfire risk probabilities for transmission lines in the Western Interconnect, identified only by the HIFLD dataset identifier. The dataset is generated using PNNL's WREST Tool (https://www.pnnl.gov/projects/wildfire-risk-resilience/tools/wrest). The input dataset includes HIFLD datasets on transmission lines and wildfire burn potentials and flame lengths from the PNNL RADR-FIRE Tool for 2025.

psps↗

DOE OSTI2025

An Open-Access Repository of Synchrophasor Data Quality Examples: Curation and Example Applications

Synchrophasor measurements are critical in providing wide-area situational awareness to power system operators. However, data artifacts may be introduced due to various issues such as loss of communication, loss of GPS signal, internal clock error, and vendor-specific implementation of phasor estimation algorithms. Tools designed to provide actionable insights from synchrophasor data, hence, must be designed to be robust to these data quality issues. In this work, two years of synchrophasor data sourced from multiple electric utilities in the United States were analyzed to identify examples of data quality problems. These examples were then labeled and published in the Grid Event Signature Library, a publicly available repository of power system measurements hosted by the Oak Ridge National Laboratory. This paper describes the data curation process, and illustrates two application use cases where the dataset can be valuable to the research community. In the first use case, a random forest classifier is trained to distinguish power system disturbance signatures from data anomalies introduced in synchrophasor measurements due to clock errors. The second use case studies the impact of data quality issues on an example synchrophasor application (specifically, event start time determination). The choice of data quality problems investigated is informed by the examples in the repository curated in this work.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Enhancing Solar Power Forecasting with Regularized Constrained Quantile Regression Averaging and Bootstrapping Techniques

Probabilistic solar power forecasting (SPF) plays an essential role in optimizing power-grid operations by quantifying the forecast uncertainty. To improve the accuracy and robustness of probabilistic SPF, this paper introduces the regularized constrained quantile regression averaging (rCQRA) method to combine outputs from multiple PSPF models. In addition, a bootstrapping method was used to quantify model uncertainty, providing insights into the reliability and significance of each ensemble component. To evaluate its efficacy, the proposed rCQRA method is used to integrate four PSPF methods. The resulting SPF models are trained and validated using a real-world six-year dataset from a rooftop solar plant in the USA. The performance of the proposed rCQRA method is evaluated and compared with two benchmark methods under three categories of weather conditions. It is shown that the rCQRA method has superior performance in its forecast reliability, sharpness, and accuracy.

Ensemble learning, probabilistic solar power forec↗

DOE OSTI2024

Cloud-based Testbed for Adaptive Under-Frequency Load Shedding with High DER Penetration

Increasing penetration of distributed energy resources and behind-the-meter renewables may soon disrupt the efficacy of critical protection schemes, such as under-frequency load shedding (UFLS). Improved data exchange and coordination across the transmission-distribution boundary will be required to maintain reliability of bulk electric system. Standards-based data integration platforms using agreed-upon semantic vocabularies, such as the Common Information Model, will be key to enabling adaptive protection schemes requiring synthesized data from both the bulk power system and behind-the-meter resources. This paper introduces a cloud-based open-source data integration environment and UFLS clustering algorithm being developed to enable adaptive relay coordination between transmission and distribution utilities in the state of Vermont.

Anderson, Alexander A.↗

DOE OSTI2024

Statistical Performance of Forced Oscillation Detectors in the Presence of Missing Measurements

In bulk power systems, measurement-based monitoring for large oscillations can help maintain system reliability. One of the challenges encountered in a recent field demonstration was the unavailability of measurements due to underlying measurement quality or communication problems. During the demonstration, the oscillation detector ignored a measurement location if even 10 seconds of data was missing. To extend the detector's ability to operate in these conditions, this paper evaluates the impact of three methods for addressing missing data. The strengths and weaknesses of each approach are evaluated using theoretical expressions for the probability of detection along with results from simulated data and publicly available field measurements. Based on these results, a suitable approach is identified that can extend the oscillation detector's performance when large segments of data are missing.

Follum, James D.↗