An Integrated Online Dynamic Security Assessment System for Improved Situational Awareness and Economic Operation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The ever-increasing penetration of centralized and distributed renewable energy, power electronics-based transmission equipment and loads, advanced protection and control systems, storage devices and new power market rules all contribute to the growing dynamics and stochastic behaviors being observed in today's grid operation. Understanding operational risks and providing prompt control actions are of great importance to ensure secure and economic operation of a bulk power system. In this paper, a novel integrated online dynamic security assessment system (DSAS) is developed that intakes real-time EMS snapshots combining both bus/branch and node/breaker network models, performs dynamic contingency analysis under various conditions, calculates real-time transfer limits, and provides online control suggestions to mitigate operational risks. Several unique and innovative features are developed to address practical challenges, including: (1) real-time stitching of power flow information from both node/breaker and bus/branch models covering different geographical regions of interest; (2) online corrections and enhancements to power flow and dynamic models; (3) equipment-name-based modelling approaches for complex contingencies and control systems; and (5) distributed computing capabilities for significant computational speed enhancement. The developed DSAS has been deployed in the control center of State Grid Jiangsu Electric Power Company with hundreds of HVAC and 8 (U)HVDC transmission lines, which has been running reliably since Sept. 2018, achieving satisfactory performance in improving situational awareness and economic operation of the power grid.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it