New visualization technology to enhance situational awareness for system operators
Bibliographic record
Abstract
Summary form only given. System operators have worked with mimic boards and tabular data for years. These mimic boards may or may not have dynamic characteristics such as analog values or equipment status changes. Generally, these boards showed the complete electrical system, and only a small portion of their system had remote terminal units (RTU) to bring the data into the control center. Another area that was lacking was EMS/SCADA. After the August 14, 2003 blackout, the US/Canadian investigation team realized that system operators needed a more dynamic view of not only their system, but also the ability to see into the system of their neighboring utilities. A group of utilities, together with an EMS vendor, began to discuss what the end user (system operator) needed to perform their job. It was soon discovered the EMS system was lacking in various areas. The EMS/SCADA system had some graphical data displays, but wasn't close to being the tool needed to monitor large areas of the system. The EMS vendor also realized that most of the information received on improvements was given by the EMS or SCADA employees of the utilities and not the system operators. While EMS/SCADA employees are good at maintaining and updating software when needed, it is seldom the system operator was asked for input. Information that used to be displayed in tabular form could now be displayed graphically which would aid the system operator in detecting abnormal conditions more rapidly. Also the system operator could look into the neighboring utility's system and determine if the cause of the abnormal condition could have been created by something not within their system. The overview of the electrical grid, which was displayed on a mimic board could now be fully dynamic. Another issue came to light as to how to display this information to the system operator. New display cube (stackable monitors) technology was being introduced into the marketplace and was being used in many different applications. This technology was explored to replace the mimic boards in control centers with outstanding results. Greater monitor (cube) resolutions and new DLP (digital light processing - Texas Instruments) technology to prevent monitor "burn in" and faster computer processing power would open the door to a new way of viewing massive amounts of information on a single wall board. Information could be readily changed on the electronic display wall by the system operator, allowing the display to be used for multiple functions. The system operator could use the display to view critical data and easily switch the display back to an overall view. Enhancing situational awareness of a system operator was another area that received attention from the blackout investigation committee. This involved the interface between the system operator and the various tools they used to monitor the electrical grid. Situational awareness (SA) has become a "buzz" word in the electrical industry. SA of a control room is developed by interviewing system operators and performing a cognitive task analysis on the information required by the operators. This ensures the proper information is easily accessible and that it can be easily understood by the system operator. Combining the new software tools for EMS/SCADA to provide information, the display technology to create an environment to place this information, and the situational awareness aspect, are all steps that are required to enable employees to better make critical decisions during normal and emergency situations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.136 | 0.012 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".