In the electric utility industry, displays provide power system operators with information on and the status of the system, who then make decisions on how to maintain the safety, the reliability and the efficient operation of the utility generation and transmission grid based on that information. Complexity of the data presented and the display itself can lead to errors or misjudgments that can cause power system operators to make unwise decisions. The primary goal of this research was to develop a method to quantify display complexity for select displays used by system operators when operating the electric generation and transmission grids. Three studies were performed: (1) complexity measure development, (2) validation of the measure using usability and situation awareness (SA) techniques, and (3) display revisions based on complexity measure findings. Fifteen 15 different complexity metrics were originally considered (additive models, multiplicative models, and combination models with five different weighting schemes). The additive model with equal weighting was found to be the most sensitive in differentiating displays and was used in the later studies. For the validation study, system operators were asked to complete a usability questionnaire and a paper-based SA test using the current displays. Correlation and scatter plot analyses was used to determine if the complexity metric and usability and SA scores were related. Results of the validation study indicated that usability and SA scores for the studied displays were not well correlated with the complexity metric. In study 3, the highest and lowest scoring displays were redesigned with an emphasis on maintaining functionality but reducing aspects of complexity that were driving the complexity score. Systems operators again completed the usability and SA testing using the redesigned displays and again correlation analysis was performed. As was the case with study 2, usability scores were not correlated with the complexity metric; however, SA scores were significantly correlated. The complexity metric developed here can be used to quantify the complexity in a display and identify redesign opportunities to reduce non-essential information, as displays that are less complex should result in improved operator performance and satisfaction with the display.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-2263 |
| Date | 14 December 2013 |
| Creators | McElhaney, Steven Hunt |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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