Design and Deployment of Specialized Visualizations for Weather-Sensitive Electric Distribution Operations



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Fourth Symposium on Policy and Socio-Economic Research 4.1 Design and Deployment of Specialized Visualizations for Weather-Sensitive Electric Distribution Operations Lloyd A. Treinish IBM, Yorktown Heights, NY lloydt@us.ibm.com http://www.research.ibm.com/weather/dt.html

Fourth Symposium on Policy and Socio-Economic Research 4.1 Design and Deployment of Specialized Visualizations for Weather-Sensitive Electric Distribution Operations Background and motivation Visualization issues Approach Example results Discussion and future work

Other Presentations of Related Work 1.6 Development and Deployment of a Mesoscale Weather and Outage Prediction Service for Electric Utility Operations (Symposium on Urban High Impact Weather) P1.7 A Spatial Model for the Prediction of Electrical Power Outages Caused by Severe Storms (Symposium on Urban High Impact Weather) 12B.2 Estimating high-resolution near-surface forecast uncertainty to support optimization of resources (13th Conference on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface) JP5.4 Application of an operational meso-scale modelling system for commercial/industrial plant operations (Eighth Symposium on the Urban Environment Symposium) P1.3 Urban Flood Forecasting using an Integrated Hydrometeorological System (Symposium on Urban High Impact Weather)

Background and Motivation The operation of the distribution system of an electric utility, particularly with an overhead infrastructure, can be highly sensitive to local weather conditions For predictions of such conditions to be useful for decision makers, the information must be disseminated in a timely fashion that enables effective decisions to be made with confidence Visualization is a critical but it requires appropriate designs to permit interpretation as part of operational planning prior to a severe storm event

Storm Impact and Response Prediction Weather causes damage and outages Outages require restoration (resources) Restoration takes time, people, etc. Build stochastic model from weather observations, storm damage and related data, and couple it to either NWP or observations Weather prediction Damage prediction Outage location, timing and response Wind, rain, lightning and duration Demographics of effected area Ancillary environmental conditions How can the results of such a model be disseminated as forecast of impact to plan effective responses? Resource requirement prediction Restoration time prediction

One Person's Emergency May Be Another's Routine "Emergency Response Schema" * Visualization Models User Visualization Assess * (based upon experience, e.g., scenario training) Observation Weather Visualization Attention: (Filter on Relevance) Use or Ignore Action Request Monitor and Evaluate Decision Making Process / Workflow Many tasks are involved in how one examines and assesses a situation, obtains and interprets information, and communicates with others.

Visualization Issues Traditional meteorological visualization is driven by data for analysis -- inappropriate for decision support applications Traditional business visualization is driven by methods for tabular data inappropriate for meteorological data Timely and effective usability requires the visualization designer to Understand how experienced people use their expertise in decision making, and how they work and interact Avoid an impedance mismatch between the data vs. how the data should be utilized Identification of user goals, which are mapped to visualization tasks and to data Design in terms relevant for user, employing familiar terminology and metaphors -- readily understood in real-time without expert interpretation and used with confidence Understanding how users perceive and interpret visualizations

Disciplines Needed for Effective Visual Design (Understand Limitations in Content and Interpretation) Meteorology Preserve data fidelity (and science) Psychophysics and human vision Perceptual rules for use of color, geometry, texture, etc. Cartography Rules for use of projections (i.e., making appropriate maps) Computer graphics Algorithms for transformation, realization, rendering, etc. Workflow and decision-making process Human factors, systems engineering, etc.

Dissemination Requirements Tailored weather visualizations available via a web browser, which are automatically updated for each forecast cycle Storm classification and outage estimation Uncertainty visualization for operational decision making Project began with capabilities already in place for various 3d and 2d visualizations

Project began with capabilities already in place for various 3d and 2d visualizations

Common Themes Ease of use by diverse users who are experts in utility operations, emergency management and weather impact are not meteorologists, mathematicians or computer scientists Enable proactive decision making affected by weather Rapid assessment important (visualizations may need to be almost preattentive) Thresholds often more important than overall content Addressing uncertainty in results when available Customized appearance and fused with ancillary data Appropriate utilization of visualization elements (e.g., geometry, color) Consistency with data Incorporation of information concerning the distribution network Cartographic reprojection to minimize spatial distortion Presentation of derived properties critical to decisions Weather or secondary physical phenomena may not be shown

Visualization Tasks for Tailored Content Direct results from the weather model Derived results from the weather model (indirect) Direct results from the damage model (derived) Examples of each and how the designs evolved

Forecasted Surface Winds Equal Area Projection Original: Magnitude only Colormap with perceptual ordering Full precision visible, but varies with each forecast Final: Emphasis on magnitude with directional overlay Fixed (familiar colormap), following DHS scale but less saturated Less precision visible but semantic association with color with user-defined thresholds

Forecasted Surface Winds Equal Area Projection Original: Magnitude only Colormap with perceptual ordering Full precision visible, but varies with each forecast Final: Emphasis on magnitude with directional overlay Fixed (familiar colormap), following DHS scale but less saturated Less precision visible but semantic association with color with user-defined thresholds

Deep Thunder Storm Classification -- 15 April 2007 Storm Category/Plan and Number of Customers Out of Service 1. Upgraded (e.g., thunderstorms), < 7000 2A. Serious (e.g., heavy thunderstorms), 7000-9000 2B. Serious, 9000-12000 2C. Serious, 12000-15000 3A. Full Scale (e.g., severe storm), 15000-40000 3B. Full Scale (e.g., hurricane), > 40000

Deep Thunder Storm Classification -- 15 April 2007 Equal Area Projection Original: Colormap with Perceptual Ordering Overhead transmission lines Overlay Final: Fixed (familiar colormap), following DHS scale but less saturated and an additional level Area substation Overlay

Deep Thunder Damage Prediction 02 September 2006 Forecasted Outages Probability of More than 100 Outages

Deep Thunder Damage Prediction 02 September 2006 Forecasted Outages Combined with Probability of More than 100 Outages

Deep Thunder Damage Prediction 02 September 2006 Forecasted Outages Combined with Probability of More than 100 Outages Opacity of Colored Area Illustrates Probability

Deep Thunder Damage Prediction 02 September 2006 Forecasted Outages Somewhat modified

Uncertainty in Damage Prediction -- 02 September 2006 Forecasted Outages Combined with Probability of More than 100 Outages Texturing of Outage Color Illustrates Probability with Value

Web Interface for Consolidated Edison Surface Wind Animation Interactive Site-Specific Forecast Table

Web Interface for Consolidated Edison Site-Specific Forecast Plots Surface Temperature Animation

Discussion and Future Work Less is more Familiar metaphors (colors, overlays) required for ease of use and in minimizing training Iteration with users critical to incorporate feedback into designs Continued work on representation of uncertainty Develop additional tailored weather visualizations (e.g., frozen precipitation, wind gusts) Apply to similar operational needs for water utilities, municipal emergency management and transportation agencies