New methods for the visualization of electric power system information

Overbye, Thomas J.; Weber, Judy

doi:10.1109/infvis.2000.885101

Cited by 47 publications

(23 citation statements)

References 14 publications

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“…The advanced graphics presentation depicts collected or processed information using color or icons on top of a geographic layout such as a geographic map. The graphics may show voltage contours, overloads, 3-D single line diagram with data bars, stack column chart, pie charts, weighted graphs with physical characteristics of underlying data [8], [9]. Similar graphical presentation can be applied for postcontingency visualization of the power flow solution, especially for high risk contingency.…”

Section: Visualization Of Resultsmentioning

confidence: 99%

Contingency analysis enhancements

Radjabli¹

2015

ijsgce

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Contingency Analysis can provide a powerful insight into potential operational emergencies if the real-time analysis is extended into near future. Predictive look-ahead analysis can take advantage of forecasted loads and generation, scheduled outages, and transmission dynamic ratings based on a weather forecast. This paper proposes to use simple estimate of outage probability in the predictive contingency analysis. In real time, the probability of outage is estimated using line loading and extreme weather conditions factor. For evaluation of each contingency, risk index presented as a product of severity and the contingency's normalized probability. Monitoring of projected near-term risks provides enhanced assessment of the contingency trends developing in the network. The look-ahead analysis becomes even more vital in case of quickly changing adverse weather conditions. It is proposed to perform "(N-X)" contingency analysis on high intensity storm area and tracking risk index for all contingencies.

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Section: Visualization Of Resultsmentioning

confidence: 99%

Contingency analysis enhancements

Radjabli¹

2015

ijsgce

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“…As part of the PSERC project, techniques are developed to visualize complex power systems and flows [15]. For the interactive analysis of network related data sources such as server logs or BGP protocol data, Fischer et al developed a visual analytics expert system in [6].…”

Section: Related Workmentioning

confidence: 99%

An Integrated In-Situ Approach to Impacts from Natural Disasters on Critical Infrastructures

Mittelstädt

Wang

Eaglin

et al. 2015

2015 48th Hawaii International Conference on System Sciences

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Abstract-Natural disasters can have a devastating effect on critical infrastructures, especially in case of cascading effects among multiple infrastructures such as the electric power grid, the communication network, and the road network. While there exist detailed models for individual types of infrastructures such as electric power grids, these do not encompass the various interconnections and interdependencies to other networks. Cascading effects are hard to discover and often the root cause of problems remain unclear. In order to enable real-time situational awareness for operational risk management one needs to be aware of the broader context of events. In this paper, we present a unique visual analytics control room system that integrates the separate visualizations of the different network infrastructures with social media analysis and mobile in-situ analysis to help to monitor the critical infrastructures, detecting cascading effects, performing root cause analyses, and managing the crisis response. Both the social media analysis and the mobile in-situ analysis are important components for an effective understanding of the crisis and an efficient crisis response. Our system provides a mechanism for conjoining the available information of different infrastructures and social media as well as mobile in-situ analysis in order to provide unified views and analytical tools for monitoring, planning, and decision support. A realistic use case scenario based on real critical infrastructures as well as our qualitative study with crisis managers shows the potential of our approach.

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“…Recently, the diagrams have been animated [8], allowing insight into power flow. Flow has also been visualized using dynamically sized pie charts that grow superlinearly as a line approaches overload.…”

Section: Visualizationmentioning

confidence: 99%

“…Contouring is a classic visualization technique for continuous data, which can be applied to discrete data by interpolation. Techniques have been developed for contouring bus data (voltage, frequency, phase, local marginal prices), and of line data (load, power transfer distribution factors) [8,10,11]. Phase-angle data as measured directly via GPS-based sensors or semi-measured/calculated from existing sensors/state estimators may be used as an indicator of transient stability margin or via "energy" functions.…”

Section: Visualizationmentioning

confidence: 99%

DDDAS for Autonomic Interconnected Systems: The National Energy Infrastructure

Hoffmann

Swain

et al. 2007

Computational Science – ICCS 2007

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Abstract.The most critical element of the nation's energy infrastructure is our electricity generation, transmission, and distribution system known as the "power grid." Computer simulation is an effective tool that can be used to identify vulnerabilities and predict the system response for various contingencies. However, because the power grid is a very large-scale nonlinear system, such studies are presently conducted "open loop" using predicted loading conditions months in advance and, due to uncertainties in model parameters, the results do not provide grid operators with accurate "real time" information that can be used to avoid major blackouts such as were experienced on the East Coast in August of 2003. However, the paradigm of Dynamic Data-Driven Applications Systems (DDDAS) provides a fundamentally new framework to rethink the problem of power grid simulation. In DDDAS, simulations and field data become a symbiotic feedback control system and this is refreshingly different from conventional power grid simulation approaches in which data inputs are generally fixed when the simulation is launched. The objective of the research described herein was to utilize the paradigm of DDDAS to develop a marriage between sensing, visualization, and modelling for large-scale simulation with an immediate impact on the power grid. Our research has focused on methodological innovations and advances in sensor systems, mathematical algorithms, and power grid simulation, security, and visualization approaches necessary to achieve a meaningful large-scale real-time simulation that can have a significant impact on reducing the likelihood of major blackouts.

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New methods for the visualization of electric power system information

Abstract: Abstract

Cited by 47 publications

References 14 publications

Contingency analysis enhancements

Contingency analysis enhancements

An Integrated In-Situ Approach to Impacts from Natural Disasters on Critical Infrastructures

DDDAS for Autonomic Interconnected Systems: The National Energy Infrastructure

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