PowerWorld Corporation

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PowerWorld Corporation

United States
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Overbye T.J.,University of Illinois at Urbana - Champaign | Mao Z.,University of Illinois at Urbana - Champaign | Shetye K.S.,University of Illinois at Urbana - Champaign | Weber J.D.,PowerWorld Corporation
2017 IEEE Texas Power and Energy Conference, TPEC 2017 | Year: 2017

Power system simulation environments with appropriate time-fidelity are needed to enable rapid testing of new smart grid technologies and for coupled simulations of the underlying cyber infrastructure. This paper presents such an environment which operates with power system models in the PMU time frame, including data visualization and interactive control action capabilities. The flexible and extensible capabilities are demonstrated by interfacing with a cyber infrastructure simulation. © 2017 IEEE.


Nicol T.D.,PowerWorld Corporation | Nicol D.M.,University of Illinois at Urbana - Champaign
Proceedings of the Annual Hawaii International Conference on System Sciences | Year: 2011

Privacy concerns surround the advent of frequently reported meter readings, as analysis of the load demand can reveal electrical customer behavior. Load masking is a means by which consumer might achieve obfuscating the load being metered, by using large-scale electrical storage to either meet some demand locally, or add to the load by charging. This paper considers algorithms for masking load by masking individual load changes, and evaluates their effectiveness in terms of an observer's ability to pin-point the actual change in load, when a new change is load is presented. © 2012 IEEE.


Overbye T.J.,University of Illinois at Urbana - Champaign | Weber J.D.,PowerWorld Corporation
IEEE PES General Meeting, PES 2010 | Year: 2010

This paper describes research in progress for a panel session presentation on how phasor measurement unit (PMU) values can be used to improve power system operations beyond their use in state estimation. ©2010 IEEE.


Overbye T.J.,University of Illinois at Urbana - Champaign | Hutchins T.R.,University of Illinois at Urbana - Champaign | Shetye K.,University of Illinois at Urbana - Champaign | Weber J.,Power World Corporation | Dahman S.,Power World Corporation
2012 North American Power Symposium, NAPS 2012 | Year: 2012

This paper presents a methodology for integrated power flow modeling of the impact of geomagnetic disturbances (GMDs) on power system voltage stability. GMDs cause quasi-dc, geomagnetically induced currents (GICs) in the transformers and transmission lines, which in turn cause saturation of the high voltage transformers, greatly increasing their reactive power consumption. GICs can be calculated using standard power flow modeling parameters such as line resistance, augmented with several GIC specific fields including substation geographic coordinates and grounding resistance, transformer configuration, and transformer coil winding resistances. When exact values are not available, estimated quantities can be used. By then integrating GIC into power flow analysis, the changes in reactive power losses and bus voltages can be quantified to assess the risk of voltage instability and large-scale voltage collapse. An example calculation is provided for a North American Eastern Interconnect model. © 2012 IEEE.


Overbye T.J.,University of Illinois at Urbana - Champaign | Shetye K.S.,University of Illinois at Urbana - Champaign | Hutchins T.R.,University of Illinois at Urbana - Champaign | Qiu Q.,American Electric Power | Weber J.D.,PowerWorld Corporation
IEEE Transactions on Power Systems | Year: 2013

Geomagnetically induced currents (GICs) have the potential to severely disrupt power grid operations, and hence their impact needs to be assessed through planning studies. This paper presents a methodology for determining the sensitivity of the GICs calculated for individual and/or groups of transformers to the assumed quasi-dc electric fields on the transmission lines that induce the GICs. Example calculations are provided for two small systems and for the North American Eastern Interconnect model. Results indicate that transformer GICs are mostly due to the electric fields on nearby transmission lines, implying localized electric field models may be appropriate for such studies. © 2013 IEEE.


Davis C.M.,PowerWorld Corporation | Overbye T.J.,University of Illinois at Urbana - Champaign
IEEE Transactions on Power Systems | Year: 2011

This paper presents a method for determining the double outage contingencies that threaten the system without solving the full contingency set. Two methods for contingency screening with complementary properties are presented. The results of the algorithms are compared to the full double outage contingency analysis results for a large North American case. The results show that the screening algorithms are able to detect nearly all of the contingencies that will result in violations, while requiring only a small fraction of the contingencies to be solved. © 2011 IEEE.


Zonouz S.,University of Miami | Rogers K.M.,PowerWorld Corporation | Berthier R.,University of Illinois at Urbana - Champaign | Bobba R.B.,University of Illinois at Urbana - Champaign | And 2 more authors.
IEEE Transactions on Smart Grid | Year: 2012

Preserving the availability and integrity of the power grid critical infrastructures in the face of fast-spreading intrusions requires advances in detection techniques specialized for such large-scale cyber-physical systems. In this paper, we present a security-oriented cyber-physical state estimation (SCPSE) system, which, at each time instant, identifies the compromised set of hosts in the cyber network and the maliciously modified set of measurements obtained from power system sensors. SCPSE fuses uncertain information from different types of distributed sensors, such as power system meters and cyber-side intrusion detectors, to detect the malicious activities within the cyber-physical system. We implemented a working prototype of SCPSE and evaluated it using the IEEE 24-bus benchmark system. The experimental results show that SCPSE significantly improves on the scalability of traditional intrusion detection techniques by using information from both cyber and power sensors. Furthermore, SCPSE was able to detect all the attacks against the control network in our experiments. © 2010-2012 IEEE.


Global Power System State Estimator Market By Software (Utility State Estimator Software And Power Control Centers) And Solution (Weighted Lease Square (WLS) Method, Least Absolute Value (LAV) Method And Others) For Transmission Network And Distribution Network Application: Global Industry Perspective, Comprehensive Analysis, Size, Share, Growth, Segment, Trends and Forecast, 2014 – 2020 The report covers forecast and analysis for the power system state estimator market on a global and regional level. The study provides historic data of 2014 along with a forecast from 2015 to 2020 based revenue (USD Million). The study includes drivers and restraints for the power system state estimator along with the impact they have on the demand over the forecast period. Additionally, the report includes study of opportunities available in the power system state estimator on a global level. In order to give the users of this report a comprehensive view on the power system state estimator market, we have included a detailed competitive scenario, and product portfolio of key vendors. To understand the competitive landscape in the market, an analysis of Porter’s five forces model for the power system state estimator has also been included. The study encompasses a market attractiveness analysis, wherein application segments are benchmarked based on their market size, growth rate and general attractiveness. The study provides a decisive view on the power system state estimator by segmenting the market based on software, solution, and applications. Software segment include utility state estimator software and power control centers. On the basis on solutions, power system state estimator has been classified into weighted lease square (WLS) method, least absolute value (LAV) method and other. All the application segments have been analyzed based on present and future trends and the market is estimated from 2014 to 2020. Key application markets covered under this study includes transmission network and distribution network. The regional segmentation includes the current and forecast demand for North America, Europe, Asia Pacific, Latin America and Middle East and Africa. The report covers detailed competitive outlook including company profiles of the key participants operating in the global market. Key players profiled in the report include ABB Ltd, Alstom SA, CYME International, DIgSILENT GmbH, Electrocon International, Inc., EPFL (Simsen), ETAP Electrical Engineering Software, GDF SUEZ Energy (ENGIE), GE Power, Inspired Interfaces (Retic Master), Kepco Inc, Neplan AG, Nexant, Open Systems International, Inc., PowerWorld Corporation, PRDC (Mipower), Siemens AG, Siemens PTI, and SKM Systems Analysis, Inc. This report segments the global power system state estimator market as follows:


Zonouz S.,University of Miami | Davis C.M.,PowerWorld Corporation | Davis K.R.,PowerWorld Corporation | Berthier R.,Urbana University | And 2 more authors.
IEEE Transactions on Smart Grid | Year: 2014

Contingency analysis is a critical activity in the context of the power infrastructure because it provides a guide for resiliency and enables the grid to continue operating even in the case of failure. In this paper, we augment this concept by introducing SOCCA, a cyber-physical security evaluation technique to plan not only for accidental contingencies but also for malicious compromises. SOCCA presents a new unified formalism to model the cyber-physical system including interconnections among cyber and physical components. The cyber-physical contingency ranking technique employed by SOCCA assesses the potential impacts of events. Contingencies are ranked according to their impact as well as attack complexity. The results are valuable in both cyber and physical domains. From a physical perspective, SOCCA scores power system contingencies based on cyber network configuration, whereas from a cyber perspective, control network vulnerabilities are ranked according to the underlying power system topology. © 2010-2012 IEEE.


Mohapatra S.,PowerWorld Corporation | Overbye T.J.,Urbana University
19th Power Systems Computation Conference, PSCC 2016 | Year: 2016

Dynamic Mode Decomposition (DMD) is a relatively new method for simultaneous modal analysis of multiple time-series signals. In this paper, DMD is successfully applied towards transmission-level power system data in an implementation that is able to run quickly. Since power systems are considered as non-linear and time-varying, modal identification is capable of monitoring the evolution of large-scale power system dynamics by providing a breakdown of the constituent oscillation frequencies and damping ratios, and their respective amplitudes. DMD is an efficient algorithm for both off-line and on-line processing of large volumes of time-series measurements, which can enable spatio-temporal analyses, improve situational awareness, and could even contribute towards control strategies. This paper applies DMD on a set of simulated measurements consisting of both frequency and voltage magnitude data. The key advantage of this implementation is its relatively fast computation; for example, it is able to process a 7 s time-window, consisting of 3392 signals with 211 time points, in 0.185 s. Automated processing of transient contingency results, and on-line mode tracking are two proposed applications. © 2016 Power Systems Computation Conference.

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