6 research outputs found

    ME-EM 2015-16 Annual Report

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    Table of Contents Alumni: Leading with Simulation Education: Simulating the Future Faculty: Advancing Simulation Graduate Seminar Series Enrollment & Degrees Graduates Department News Faculty & Staff Alumni Donors Contracts & Grants Patents & Publicationshttps://digitalcommons.mtu.edu/mechanical-annualreports/1003/thumbnail.jp

    Cyber-Based Contingency Analysis and Insurance Implications of Power Grid

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    Cybersecurity for power communication infrastructure is a serious subject that has been discussed for a decade since the first North American Electric Reliability Corporation (NERC) critical infrastructure protection (CIP) initiative in 2006. Its credibility on plausibility has been evidenced by attack events in the recent past. Although this is a very high impact, rare probability event, the establishment of quantitative measures would help asset owners in making a series of investment decisions. First, this dissertation tackles attackers\u27 strategies based on the current communication architecture between remote IP-based (unmanned) power substations and energy control centers. Hypothetically, the identification of intrusion paths will lead to the worst-case scenarios that the attackers could do harm to the grid, e.g., how this switching attack may perturb to future cascading outages within a control area when an IP-based substation is compromised. Systematic approaches are proposed in this dissertation on how to systematically determine pivotal substations and how investment can be prioritized to maintain and appropriate a reasonable investment in protecting their existing cyberinfrastructure. More specifically, the second essay of this dissertation focuses on digital protecting relaying, which could have similar detrimental effects on the overall grid\u27s stability. The R-k contingency analyses are proposed to verify with steady-state and dynamic simulations to ensure consistencies of simulation outcome in the proposed modeling in a power system. This is under the assumption that attackers are able to enumerate all electronic devices and computers within a compromised substation network. The essay also assists stakeholders (the defenders) in planning out exhaustively to identify the critical digital relays to be deployed in substations. The systematic methods are the combinatorial evaluation to incorporate the simulated statistics in the proposed metrics that are used based on the physics and simulation studies using existing power system tools. Finally, a risk transfer mechanism of cyber insurance against disruptive switching attacks is studied comprehensively based on the aforementioned two attackers\u27 tactics. The evaluation hypothetically assesses the occurrence of anomalies and how these footprints of attackers can lead to a potential cascading blackout as well as to restore the power back to normal stage. The research proposes a framework of cyber insurance premium calculation based on the ruin probability theory, by modeling potential electronic intrusion and its direct impacts. This preliminary actuarial model can further improve the security of the protective parameters of the critical infrastructure via incentivizing investment in security technologies

    Data Challenges and Data Analytics Solutions for Power Systems

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    ANOMALY INFERENCE BASED ON HETEROGENEOUS DATA SOURCES IN AN ELECTRICAL DISTRIBUTION SYSTEM

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    Harnessing the heterogeneous data sets would improve system observability. While the current metering infrastructure in distribution network has been utilized for the operational purpose to tackle abnormal events, such as weather-related disturbance, the new normal we face today can be at a greater magnitude. Strengthening the inter-dependencies as well as incorporating new crowd-sourced information can enhance operational aspects such as system reconfigurability under extreme conditions. Such resilience is crucial to the recovery of any catastrophic events. In this dissertation, it is focused on the anomaly of potential foul play within an electrical distribution system, both primary and secondary networks as well as its potential to relate to other feeders from other utilities. The distributed generation has been part of the smart grid mission, the addition can be prone to electronic manipulation. This dissertation provides a comprehensive establishment in the emerging platform where the computing resources have been ubiquitous in the electrical distribution network. The topics covered in this thesis is wide-ranging where the anomaly inference includes load modeling and profile enhancement from other sources to infer of topological changes in the primary distribution network. While metering infrastructure has been the technological deployment to enable remote-controlled capability on the dis-connectors, this scholarly contribution represents the critical knowledge of new paradigm to address security-related issues, such as, irregularity (tampering by individuals) as well as potential malware (a large-scale form) that can massively manipulate the existing network control variables, resulting into large impact to the power grid

    Extraction of Energy Information from Analog Meters Using Image Processing

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    There has been an ongoing effort to increase the number of advanced metering infrastructure (AMI) devices to improve system observability. When deployed across distribution secondary networks, AMI provides building-level load and consumption information, which can be used to improve grid management strategies. A barrier to implementation is the significant upgrade costs associated with retrofitting existing meters with network-capable sensing. One economic way is to use image processing methods to extract usage information from images of the existing meters. This paper presents a solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, a systematic approach to extract energy data from images is applied to replace the manual reading process. A case study is presented where the digital imaging approach is compared to the averages determined by visual readings over a one-month period
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