An Introduction to MultiAgent Systems.

(1990). ENERGY FUNCTION ANALYSIS FOR POWER SYSTEM STABILITY. Electric Machines & Power Systems: Vol. 18, No. 2, pp. 209-210.

Energy function analysis for power system stability

Control Systems Engineering

Distribution automation (DA) is deployed to reduce outages and to rapidly reconnect customers following network faults. Recent developments in DA equipment have enabled the logging of load and fault event data, referred to as “pick-up activity.” This pick-up activity provides a picture of the underlying circuit activity occurring between successive DA operations over a period of time and has the potential to be accessed remotely for off-line or on-line analysis. The application of data analytics and automated analysis of this data supports reactive fault management and post fault investigation into anomalous network behavior. It also supports predictive capabilities that identify when potential network faults are evolving and offers the opportunity to take action in advance in order to mitigate any outages. This paper details the design of a novel decision support system to achieve fault diagnosis and prognosis for DA schemes. It combines detailed data from a specific DA device with rule-based, data mining, and clustering techniques to deliver the diagnostic and prognostic functions. These are applied to 11-kV distribution network data captured from Pole Mounted Auto-Reclosers as provided by a leading U.K. network operator. This novel automated analysis system diagnoses the nature of a circuit’s previous fault activity, identifies underlying anomalous circuit activity, and highlights indications of problematic events gradually evolving into a full scale circuit fault. The novel contributions include the tackling of “semi-permanent faults” and the re-usable methodology and approach for applying data analytics to any DA device data sets in order to provide diagnostic decisions and mitigate potential fault scenarios.

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A Data Analytic Approach to Automatic Fault Diagnosis and Prognosis for Distribution Automation

Physical and cyber security in a smart grid environment

Power grid facilities can be vulnerable with respect to malicious physical attacks. Preventive and/or remedial actions are essential to maintain the system integrity. This paper is focused on the physical security of power substations. The proposed methodology consists of an intrusion classification method, dynamic and static threat assessment methods, and decision support for the system operator's response in a contingency scenario. An important feature of the proposed method is to build the linkage between substation physical security monitoring and power system analysis. In addition, industry experience from two Transmission System Operators (TSOs) is incorporated in the development of the methodology.

Threat assessment and response for physical security of power substations

Power substations are vulnerable with respect to malicious physical attacks. Various types of sensors and technologies are developed for enhancing the physical security of critical infrastructures. In this paper, the proposed intelligent substation physical security monitoring (ISPSM) system uses a multi-agent system (MAS) with the distributed Kalman filtering (DKF) algorithm. The system architecture and computational methods are presented. In addition, industry experience is considered. Data collected from a drill and computer simulations is used for validation of the proposed ISPSM system.

Intelligent physical security monitoring system for power substations

Summary

Power grid facilities can be vulnerable with respect to malicious physical attacks. An advanced system to monitor physical security of substations and other facilities is essential to maintain system integrity. This paper describes a substation physical security monitoring (SPSM) system for remote monitoring of power substations. The proposed methodology consists of video surveillance for outdoors, motion detectors for indoors, and the classification of intrusion events. An important feature of the proposed method is the ability to determine the response to a threat based on the result of physical security monitoring. In addition, industry experience from two transmission system operators (TSOs) is incorporated in the development of the methodology. To validate the proposed SPSM system, an experiment was performed at a critical substation involving two physical intrusion scenarios. Copyright © 2015 John Wiley & Sons, Ltd.

Radek Hamza

Papers

Threat assessment and response for physical security of power substations

Intelligent physical security monitoring system for power substations

On‐line physical security monitoring of power substations