Mohamad El Hariri

IEC 61850: Technology standards and cyber-threats

Substations constitute a fundamental part in providing reliable electricity to consumers. For a substation to maintain electricity reliability and its own real-time operability, communication between its components is inevitable. Before the emergence of IEC 61850, inter-substation communication was established via expensive copper wires with limited capabilities. IEC 61850 is the standard set by the International Electro-technical Commission (IEC) Technical Committee Number 57 Working Group 10 and IEEE for Ethernet (IEEE 802.3)-based communication in electrical substations. Like many power grid systems standards, IEC 61850 was set without extensive consideration for critical security measures. This paper discusses IEC 61850 technology standards and applications thoroughly and points out major security vulnerabilities it introduces in the context of current cyber-physical smart grid systems.

Online false data detection and lost packet forecasting system using time series neural networks for IEC 61850 sampled measured values

Migrating to a smart grid requires a paradigm shift in the implementation of power system applications. With the advent of IEC 61850, contemporary Substation Automation Systems (SAS) are utilizing electronic instrument transformers and merging units to transmit current and voltage measurements over Ethernet as Sampled Measured Values (SMV). However, if a substations network resources are not properly managed, the high transmission rate of SMV would make them prone to packet loss. Also, the strict 4ms time constraint imposed on SMVs makes encrypting these messages nearly impossible. As such, this paper presents an online device level fake data detection system for detecting fake SMV messages without violating the 4ms time constraint set forth by IEC 61850. In order to ensure a reliable SAS operation, this paper also presents a coupled neural network — time series method for forecasting lost SMV packets. The proposed algorithm was implemented in a system composed of merging units and intelligent electronic devices developed for this purpose. Real-time experimental results of the proposed algorithms over a real IEC 61850 network showed excellent results in terms of detecting fake messages and increasing the robustness of protection schemes by accurately forecasting dropped SMV packets.

A DDS-Based Energy Management Framework for Small Microgrid Operation and Control

The smart grid is seen as a power system with real-time communication and control capabilities between the consumer and the utility. This modern platform facilitates the optimization in energy usage based on several factors including environmental, price preferences, and system technical issues. In this paper, a real-time energy management system (EMS) for microgrids or nanogrids was developed. The developed system involves an online optimization scheme to adapt its parameters based on previous, current, and forecasted future system states. The communication requirements for all EMS modules were analyzed and are all integrated over a data distribution service Ethernet network with appropriate quality-of-service profiles. The developed EMS was emulated with actual residential energy consumption and irradiance data from Miami, Florida, and proved its effectiveness in reducing consumers’ bills and achieving flat peak load profiles.

An Iterative Design Approach for Shielding of WPT Systems in Electric Vehicle Charging Applications

Several factors are considered when designing a Wireless Power Transfer (WPT) system for Electric Vehicle (EV) charging. These include the efficiency of the system, amount of power transferred, near field emissions, cost, and weight. Reaching the best combination of design parameters often requires trade-offs between them. Accordingly, and starting from a given coil design, this paper proposes an iterative shield design approach for selecting an adequate aluminum shield radius and thickness, using Finite Elements (FE) Analysis, which ensures a safe level of EMC near field exposure, minimal cost, and minimal weight. Design considerations were done considering the 85 KHz frequency level set by SAE-J2954 TF.

Physical-Model-Checking to Detect Switching-Related Attacks in Power Systems

Recent public disclosures on attacks targeting the power industry showed that savvy attackers are now capable of occulting themselves from conventional rule-based network intrusion detection systems (IDS), bringing about serious threats. In order to leverage the work of rule-based IDS, this paper presents an artificially intelligent physical-model-checking intrusion detection framework capable of detecting tampered-with control commands from control centers of power grids. Unlike the work presented in the literature, the work in this paper utilizes artificial intelligence (AI) to learn the load flow characteristics of the power system and benefits from the fast responses of the AI to decode and understand contents of network packets. The output of the AI is processed through an expert system to verify that incoming control commands do not violate the physical system operational constraints and do not put the power system in an insecure state. The proposed content-aware IDS is tested in simulation on a 14-bus IEEE benchmark system. Experimental verification on a small power system, with an IEC 61850 network architecture is also carried out. The results showed the accuracy of the proposed framework in successfully detecting malicious and/or erroneous control commands.