The Smart Grid, regarded as the next generation power grid, uses two-way flows of electricity and information to create a widely distributed automated energy delivery network. In this article, we survey the literature till 2011 on the enabling technologies for the Smart Grid. We explore three major systems, namely the smart infrastructure system, the smart management system, and the smart protection system. We also propose possible future directions in each system. colorred{Specifically, for the smart infrastructure system, we explore the smart energy subsystem, the smart information subsystem, and the smart communication subsystem.} For the smart management system, we explore various management objectives, such as improving energy efficiency, profiling demand, maximizing utility, reducing cost, and controlling emission. We also explore various management methods to achieve these objectives. For the smart protection system, we explore various failure protection mechanisms which improve the reliability of the Smart Grid, and explore the security and privacy issues in the Smart Grid.

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Smart Grid — The New and Improved Power Grid: A Survey

Smart Grid - The New and Improved Power Grid:

A power grid is a complex system connecting electric power generators to consumers through power transmission and distribution networks across a large geographical area. System monitoring is necessary to ensure the reliable operation of power grids, and state estimation is used in system monitoring to best estimate the power grid state through analysis of meter measurements and power system models. Various techniques have been developed to detect and identify bad measurements, including interacting bad measurements introduced by arbitrary, nonrandom causes. At first glance, it seems that these techniques can also defeat malicious measurements injected by attackers.In this article, we expose an unknown vulnerability of existing bad measurement detection algorithms by presenting and analyzing a new class of attacks, called false data injection attacks, against state estimation in electric power grids. Under the assumption that the attacker can access the current power system configuration information and manipulate the measurements of meters at physically protected locations such as substations, such attacks can introduce arbitrary errors into certain state variables without being detected by existing algorithms. Moreover, we look at two scenarios, where the attacker is either constrained to specific meters or limited in the resources required to compromise meters. We show that the attacker can systematically and efficiently construct attack vectors in both scenarios to change the results of state estimation in arbitrary ways. We also extend these attacks to generalized false data injection attacks, which can further increase the impact by exploiting measurement errors typically tolerated in state estimation. We demonstrate the success of these attacks through simulation using IEEE test systems, and also discuss the practicality of these attacks and the real-world constraints that limit their effectiveness.

False data injection attacks against state estimation in electric power grids

A power grid is a complex system connecting electric power generators to consumers through power transmission and distribution networks across a large geographical area. System monitoring is necessary to ensure the reliable operation of power grids, and state estimation is used in system monitoring to best estimate the power grid state through analysis of meter measurements and power system models. Various techniques have been developed to detect and identify bad measurements, including the interacting bad measurements introduced by arbitrary, non-random causes. At first glance, it seems that these techniques can also defeat malicious measurements injected by attackers.In this paper, we present a new class of attacks, called false data injection attacks, against state estimation in electric power grids. We show that an attacker can exploit the configuration of a power system to launch such attacks to successfully introduce arbitrary errors into certain state variables while bypassing existing techniques for bad measurement detection. Moreover, we look at two realistic attack scenarios, in which the attacker is either constrained to some specific meters (due to the physical protection of the meters), or limited in the resources required to compromise meters. We show that the attacker can systematically and efficiently construct attack vectors in both scenarios, which can not only change the results of state estimation, but also modify the results in arbitrary ways. We demonstrate the success of these attacks through simulation using IEEE test systems. Our results indicate that security protection of the electric power grid must be revisited when there are potentially malicious attacks.

Cyber-physical systems are ubiquitous in power systems, transportation networks, industrial control processes, and critical infrastructures. These systems need to operate reliably in the face of unforeseen failures and external malicious attacks. In this paper: (i) we propose a mathematical framework for cyber-physical systems, attacks, and monitors; (ii) we characterize fundamental monitoring limitations from system-theoretic and graph-theoretic perspectives; and (ii) we design centralized and distributed attack detection and identification monitors. Finally, we validate our findings through compelling examples.

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Attack Detection and Identification in Cyber-Physical Systems

State estimators in power systems are currently used to, for example, detect faulty equipment and to route power flows. It is believed that state estimators will also play an increasingly important role in future smart power grids, as a tool to optimally and more dynamically route power flows. Therefore security of the estimator becomes an important issue. The estimators are currently located in control centers, and large numbers of measurements are sent over unencrypted communication channels to the centers. We here study stealthy false-data attacks against these estimators. We define a security measure tailored to quantify how hard attacks are to perform, and describe an efficient algorithm to compute it. Since there are so many measurement devices in these systems, it is not reasonable to assume that all devices can be made encrypted overnight in the future. Therefore we propose two algorithms to place encrypted devices in the system such as to maximize their utility in terms of increased system security. We illustrate the effectiveness of our algorithms on two IEEE benchmark power networks under two attack and protection cost models.

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Stealth Attacks and Protection Schemes for State Estimators in Power Systems

Automated and smart meters are devices that are able to monitor the energy consumption of electricity consumers in near real-time. They are considered key technological enablers of the smart grid, as the real-time consumption data that they can collect could enable new sophisticated billing schemes, could facilitate more efficient power distribution system operation and could give rise to a variety of value-added services. At the same time, the energy consumption data that the meters collect are sensitive consumer information; thus, privacy is a key concern and is a major inhibitor of real-time data collection in practice. In this paper, we review the different uses of metering data in the smart grid and the related privacy legislation. We then provide a structured overview, shortcomings, recommendations, and research directions of security solutions that are needed for privacy-preserving meter data delivery and management. We finally survey recent work on privacy-preserving technologies for meter data collection for the three application areas: 1) billing; 2) operations; and 3) value-added services including demand response.

Smart Meter Data Privacy: A Survey

Critical power system applications like contingency analysis and optimal power flow calculation rely on the power system state estimator. Hence the security of the state estimator is essential for the proper operation of the power system. In the future more applications are expected to rely on it, so that its importance will increase. Based on realistic models of the communication infrastructure used to deliver measurement data from the substations to the state estimator, in this paper we investigate the vulnerability of the power system state estimator to attacks performed against the communication infrastructure. We define security metrics that quantify the importance of individual substations and the cost of attacking individual measurements. We propose approximations of these metrics, that are based on the communication network topology only, and we compare them to the exact metrics. We provide efficient algorithms to calculate the security metrics. We use the metrics to show how various network layer and application layer mitigation strategies, like single and multi-path routing and data authentication, can be used to decrease the vulnerability of the state estimator. We illustrate the efficiency of the algorithms on the IEEE 118 and 300 bus benchmark power systems.

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Network-Aware Mitigation of Data Integrity Attacks on Power System State Estimation

https://people.kth.se/~gyuri/Pub/TeiDSJ-IFAC11.pdf

A Cyber Security Study of a SCADA Energy Management System: Stealthy Deception Attacks on the State Estimator

The electrical power network is a critical infrastructure in today's society, so its safe and reliable operation is of major concern. State estimators are commonly used in power networks, for example, to detect faulty equipment and to optimally route power flows. The estimators are often located in control centers, to which large numbers of measurements are sent over unencrypted communication channels. Therefore cyber security for state estimators becomes an important issue. In this paper we analyze the cyber security of state estimators in supervisory control and data acquisition (SCADA) for energy management systems (EMS) operating the power network. Current EMS state estimation algorithms have bad data detection (BDD) schemes to detect outliers in the measurement data. Such schemes are based on high measurement redundancy. Although these methods may detect a set of basic cyber attacks, they may fail in the presence of an intelligent attacker. We explore the latter by considering scenarios where stealthy deception attacks are performed by sending false information to the control center. We begin by presenting a recent framework that characterizes the attack as an optimization problem with the objective specified through a security metric and constraints corresponding to the attack cost. The framework is used to conduct realistic experiments on a state-of-the-art SCADA EMS software for a power network example with 14 substations, 27 buses, and 40 branches. The results indicate how state estimators for power networks can be made more resilient to cyber security attacks.

Gyorgy Dan

Papers

Stealth Attacks and Protection Schemes for State Estimators in Power Systems

Smart Meter Data Privacy: A Survey

Network-Aware Mitigation of Data Integrity Attacks on Power System State Estimation

A Cyber Security Study of a SCADA Energy Management System: Stealthy Deception Attacks on the State Estimator

A Cyber Security Study of a SCADA Energy Management System: Stealthy Deception Attacks on the State Estimator