The Theory of Matrices. By F R. Gantmacher. Two volumes, pp. 374 and 276. 1959. (Translated from the Russian by K. A. Hirsch; Chelsea Publishing Company, New York)

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

1 Introduction 2 Electromagnetic Transients 3 Synchronous Machine Modeling 4 Synchronous Machine Control Models 5 Single-Machine Dynamic Models 6 Multimachine Dynamic Models 7 Multimachine Simulation 8 Small-Signal Stability 9 Energy Function Methods Appendix A: Integral Manifolds for Model Bibliography Index

Power System Dynamics and Stability

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.

The development of a trustworthy smart grid requires a deeper understanding of potential impacts resulting from successful cyber attacks. Estimating feasible attack impact requires an evaluation of the grid's dependency on its cyber infrastructure and its ability to tolerate potential failures. A further exploration of the cyber-physical relationships within the smart grid and a specific review of possible attack vectors is necessary to determine the adequacy of cybersecurity efforts. This paper highlights the significance of cyber infrastructure security in conjunction with power application security to prevent, mitigate, and tolerate cyber attacks. A layered approach is introduced to evaluating risk based on the security of both the physical power applications and the supporting cyber infrastructure. A classification is presented to highlight dependencies between the cyber-physical controls required to support the smart grid and the communication and computations that must be protected from cyber attack. The paper then presents current research efforts aimed at enhancing the smart grid's application and infrastructure security. Finally, current challenges are identified to facilitate future research efforts.

Cyber–Physical System Security for the Electric Power Grid

The extended equal area criterion (EEAC) for online transient stability analysis is considered with the following objectives. The first is to state systematically its main hypotheses and key conditions, justify the former, and suggest means to guarantee the latter. The identification and error analysis of critical machines are among the investigated issues. The second is to scan all possible types of instabilities likely to arise in practice and devise means to treat them. The extension of the EEAC to cases beyond the so-called first-swing stability makes it more robust than all direct methods developed up to now. The third objective is to extract essential information out of a large body of simulations and show that the above improvements and extensions enhance the EEAC accuracy and its capability to work properly even under stringent conditions. Possible EEAC applications are also discussed, and uses of the method as such or as an auxiliary technique for more sophisticated approaches are suggested. >

Extended equal area criterion justifications, generalizations, applications

A method for online transient stability assessment of large power systems is proposed. It consists of: replacing the multimachine system by a two-machine dynamic equivalent, further amenable to a one-machine-infinite-bus system; reducing the stability problem to a sole algebraic equation, devised from the equal area criterion, or equivalently from the Lyapunov direct criterion; and using this equation to derive one-shot stability analysis strategies. A technique for system admittance matrix reduction is developed that proves efficient, especially for large systems and multiple-contingency evaluation. The method's main appeal is rapidity: it is about one order of magnitude faster than the most efficient direct criterion. Other attractive features are flexibility and ability to encompass various simulation conditions. Extensions to online sensitivity analysis and control are suggested. >

A simple direct method for fast transient stability assessment of large power systems

The anomalous data identification procedures existing today in power system state estimation become problematic-if not totally unefficient-under stringent conditions, such as multiple and interacting bad data. The identification method presented in this paper attempts to alleviate these difficulties. It consists in :(i) computing measurement error estimates and using them as the random variables of concern;(ii) making decisions on the basis of a hypothesis testing which takes into account their statistical properties. Two identification techniques are then derived and further investigated and assessed by means of a realistic illustrative example. Conceptually novel, the identification methodology is thus shown to lead to practical procedures which are efficient, reliable and workable under all theoretically feasible conditions.

Hypothesis Testing Identification: A New Method For Bad Data Analysis In Power System State Estimation

Direct methods for studying dynamics of large-scale electric power systems-A survey

A hierarchical concept is used to solve the static state estimation problem for large-scale composite power systems. The solution is obtained by performing a two-level calculation. In the lower level, a conventional state estimation is carried out simultaneously for all subsystems. The coordination of these local estimations is realized in the upper level. One of the main contributions of the paper lies in the construction of an appropriate second-level algorithm. Its suitability and also the main features of the overall procedure are then explored and illustrated on the basis of the Belgian 380-220-150 kV transmission network. Comparisons with the standard "integrated" state estimation are also performed.

Mania Ribbens-Pavella

Papers

Extended equal area criterion justifications, generalizations, applications

A simple direct method for fast transient stability assessment of large power systems

Hypothesis Testing Identification: A New Method For Bad Data Analysis In Power System State Estimation

Direct methods for studying dynamics of large-scale electric power systems-A survey

A Two-Level Static State Estimator for Electric Power Systems