Publications

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Design and operation of the electric power grid (EPG) relies heavily on computational models. High-fidelity, full-order models are used to study transient phenomena on only a small part of the network. Reduced-order dynamic and power flow models are used when analysis involving thousands of nodes are required due to the computational demands when simulating large numbers of nodes. The level of complexity of the future EPG will dramatically increase due to large-scale deployment of variable renewable generation, active load and distributed generation resources, adaptive protection and control systems, and price-responsive demand. High-fidelity modeling of this future grid will require significant advances in coupled, multi-scale tools and their use on high performance computing (HPC) platforms. This LDRD report demonstrates SNL's capability to apply HPC resources to these 3 tasks: (1) High-fidelity, large-scale modeling of power system dynamics; (2) Statistical assessment of grid security via Monte-Carlo simulations of cyber attacks; and (3) Development of models to predict variability of solar resources at locations where little or no ground-based measurements are available.

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The development continues for Finite State Abstraction (FSA) methods to enable Impacts Analysis (IA) for cyber attack against power grid control systems. Building upon previous work, we successfully demonstrated the addition of Bounded Model Checking (BMC) to the FSA method, which constrains grid conditions to reasonable behavior. The new FSA feature was successfully implemented and tested. FSA is an important part of IA for the power grid, complementing steady-state approaches. It enables the simultaneous evaluation of myriad dynamic trajectories for the system, which in turn facilitates IA for whole ranges of system conditions simultaneously. Given the potentially wide range and subtle nature of potential control system attacks, this is a promising research approach. In this report, we will explain the addition of BMC to the previous FSA work and some testing/simulation upon the implemented code using a two-bus test system. The current FSA approach and code allow the calculation of the acceptability of power grid conditions post-cyber attack (over a given time horizon and for a specific grid topology). Future work will enable analysis spanning various topologies (to account for switching events), as well as an understanding of the cyber attack stimuli that can lead to undesirable grid conditions.

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To analyze the risks due to cyber attack against control systems used in the United States electrical infrastructure, new algorithms are needed to determine the possible impacts. This research is studying the Reliability Impact of Cyber ttack (RICA) in a two-pronged approach. First, malevolent cyber actions are analyzed in terms of reduced grid reliability. Second, power system impacts are investigated using an abstraction of the grid's dynamic model. This second year of esearch extends the work done during the first year.

Process Control System (PCS) security is critical to our national security. Yet, there are a number of technological, economic, and educational impediments to PCS owners implementing effective security on their systems. OPSAID (Open PCS Security Architecture for Interoperable Design), a project sponsored by the US Department of Energy's Office of Electricity Delivery and Reliability, aims to address this issue through developing and testing an open source architecture for PCS security. Sandia National Laboratories, along with a team of PCS vendors and owners, have developed and tested this PCS security architecture. This report describes their progress to date.2 AcknowledgementsThe authors acknowledge and thank their colleagues for their assistance with the OPSAID project.Sandia National Laboratories: Alex Berry, Charles Perine, Regis Cassidy, Bryan Richardson, Laurence PhillipsTeumim Technical, LLC: Dave TeumimIn addition, the authors are greatly indebted to the invaluable help of the members of the OPSAID Core Team. Their assistance has been critical to the success and industry acceptance of the OPSAID project.Schweitzer Engineering Laboratory: Rhett Smith, Ryan Bradetich, Dennis GammelTelTone: Ori Artman Entergy: Dave Norton, Leonard Chamberlin, Mark AllenThe authors would like to acknowledge that the work that produced the results presented in this paper was funded by the U.S. Department of Energy/Office of Electricity Delivery and Energy Reliability (DOE/OE) as part of the National SCADA Test Bed (NSTB) Program. Executive SummaryProcess control systems (PCS) are very important for critical infrastructure and manufacturing operations, yet cyber security technology in PCS is generally poor. The OPSAID (Open PCS (Process Control System) Security Architecture for Interoperable Design) program is intended to address these security shortcomings by accelerating the availability and deployment of comprehensive security technology for PCS, both for existing PCS and inherently secure PCS in the future. All activities are closely linked to industry outreach and advisory efforts.Generally speaking, the OPSAID project is focused on providing comprehensive security functionality to PCS that communicate using IP. This is done through creating an interoperable PCS security architecture and developing a reference implementation, which is tested extensively for performance and reliability.This report first provides background on the PCS security problem and OPSAID, followed by goals and objectives of the project. The report also includes an overview of the results, including the OPSAID architecture and testing activities, along with results from industry outreach activities. Conclusion and recommendation sections follow. Finally, a series of appendices provide more detailed information regarding architecture and testing activities.Summarizing the project results, the OPSAID architecture was defined, which includes modular security functionality and corresponding component modules. The reference implementation, which includes the collection of component modules, was tested extensively and proved to provide more than acceptable performance in a variety of test scenarios. The primary challenge in implementation and testing was correcting initial configuration errors.OPSAID industry outreach efforts were very successful. A small group of industry partners were extensively involved in both the design and testing of OPSAID. Conference presentations resulted in creating a larger group of potential industry partners.Based upon experience implementing and testing OPSAID, as well as through collecting industry feedback, the OPSAID project has done well and is well received. Recommendations for future work include further development of advanced functionality, refinement of interoperability guidance, additional laboratory and field testing, and industry outreach that includes PCS owner education. 4 5 --This page intentionally left blank --

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Supervisory Control and Data Acquisition (SCADA) systems for automation are very important for critical infrastructure and manufacturing operations. They have been implemented to work in a number of physical environments using a variety of hardware, software, networking protocols, and communications technologies, often before security issues became of paramount concern. To offer solutions to security shortcomings in the short/medium term, this project was to identify technologies used to secure "traditional" IT networks and systems, and then assess their efficacy with respect to SCADA systems. These proposed solutions must be relatively simple to implement, reliable, and acceptable to SCADA owners and operators. 4This page intentionally left blank.

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This report presents a classification scheme for risk assessment methods. This scheme, like all classification schemes, provides meaning by imposing a structure that identifies relationships. Our scheme is based on two orthogonal aspects--level of detail, and approach. The resulting structure is shown in Table 1 and is explained in the body of the report. Each cell in the Table represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. This report imposes structure on the set of risk assessment methods in order to reveal their relationships and thus optimize their usage.We present a two-dimensional structure in the form of a matrix, using three abstraction levels for the rows and three approaches for the columns. For each of the nine cells in the matrix we identify the method type by name and example. The matrix helps the user understand: (1) what to expect from a given method, (2) how it relates to other methods, and (3) how best to use it. Each cell in the matrix represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. The matrix, with type names in the cells, is introduced in Table 2 on page 13 below. Unless otherwise stated we use the word 'method' in this report to refer to a 'risk assessment method', though often times we use the full phrase. The use of the terms 'risk assessment' and 'risk management' are close enough that we do not attempt to distinguish them in this report. The remainder of this report is organized as follows. In Section 2 we provide context for this report--what a 'method' is and where it fits. In Section 3 we present background for our classification scheme--what other schemes we have found, the fundamental nature of methods and their necessary incompleteness. In Section 4 we present our classification scheme in the form of a matrix, then we present an analogy that should provide an understanding of the scheme, concluding with an explanation of the two dimensions and the nine types in our scheme. In Section 5 we present examples of each of our classification types. In Section 6 we present conclusions.

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