High-altitude electromagnetic pulses pose an unknown risk to the electric power grid, and the vulnerabilities will continue to arise as the structure and needs of the grid change. This is especially true with the increasing prevalence of renewable energy sources. This work investigates the vulnerability of photovoltaic modules to E1-like radiated environments with maximum field levels exceeding 100 kV/m. State of health checks via I-V curve trace measurements and physical inspection indicated no readily observable damage or degradation of the module behavior after multiple field exposures. Any variation in I-V curve data was attributable to ambient conditions at the time of measurement and was reflected in similar measurements of the experimental control. Follow-up measurements with a calibrated light source showed that all modules aligned with the experimental control and exceeding the manufacturer ratings for fill factor and efficiency, implying that no damage was incurred from field exposure. Coupled current measurements were also performed over the course of testing, showing a damped sine response in common mode and double exponential response in differential mode. The responses were observed to scale with incident field and were dependent on the module orientation.
High-altitude electromagnetic pulses pose an unknown risk to the electric power grid, and the vulnerabilities will continue to arise as the structure and needs of the grid change. This is especially true with the increasing prevalence of renewable energy sources. This work investigates the vulnerability of photovoltaic modules to E1-like radiated environments with maximum field levels exceeding 100 kV/m. State of health checks via I-V curve trace measurements and physical inspection indicated no readily observable damage or degradation of the module behavior after multiple field exposures. Any variation in I-V curve data was attributable to ambient conditions at the time of measurement and was reflected in similar measurements of the experimental control. Follow-up measurements with a calibrated light source showed that all modules aligned with the experimental control and exceeding the manufacturer ratings for fill factor and efficiency, implying that no damage was incurred from field exposure. Coupled current measurements were also performed over the course of testing, showing a damped sine response in common mode and double exponential response in differential mode. The responses were observed to scale with incident field and were dependent on the module orientation.
Impacts of a high-altitude electromagnetic pulse (HEMP) on the power grid are a growing concern due to the increased reliance on the power grid. A critical area of research is quantifying power system equipment response to HEMP since this is not known in general. Substation site surveys were performed at seven high voltage substations across the United States to gather substation layout and construction details pertinent to HEMP coupling calculations and component vulnerability assessments. The primary objective for the survey was to gather information on cable layouts and cable construction within substations. Additional information was also gathered on equipment present within the substations and control house layouts. This report provides information gathered from the substation surveys.
This report details the test setup, process, and results for radiated susceptibility testing of multicrystalline silicon photovoltaic (PV) modules as part of the EMP-Resilient Electric Grid Grand Challenge Laboratory Directed Research and Development (LDRD) project at Sandia National Laboratories. Testing was conducted over October 10-17, 2019, where 8 photovoltaic modules were exposed to E1 transient pulses with peak field levels up to 100 kV/m. Modules were terminated in a resistive load representing connected components. State of health testing conducted via I-V curve tracing of the photovoltaic modules showed no observable loss of device function due to large electric field transients. Differential mode currents were measured on the order of 10's of amps for up to a microsecond following the radiated field pulse. Common mode currents took the form of a damped sinusoid with a maximum peak of 10's to 100's of amps with a resonance near 60 MHz.
This report explores the reliance on communication systems for bulk grid operations and considers selected options as a supplement to cyber security. The extreme scenario of a complete loss of communications for power grid operation is assessed, presenting a bounded, worst-case perspective. The paper explores grid communications failures and how a system modifications can, at an increased cost, retain a moderate level of preparedness for a loss of communications and control when used in partnership with cyber security protocols. Doing so allows the increased economic and secure operation that communication based controls affords, but also ensures a level of resilient operation if they are lost. The motivation of this paper is due to the proliferation of photovoltaic (PV) resources, and more generally, smart-grid resources within the US grid, which are requiring more and more active and wide-area controls. Though the loss of communication and control can affect nearly any grid control system, the risk of losing load at large scales requires a broad view of system interconnectivity, so it has been evaluated from a transmission perspective in this report.
This project explored coupling modeling and analysis methods from multiple domains to address complex hybrid (cyber and physical) attacks on mission critical infrastructure. Robust methods to integrate these complex systems are necessary to enable large trade-space exploration including dynamic and evolving cyber threats and mitigations. Reinforcement learning employing deep neural networks, as in the AlphaGo Zero solution, was used to identify "best" (or approximately optimal) resilience strategies for operation of a cyber/physical grid model. A prototype platform was developed and the machine learning (ML) algorithm was made to play itself in a game of 'Hurt the Grid'. This proof of concept shows that machine learning optimization can help us understand and control complex, multi-dimensional grid space. A simple, yet high-fidelity model proves that the data have spatial correlation which is necessary for any optimization or control. Our prototype analysis showed that the reinforcement learning successfully improved adversary and defender knowledge to manipulate the grid. When expanded to more representative models, this exact type of machine learning will inform grid operations and defense - supporting mitigation development to defend the grid from complex cyber attacks! This same research can be expanded to similar complex domains.
Power system utilities continue to strive for increased system resiliency. However, quantifying a baseline system resilience, and deciding the optimal investments to improve their resilience is challenging. This paper discusses a method to create scenarios, based on historical data, that represent the threats of severe weather events, their probability of occurrence, and the system wide consequences they generate. This paper also presents a mixed-integer stochastic nonlinear optimization model which uses the scenarios as an input to determine the optimal investments to reduce the system impacts from those scenarios. The optimization model utilizes a DC power flow to determine the loss of load during an event. Loss of load is the consequence that is minimized in this optimization model as the objective function. The results shown in this paper are from the IEEE RTS-96 three area reliability model. The scenario generation and optimization model have also been utilized on full utility models, but those results cannot be published.
Power system utilities continue to strive for increased system resiliency. However, quantifying a baseline system resilience, and deciding the optimal investments to improve their resilience is challenging. This paper discusses a method to create scenarios, based on historical data, that represent the threats of severe weather events, their probability of occurrence, and the system wide consequences they generate. This paper also presents a mixed-integer stochastic nonlinear optimization model which uses the scenarios as an input to determine the optimal investments to reduce the system impacts from those scenarios. The optimization model utilizes a DC power flow to determine the loss of load during an event. Loss of load is the consequence that is minimized in this optimization model as the objective function. The results shown in this paper are from the IEEE RTS-96 three area reliability model. The scenario generation and optimization model have also been utilized on full utility models, but those results cannot be published.
This report documents the use of wind turbine inertial energy for the supply of two specific electric power grid services; system balancing and real power modulation to improve grid stability. Each service is developed to require zero net energy consumption. Grid stability was accomplished by modulating the real power output of the wind turbine at a frequency and phase associated with wide-area modes. System balancing was conducted using a grid frequency signal that was high-pass filtered to ensure zero net energy. Both services used Phasor Measurement Units (PMUs) as their primary source of system data in a feedforward control (for system balancing) and feedback control (for system stability).
This paper discusses the broad use of rotational kinetic energy stored in wind turbine rotors to supply services to the electrical power grid. The grid services are discussed in terms of zero-net-energy, which do not require a reduction in power output via pitch control (spill), but neither do they preclude doing so. The services discussed include zero-net-energy regulation, transient and small signal stability, and other frequency management services. The delivery of this energy requires a trade-off between the frequency and amplitude of power modulation and is limited, in some cases, by equipment ratings and the unresearched long-term mechanical effects on the turbine. As wind displaces synchronous generation, the grid's inertial storage is being reduced, but the amount of accessible kinetic energy in a wind turbine at rated speed is approximately 6 times greater than that of a generator with only a 0.12% loss in efficiency and 75 times greater at 10% loss. The potential flexibility of the wind's kinetic storage is also high. However, the true cost of providing grid services using wind turbines, which includes a potential increase in operations and maintenance costs, have not been compared to the value of the services themselves.
This report characterizes communications network latency under various network topologies and qualities of service (QoS). The characterizations are probabilistic in nature, allowing deeper analysis of stability for Internet Protocol (IP) based feedback control systems used in grid applications. The work involves the use of Raspberry Pi computers as a proxy for a controlled resource, and an ns-3 network simulator on a Linux server to create an experimental platform (testbed) that can be used to model wide-area grid control network communications in smart grid. Modbus protocol is used for information transport, and Routing Information Protocol is used for dynamic route selection within the simulated network.
The Energy Surety Design Methodology (ESDM) provides a systematic approach for engineers and researchers to create a preliminary electric grid design, thus establishing a means to preserve and quickly restore customer-specified critical loads. Over a decade ago, Sandia National Laboratories (Sandia) defined Energy Surety for applications with energy systems to include elements of reliability, security, safety, cost, and environmental impact. Since then, Sandia has employed design concepts of energy surety for over 20 military installations and their interaction with utility systems, including the Smart Power Infrastructure Demonstration for Energy Reliability and Security (SPIDERS) Joint Capability Technology Demonstration (JCTD) project. In recent years, resilience has also been added as a key element of energy surety. This methodology document includes both process recommendations and technical guidance, with references to useful tools and analytic approaches at each step of the process.
In 2012, Hurricane Sandy devastated much of the U.S. northeast coastal areas. Among those hardest hit was the small community of Hoboken, New Jersey, located on the banks of the Hudson River across from Manhattan. This report describes a city-wide electrical infrastructure design that uses microgrids and other infrastructure to ensure the city retains functionality should such an event occur in the future. The designs ensure that up to 55 critical buildings will retain power during blackout or flooded conditions and include analysis for microgrid architectures, performance parameters, system control, renewable energy integration, and financial opportunities (while grid connected). The results presented here are not binding and are subject to change based on input from the Hoboken stakeholders, the integrator selected to manage and implement the microgrid, or other subject matter experts during the detailed (final) phase of the design effort.