1 Smart Grid Design, Development, and Cyber Security for Small Modular ReactorsInvited Presentation Sal Rodríguez Advanced Nuclear Concepts Org. 6221 Principal Member of the Tech Staff Sandia National Laboratories (505) CyberCon 2.0 San Juan College April 27, 2017 SNL document SAND C. Tracking number Unclassified Unlimited Release. 04/25/2017. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL SAND NO PR
2 Introduction Motivation—Why Small Modular Reactors (SMRs) in Smart Grids and Microgrids? Sandia National Laboratories’ (SNL) Integral Approach for Economically-Viable SMRs: High Performance Computing (HPC) and Computational Dynamics Coupled Multi-Physics, Computational Fluid Dynamics (CFD) Smart Grid Tools Advanced Manufacturing (AM) State-of-the-Art Experiments Balance Between Smart and CyberSecurity Path Forward Conclusion
3 Motivation We are faced with a difficult challenge as a result of diminishing natural resources, a more fragile environment, and increasing population. Cities with limited water supplies cannot sustain water-based power systems. Evaporative water loss at power-generating sites is significant. Current water cycles require 650 to 850 gallons of water per MWh of generated electricity. 80,000,000 gallons of water per day is evaporated at Palo Verde nuclear reactors. Clearly, this trend is unsustainable under a growing population with diminishing natural resources. It is therefore crucial that more efficient energy and water technologies be developed, while reducing environmental impact. An ideal solution is the inclusion of SMRs onto smart microgrids.
4 Motivation The Department of Energy (DOE) is leading grid infrastructure modernization. Smart grids and microgrids are a crucial component for enabling the nation’s future energy needs. Smart grids and microgrids are being considered in niche applications, and as part of a comprehensive energy strategy: Manage the nation’s growing energy demands, Critical infrastructures, Military installations, Small rural communities, and Large populations with limited water supplies.
5 Why SMRs in Smart Grids? SMRs have many exclusive features found in no other energy source. Unique SMR features that are highly desirable for integration onto smart grids: High reliability, Scalable, right-sized power sources, Economical, Load balancing, Highly-reduced CO2 footprint, Diversified energy portfolio, and Strong potential for lower water usage. Nuclear, solar, and wind energy output cycles—benefit of nuclear load balancing [NuScale Why SMR, 2017A].
6 Why SMRs in Smart Grids? If various cost-reducing measures are implemented, SMRs have a lower levelized unit electricity cost (LUEC) than conventional (large) reactors. SMR cost comparison vs. conventional reactor: pessimistic cost reduction factors. SMR cost comparison vs. conventional reactor: optimistic cost reduction factors.
7 Why SMRs in Smart Grids? Heat rejection to the environment with waterless-power system. Nuclear’s small CO2 footprint. SMR with waterless power generation [Rodriguez, 2017A]. CO2 Gas Emission from Various Energy Sources [NuScale Why SMR, 2017C].
8 HPC and Computational DynamicsSNL has 179,858 parallel processors, for an astonishing computational power equal to 3,706 teraflops. As an example, an air-cooled nuclear fuel bundle simulation using 128 processors requires a total of 10 hours to complete. This represents just 0.071% of Sandia’s total HPC capacity! Our HPC provides system designers and analysts a tool that, compared with experiments, is Less costly, Provides more data (including data that is not currently measurable with current instrumentation), and Probes deeper into system behavior; exploits physics for better designs. This allows for the development of more efficient energy systems that are more cost-competitive and more benign towards the environment.
9 HPC and Computational DynamicsCoupled CFD, heat transfer, and structural analysis of Westinghouse fuel rod [Rodriguez and Turner, 2012]. CFD simulation of natural circulation fuel bundle experiment—velocity and temperature distribution [Rodriguez, 2016B].
10 Smart Grid/Microgrid TechnologySandia’s current computational capabilities model the entire grid, including temporal aspects and cyber security issues. Includes a comprehensive set of tools for system development, integration, testing and evaluation, monitoring, and sustainment. State-of-the-art smart grid tools at SNL: Smart Power Infrastructure Demonstration for Energy Reliability and Security (SPIDERS): a suite of smart grid methodologies and tools. Energy Surety Design Methodology (ESDM): a quantitative, risk-based tool to enable communities to identify and solve critical, high-priority energy needs. Reference Architecture (RA): has been validated and applied to civilian and military critical infrastructures. Microgrid Cybersecurity Reference Architecture (MCRA): a tool to perform cybersecurity analysis, including design and implementation of secure microgrid control networks, network segmentation, and monitoring. Microgrid Design Toolkit (MDT): optimizes microgrid designs for civilian and military applications.
11 Smart Grid/Microgrid TechnologySummary of Sandia’s experience with smart microgrids: design and cyber security [Nanco, 2016]. .
12 Smart Grid/Microgrid TechnologyAreas where Sandia excels in smart grid/microgrid modernization: Grid cybersecurity and resilience, Planning and implementation assessments, Integration of distributed resources, renewables, and SMRs, Probabilistic methods, Grid enhancement and improved efficiency, Energy storage, and System dampening/load balancing. Primary oscillation mode shapes for grid security [Pierre et al., 2016A].
13 Advanced ManufacturingSandia’s goal is manufacturing of fast and cost-effective system components. Our current AM areas of interest and research include technologies that are either exclusive to Sandia, or that are currently being advanced by Sandia: FastCast, Laser engineered net shaping, RoboCast, Direct write, Thermal spray, and Micro-nano scale manufacturing. Our three major AM areas of research and development are analysis-driven design tools, materials assurance, and multi-material components. The ultimate goal of our AM program is to have a fully-integrated, model-based, design/production approach that is agile, affordable, and assured.
14 Advanced ManufacturingAM has various remarkable advantages over conventional manufacturing that can be exploited for SMR applications: Simplification of the assembly process (integration), Streamlined path from design to prototyping, Generation of complex geometries and material composites, and On-site manufacturing for reduced shipping cost, as well as reduced assembly time. Current areas of AM sensitivity research at Sandia include process and material variability. Conceptually, process sensitivity control will be achieved with point qualification of AM parts, better understanding of the dynamics for machine and process variability, and process qualification. These will be synthesized with the goal of deriving AM best practices.
15 Advanced ManufacturingAn example of thermal spray using metal on plastic at Sandia [Smith, 2016]. An example of simplified assembly process, rapid prototyping, and the generation of complex geometries at Sandia [Smith, 2016]. An example of FastCast at Sandia [Smith, 2016].
16 Advanced ManufacturingCut-off point for profitability: AM vs. conventional manufacturing. Cost comparison between AM and conventional manufacturing [AT Kearney, 2015].
17 State-of-the-Art ExperimentsParticle image velocimetry (PIV) allows Economical experimental observation of system fluid velocity. Provides design optimization based on data analysis. Example: design an inexpensive, passive, water tank for collection of solar heat (modular solar water tank—MSWT). Tools: HPC, CFD, and PIV. Recent advances in dimpled surfaces. Results: MSWT harvests $575.10/yr solar heat. Total cost to build device: $1, Break-even point: 2.6 years. PIV and CFD comparison of experimental vs. computational velocity.
18 State-of-the-Art Experiments1 MW sCO2 Brayton Loop. 550 C, 14 MPa. Enable waterless power production. Commercialize the technology, scale to 1 GW by 2020 [Rochau, 2014].
19 Balance Between Smart and CyberSecuritySo, ‘smart’ grids help enable abundant energy at competitive cost… …but its inherent nature can make systems prone to cyber attacks. Clearly, a cost/risk/benefit balance must be achieved… …hence grid/microgrid cybersecurity tools and measures. “What we know about North Korea's failed missile launch” By Luis Martinez Apr 17, 2017, 5:27 PM ET, ABC News The North Korean missile that exploded shortly after launch on Saturday was a new kind of single-stage missile that the country had previously tested in another failed launch two weeks ago. The launch failure has fueled speculation about the possibility that the United States may be using cyber technology to interfere with North Korea's missile program. “Russia claims it can wipe out US Navy with single 'electronic bomb‘” Published April 19, 2017 Russia has claimed it can disable the entire US Navy in one fell swoop using powerful electronic signal jamming. A news report from the country – where the media is essentially controlled by the state – said the technology could render planes, ships and missiles useless…
20 Balance Between Smart and CyberSecurityCybersecurity in NuScale SMR MicroGrids: Jose Reyes, Co-Founder and Chief Technology Officer, “An SMR Perspective”, NuScale, February 8, 2017.
21 Path Forward How Can We Contribute Towards Making SMRs/Smart Grids Cost-Competitive? Near Term: Couple the computational physics with the smart grid tools. Apply the HPC towards the streamlined design and modeling of an entire SMR coupled to the grid. Apply scaling to validate subsystem behavior using PIV, etc. Seek niche applications where AM technology makes SMRs more cost-competitive than conventional manufacturing: Any system components where assembly simplifications result in a reduction in the integration work,
22 Path Forward How Can We Contribute Towards Making SMRs/Smart Grids Cost-Competitive? Near Term (continued): Apply tools to new SMR subsystems that still require research and development. Rapid prototyping of the subsystems will result in significantly-reduced costs because of the close coupling between design, computational analysis, and experimental validation. Production of any subcomponents with complex geometries, especially components that are only needed in small quantities. On-site manufacturing.
23 Path Forward How Can We Contribute Towards Making SMRs/Smart Grids Cost-Competitive? Long Term: Parallelize the smart grid tools. Increase the fidelity of the SMR-smart grid designs for additional functionality and higher economic return on investment. Perform state-of-the-art experiments to further optimize the system performance and to validate the design metrics. The number of AM components that are cost-competitive will increase as best-practice process and materials controls are implemented, systems are integrated, and larger components are manufactured. Continue to seek agile, affordable, and assured fully-integrated, model-based design/production. As material variability is controlled to approach nuclear-grade quality, more economical manufacturing of complex metallic composites and streamlined subsystem integration will occur.
24 Path Forward How Can We Contribute Towards Making SMRs Cost-Competitive? Long Term (continued): This will allow AM of larger nuclear components or nuclear-grade subsystems (e.g., vessel heads, nuclear-qualified material components, and complex structures). The goal is to attain ever-higher complexity, starting from relatively simple subsystems, expanding onto highly-complex systems, and culminating in system of systems. For example: start with AM of fuel rods, followed by AM of entire fuel assemblies, and culminating in more complex systems (e.g., entire nuclear cores, vessel heads, etc.).
25 Summary/Conclusion SMRs are ideal for enabling environmentally-benign, cost-efficient, load-balanced, diversified, power-production in smart grids. High performance computational dynamics is not just “eye candy”, but a powerful predictor of system/design behavior and a resource for advanced systems with excellent profitable margins. Smart grid tools are already providing many solutions, as part of DOE’s desire to modernize the grid and provide reliable, economical energy. AM already provides cost-competitive SMR components; this trend is expected to increase dramatically as best-practices are implemented. State-of-the-art PIV and various modern experimental tools validate system designs and provide data for additional design improvements. The confluence of smart grid tools, HPC, AM, and state-of-the-art experiments are key for profitable SMR/smart grid development. Government/labs/universities: need to seek and partner in emergent technologies that have a strong potential for return on investment. Industrial collaboration, scientific advances, and profit will fuel the technical advances and infrastructure of the future.