SEARCH · Engineering Papers

Results for “time security”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Cyber physical attack detection

A cyber-security threat detection system and method stores physical data measurements from a cyber-physical system and extracts synchronized measurement vectors synchronized to one or more timing pulses. The system and method synthesize data integrity attacks in response to the physical data measurements and applies alternating parameterized linear and non-linear operations in response to the synthesized data integrity attacks. The synthesis renders optimized model parameters used to detect multiple cyber-attacks.

Ferragut, Erik M.↗

DOE OSTI2022

Systems and methods for authentication and key agreement in a smart grid

Systems and methods for authentication and key agreement are provided and can utilize a scheme that uses dynamic key generation to achieve replay-attack resistance in zero round trip time (0-RTT). The hash-chain concept can be integrated with the Diffie-Hellman (DH) key exchange scheme. With this scheme, a device can securely determine the new shared key immediately (i.e., in 0-RTT) and start using it.

Akkaya, Kemal↗

DOE OSTI2023

Advanced Reactor Supply Chain Assessment (GAIN Report)

Several net-zero scenario evaluations predict a rapid ramp up of nuclear energy in the coming decades. If this materializes, it will most likely strain the supply chains associated with the potential advanced reactor concepts awaiting deployment. To help assess the current and potential capacities of the various advanced reactor supply chains, the Gateway for Accelerated Innovation in Nuclear (GAIN) conducted a survey of companies able to produce components for advanced reactors in the near future (namely for sodium, gas-cooled, and molten salt reactors). Using an aggressive nuclear deployment scenario, the objective was to assess the ability of the various supply chains to meet the considerable demand projections for certain key components (vessels, heat exchangers, pumps, graphite, and sensors) and identify potential challenges. While individual companies were unable to meet the most optimistic nuclear deployment rate projections, it was found that on aggregate, a United States-based supply chain projected that expansion could be ramped up to meet a larger future demand of these components. However, meeting projected demand for several more complex items (namely gas or salt heat exchangers) was found to be more challenging. Deploying new reactors at scale necessitates the production of more and more supply chain components, requiring a ramp up in production. Supply chain companies were surveyed, and respondents appeared less able to meet short term demand (next year) versus longer-term demand projections (5 and 10 years). This reflects the need to obtain orders with adequate lead times (can range from 3 to 30 months). Future demand will need to be met by expanding existing capacity. These expansions will require suppliers to raise capital or secure other types of support (federal loans or grants) to invest in facilities, equipment, and workforce. Individual suppliers indicated financial investments could be in the range of $\$ $100 million to $\$ $1 billion for their own facilities (depending on the type of facility). The biggest risk, according to respondents, related to general uncertainties surrounding the future nuclear industry and whether the potential demand projections will materialize into real demand that is actionable from a business perspective. Businesses do not seem willing to take investments risks without clear orders. If businesses are not able to invest to expand the supply, it will either delay the deployment of advanced nuclear technology, or the supply chain will be met by suppliers outside of the United States. This report only focuses on the domestic supply chain’s ability to meet the various projections stipulated here for the specific assessed components (vessels, heat exchangers, pumps, graphite, and sensors). The report does not cover all reactor designs or all components that may ultimately be needed for any one reactor design. It also does not address whether any specific aspect of the supply chain will be cost competitive in the global market, nor how potential state-backed entities could affect the expansion of a United States-based supply chain. The largest challenges in ramping up capacity among respondents appear to be workforce related. This includes workforce availability, experience, training, and turnover. In addition to facility investment, suppliers will also need to invest heavily in long-term workforce training to meet production goals. This issue is not nuclear-specific, and the expansion of any supply chain will likely face similar challenges. While suppliers evaluated expected normal business demand from other markets outside of nuclear, it is possible that other market segments could expand more than predicted and compete for the same suppliers. One potential market that may compete for the same supplier resources is the United States military, as many of these suppliers support both the commercial nuclear sector as well as the Navy with reactors and components. In summary, suppliers in the United States believe that there is a way to increase production in order to begin meeting the demand which will exist for advanced reactors—as long as appropriate investments can be made in the supply chain in an appropriate timeframe. Based on the capacity projections and lead times, investment will be needed to meet the 5-year and 10-year production targets. Therefore, if significant nuclear deployment is to occur in the 2030s, investment and ramp up of the advanced nuclear supply chain will need to begin in the near future for the United States to successfully deploy these advanced reactors with domestic supply chains.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2018

Changes in Exercise Data Management

The suite of exercise hardware aboard the International Space Station (ISS) generates an immense amount of data. The data collected, treadmill, cycle ergometer, and resistance strength training hardware, are basic exercise parameters (time, heart rate, speed, load, etc.). The raw data are processed in the laboratory and more detailed parameters are calculated from each exercise data file. Updates recently have been made to how these valuable data are stored, adding an additional level of security, increasing accessibility, and resulting in overall increased efficiency of medical report delivery. Questions regarding exercise performance or how exercise may influence other variables of crew health frequently arise within the crew health care community. Inquiries regarding the health of the exercise hardware often need quick analysis and response to ensure the exercise system is operable on a continuous basis. Consolidating all of the exercise system data in a single repository enables a quick response to both the medical and engineering communities. A SQL server database is currently in use, and provides a secure location for all of the exercise data starting at ISS Expedition 1 to current date. The database has been structured to update derived metrics automatically, making analysis and reporting available within minutes of dropping the in-flight data into the database. Commercial tools were evaluated to help aggregate and visualize data from the SQL database. The Tableau software provides manageable interface, which has improved the laboratory’s output time of crew reports by 67%. Expansion of the SQL database, to be inclusive of additional medical requirement metrics, addition of ‘app-like’ tools for mobile visualization, and collaborative use (e.g., operational support teams, research groups, and International Partners) of the data system, is currently being explored.

Buxton, R. E.↗

NASA NTRS2003

Aerospace Communications Security Technologies Demonstrated

In light of the events of September 11, 2001, NASA senior management requested an investigation of technologies and concepts to enhance aviation security. The investigation was to focus on near-term technologies that could be demonstrated within 90 days and implemented in less than 2 years. In response to this request, an internal NASA Glenn Research Center Communications, Navigation, and Surveillance Aviation Security Tiger Team was assembled. The 2-year plan developed by the team included an investigation of multiple aviation security concepts, multiple aircraft platforms, and extensively leveraged datalink communications technologies. It incorporated industry partners from NASA's Graphical Weather-in-the-Cockpit research, which is within NASA's Aviation Safety Program. Two concepts from the plan were selected for demonstration: remote "black box," and cockpit/cabin surveillance. The remote "black box" concept involves real-time downlinking of aircraft parameters for remote monitoring and archiving of aircraft data, which would assure access to the data following the loss or inaccessibility of an aircraft. The cockpit/cabin surveillance concept involves remote audio and/or visual surveillance of cockpit and cabin activity, which would allow immediate response to any security breach and would serve as a possible deterrent to such breaches. The datalink selected for the demonstrations was VDL Mode 2 (VHF digital link), the first digital datalink for air-ground communications designed for aircraft use. VDL Mode 2 is beginning to be implemented through the deployment of ground stations and aircraft avionics installations, with the goal of being operational in 2 years. The first demonstration was performed December 3, 2001, onboard the LearJet 25 at Glenn. NASA worked with Honeywell, Inc., for the broadcast VDL Mode 2 datalink capability and with actual Boeing 757 aircraft data. This demonstration used a cockpitmounted camera for video surveillance and a coupling to the intercom system for audio surveillance. Audio, video, and "black box" data were simultaneously streamed to the ground, where they were displayed to a Glenn audience of senior management and aviation security team members.

Griner, James H.↗

NASA NTRS2003

CORBASec Used to Secure Distributed Aerospace Propulsion Simulations

The NASA Glenn Research Center and its industry partners are developing a Common Object Request Broker (CORBA) Security (CORBASec) test bed to secure their distributed aerospace propulsion simulations. Glenn has been working with its aerospace propulsion industry partners to deploy the Numerical Propulsion System Simulation (NPSS) object-based technology. NPSS is a program focused on reducing the cost and time in developing aerospace propulsion engines. It was developed by Glenn and is being managed by the NASA Ames Research Center as the lead center reporting directly to NASA Headquarters' Aerospace Technology Enterprise. Glenn is an active domain member of the Object Management Group: an open membership, not-for-profit consortium that produces and manages computer industry specifications (i.e., CORBA) for interoperable enterprise applications. When NPSS is deployed, it will assemble a distributed aerospace propulsion simulation scenario from proprietary analytical CORBA servers and execute them with security afforded by the CORBASec implementation. The NPSS CORBASec test bed was initially developed with the TPBroker Security Service product (Hitachi Computer Products (America), Inc., Waltham, MA) using the Object Request Broker (ORB), which is based on the TPBroker Basic Object Adaptor, and using NPSS software across different firewall products. The test bed has been migrated to the Portable Object Adaptor architecture using the Hitachi Security Service product based on the VisiBroker 4.x ORB (Borland, Scotts Valley, CA) and on the Orbix 2000 ORB (Dublin, Ireland, with U.S. headquarters in Waltham, MA). Glenn, GE Aircraft Engines, and Pratt & Whitney Aircraft are the initial industry partners contributing to the NPSS CORBASec test bed. The test bed uses Security SecurID (RSA Security Inc., Bedford, MA) two-factor token-based authentication together with Hitachi Security Service digital-certificate-based authentication to validate the various NPSS users. The test bed is expected to demonstrate NPSS CORBASec-specific policy functionality, confirm adequate performance, and validate the required Internet configuration in a distributed collaborative aerospace propulsion environment.

Blaser, Tammy M.↗

DOE OSTI2021

Cyber-Attack Detection for Photovoltaic Farms Based on Power-Electronics-Enabled Harmonic State Space Modeling

Here in this paper, a physics-data-based detection method is proposed to detect a variety of cyber-attacks in Photovoltaic (PV) farms using the power electronics-enabled harmonic state space (HSS) models, which, to our knowledge, is original. At the device level, HSS-based detection is developed to monitor harmonic vectors of individual PV converter with minimum sensor measurements, thus improving accuracy and robustness compared to Kalman Filter-based detection. At the system level that involves multiple PV converters, a clustering approach is developed to investigate attack propagation and accurately locate attack sources within a PV farm. The proposed approach is one of the first attempts to address PV security through interaction between the device and system, maximizing the accuracy and robustness at different levels. To verify the feasibility, a comprehensive attacks model is built, including single attack, coordinated attacks, and replay attacks. Besides, the impacts of irradiance changes are taken into consideration in the test scenarios. With the real-time data acquisition and hardware-in-the-loop testbed, comprehensive test results are provided to verify the feasibility of the proposed detection methodology.

42 ENGINEERING↗

NASA NTRS2018

Changes in Exercise Data Management

The suite of exercise hardware aboard the International Space Station (ISS) generates an immense amount of data. The data collected from the treadmill, cycle ergometer, and resistance strength training hardware are basic exercise parameters (time, heart rate, speed, load, etc.). The raw data are post processed in the laboratory and more detailed parameters are calculated from each exercise data file. Updates have recently been made to how this valuable data are stored, adding an additional level of data security, increasing data accessibility, and resulting in overall increased efficiency of medical report delivery. Questions regarding exercise performance or how exercise may influence other variables of crew health frequently arise within the crew health care community. Inquiries over the health of the exercise hardware often need quick analysis and response to ensure the exercise system is operable on a continuous basis. Consolidating all of the exercise system data in a single repository enables a quick response to both the medical and engineering communities. A SQL server database is currently in use, and provides a secure location for all of the exercise data starting at ISS Expedition 1 - current day. The database has been structured to update derived metrics automatically, making analysis and reporting available within minutes of dropping the inflight data it into the database. Commercial tools were evaluated to help aggregate and visualize data from the SQL database. The Tableau software provides manageable interface, which has improved the laboratory's output time of crew reports by 67%. Expansion of the SQL database to be inclusive of additional medical requirement metrics, addition of 'app-like' tools for mobile visualization, and collaborative use (e.g. operational support teams, research groups, and International Partners) of the data system is currently being explored.

Buxton, R. E.↗

DOE OSTI2025

Secure State Estimation with Asynchronous Measurements for Coordinated Cyber Attack Detection in Active Distribution Systems

Coordinated cyber attacks tamper with measurement data to disrupt the situational awareness of active distribution systems. Various sensors report measurements asynchronously at different rates, which introduces challenges during state estimation. In addition, this forces cyber intruders to exert greater effort to compromise multiple communication channels and launch coordinated attacks. Therefore, multi-channel and asynchronous measurements could be harnessed to develop more secure cyber defense strategies. In this paper, a prediction-correction-based multi-rate observer is designed to exploit the value of asynchronous measurements for the detection of coordinated false data injection (FDI) attacks. First, a time-function-dependent prediction-correction strategy is proposed to adjust the sampling interval for each sensor’s measurement. Then, an observer is designed based on the trade-off between estimation error and the optimal period of the most recent sampling instant, with the convergence of estimation error with the maximum permitted sampling interval. Moreover, the conditions for exponential stability are developed using the Lyapunov–Krasovskii functional technique. Next, a coordinated FDI attack detection strategy is developed based on the dual nonlinear minimization problem. The proposed attack detection and secure state estimation strategies are tested on the IEEE 13-node system. Simulation results show that these schemes are effective in enhancing attack detection based on asynchronous measurements or compromised data.

asynchronous measurements↗

DOE OSTI2023

A Photovoltaic MPPT Charge Controller Real-Time Testbed for Cybersecurity Applications

The increasing deployment of distributed energy resources (DER) over the last decade is a great ally to combat climate change and strengthen the grid during increasingly common extreme weather events. However, DER systems, combined with the ongoing transition to a digital power grid, also pose substantial cybersecurity threats. One of the most common communication protocols used in DER integration is the Distributed Network Protocol 3 (DNP3), which is known to have many security vulnerabilities. Thus, it is essential to investigate cyberattack behaviors and mitigation on power systems using DNP3. In this paper, we designed and implemented a cybersecurity testbed for a simulated photovoltaic (PV) maximum power point tracking (MPPT) charge controller. Our testbed uses an MPPT charge controller simulated on a Typhoon HIL602+ real-time simulator with a real DNP3 communication connection over TCP/IP, allowing for safe and efficient monitoring and manipulation of data traffic between the simulated hardware and supervisory control and data acquisition (SCADA) systems.

14 SOLAR ENERGY↗

DOE OSTI2021

Incorporating the Role(s) of Human Actors in Complex System Design for Safety and Security

Traditional systems engineering demonstrates the importance of customer needs in scoping and defining design requirements; yet, in practice, other human stakeholders are often absent from early lifecycle phases. Human factors are often omitted in practice when evaluating and down-selecting design options due to constraints such as time, money, access to user populations, or difficulty in proving system robustness through the inclusion of human behaviors. Advances in systems engineering increasingly include non-technical influences into the design, deployment, operations, and maintenance of interacting components to achieve common performance objectives. Furthermore, such advances highlight the need to better account for the various roles of human actors to achieve desired performance outcomes in complex systems. Many of these efforts seek to infuse lessons and concepts from human factors (enhanced decision-making through Crew Resource Management), systems safety (Rasmussen's “drift toward danger”) and organization science (Giddens' recurrent human acts leading to emergent behaviors) into systems engineering to better understand how socio-technical interactions impact emergent system performance. Safety and security are examples of complex system performance outcomes that are directly impacted by varying roles of human actors. Using security performance of high consequence facilities as a representative use case, this article will outline the System Context Lenses to understand how to include various roles of human actors into systems engineering design. Several exemplar applications of this organizing lenses will be summarized and used to highlight more generalized insights for the broader systems engineering community.

42 ENGINEERING↗

DOE OSTI2026

Feasibility and strategic implications of deploying nuclear power reactors in Africa

This report assesses the feasibility and strategic implications of deploying nuclear power reactors, including large-scale plants, advanced small modular reactors (SMRs), and microreactors, in African countries. Case studies focus on South Africa, Egypt, Kenya, Ghana, and Nigeria, examining nuclear energy’s role in Africa’s rapidly evolving energy landscape, marked by fast-growing demand, significant electricity access gaps, increasing renewable penetration, and strong policy commitments to industrialization and energy security. Several U.S. reactor technologies and designs are considered based on their development status and readiness for deployment. The analysis finds that nuclear power can provide reliable, clean baseload and flexible generation, as well as high-temperature process heat for desalination, hydrogen production, and industrial applications. However, suitability is highly country-specific, depending on grid size and stability, transmission capacity, cooling water availability, regulatory readiness, and fuel supply chains. Near-term deployment opportunities are strongest for light-water reactors (such as NuScale, BWRX-300, AP300, and SMR-300) that use low-enriched uranium and build on proven technology. More advanced concepts, including gas-cooled, sodium-cooled, molten-salt cooled reactors, and microreactors, will likely be relevant for African deployment in the 2030s or later, contingent on demonstration projects, high-assay low-enriched uranium (HALEU) fuel availability, and mature international licensing frameworks. Economic analysis shows that SMRs are capital-intensive, with projected overnight costs for 300 MWe units in 2025 ranging from approximately 1.4 to 2.6 billion USD per module. The levelized cost of electricity (LCOE) is highly sensitive to the weighted average cost of capital (WACC). Given typically higher financing costs and utility balance-sheet weaknesses in many African countries, bankable project structures will require sovereign guarantees, robust offtake arrangements, and layered financing from export credit agencies, development finance institutions, and vendor nations. Comparisons with recent large nuclear projects in the United Arab Emirates (UAE) and Egypt underscore the central role of state-backed loans, long tenors, and concessional terms. Country case studies illustrate a spectrum of readiness and opportunity. South Africa operates two 920 MWe pressurized light water reactors (totaling 1,840 MWe) at Koeberg and has the most mature regulatory and industrial base, positioning it as a prime candidate for both large reactors and SMRs to replace coal, support desalination, and anchor industrial hubs. Egypt is constructing four VVER-1200 units at El Dabaa with strong state leadership and could later complement this fleet with SMRs for coastal and industrial applications. Kenya and Ghana are advancing through IAEA Milestones with growing institutional capacity and clear interest in SMRs that match their smaller grids and industrialization plans. Nigeria has the largest demand potential but faces acute constraints in grid reliability, project bankability, and regulatory capacity; targeted deployments of large reactors and SMRs near coastal or industrial sites could have high impact if accompanied by major grid upgrades and institutional reforms. The report identifies cross-cutting challenges such as financing, political continuity, public acceptance, nonproliferation and security, waste and back-end management, regulatory capacity, grid adequacy, and long deployment timelines for first-of-a-kind designs, and ANL/NSE-26/3 ii proposes broad directions for resolution. These include stronger multifaceted financing for nuclear, long-term national energy strategies that transcend electoral cycles, proactive stakeholder engagement, strengthened regional and national regulators, and systematic workforce development through centers of excellence and expanded training. The United States should develop partnerships with African countries and offer end-to-end nuclear package similar to those used effectively by competitors: coordinated project development, state-backed financing, long-term fuel services, and durable in-country support through regional offices and sustained workforce/regulatory training. With timely planning, sustained political commitment, and appropriate financing and institutional support, nuclear energy, both large reactors and advanced SMRs, can become a meaningful, though not dominant, pillar of Africa’s future power mix, enhancing energy security, enabling industrial growth, and supporting climate goals.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Multi‐Layered Systems for Permanent Geologic Storage of CO 2 at the Gigatonne Scale

Abstract The effectiveness of Carbon Capture and Storage (CCS) as an imperative decarbonization technology relies on the sealing capacity of a fine‐grained caprock to permanently store CO 2 deep underground. Uncertainties in assessing the caprock sealing capacity increase with the spatial and temporal scales and may delay CCS deployment at the gigatonne scale. We have developed a computationally efficient transport model to capture the dynamics of basin‐wide upward CO 2 migration in a multi‐layered setting over geological time scales. We find that massive capillary breakthrough and viscous flow of CO 2 , even through pervasively fractured caprocks, are unlikely to occur and compromise the storage security. Potential leakage from the injection reservoir is hampered by repetitive layering of overlying caprocks. This finding agrees with geologic intuition and should be understandable by the public, contributing to the development of climate policies around this technology with increased confidence that CO 2 will be indefinitely contained in the subsurface.

58 GEOSCIENCES↗

DOE OSTI2023

Rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor

Abstract Terahertz waves offer advantages for nondestructive detection of hidden objects/defects in materials, as they can penetrate most optically-opaque materials. However, existing terahertz inspection systems face throughput and accuracy restrictions due to their limited imaging speed and resolution. Furthermore, machine-vision-based systems using large-pixel-count imaging encounter bottlenecks due to their data storage, transmission and processing requirements. Here, we report a diffractive sensor that rapidly detects hidden defects/objects within a 3D sample using a single-pixel terahertz detector, eliminating sample scanning or image formation/processing. Leveraging deep-learning-optimized diffractive layers, this diffractive sensor can all-optically probe the 3D structural information of samples by outputting a spectrum, directly indicating the presence/absence of hidden structures or defects. We experimentally validated this framework using a single-pixel terahertz time-domain spectroscopy set-up and 3D-printed diffractive layers, successfully detecting unknown hidden defects inside silicon samples. This technique is valuable for applications including security screening, biomedical sensing and industrial quality control.

Li, Jingxi (ORCID:0000000165958680)↗

DOE OSTI2025

Efficiently Verifiable Quantum Advantage on Near-Term Analog Quantum Simulators

Existing schemes for demonstrating quantum computational advantage are subject to various practical restrictions, including the hardness of verification and challenges in experimental implementation. Meanwhile, analog quantum simulators have been realized in many experiments to study novel physics. In this work, we propose a quantum advantage protocol based on verification of an analog quantum simulation, in which the verifier need only run an O ( λ 2 ) -time classical computation, and the prover need only prepare O ( 1 ) samples of a history state and perform O ( λ 2 ) single-qubit measurements, for a security parameter λ . We also propose a near-term feasible strategy for honest provers and discuss potential experimental realizations. Published by the American Physical Society 2025

Liu, Zhenning (ORCID:000000020794419X)↗

DOE OSTI2020

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We suggest a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118-and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We propose a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118- and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

alternating direction method of multipliers↗

DOE OSTI2020

Learning to Solve Large-Scale Security-Constrained Unit Commitment Problems

Security-constrained unit commitment (SCUC) is a fundamental problem in power systems and electricity markets. In practical settings, SCUC is repeatedly solved via mixed-integer linear programming (MIP), sometimes multiple times per day, with only minor changes in input data. In this work, we propose a number of machine learning techniques to effectively extract information from previously solved instances in order to significantly improve the computational performance of MIP solvers when solving similar instances in the future. Based on statistical data, we predict redundant constraints in the formulation, good initial feasible solutions, and affine subspaces where the optimal solution is likely to lie, leading to a significant reduction in problem size. Computational results on a diverse set of realistic and large-scale instances show that using the proposed techniques, SCUC can be solved on average 4.3 times faster with optimality guarantees and 10.2 times faster without optimality guarantees, with no observed reduction in solution quality. Out-of-distribution experiments provide evidence that the method is somewhat robust against data-set shift. Summary of Contribution. The paper describes a novel computational method, based on a combination of mixed-integer linear programming (MILP) and machine learning (ML), to solve a challenging and fundamental optimization problem in the energy sector. The method advances the state-of-the-art, not only for this particular problem, but also, more generally, in solving discrete optimization problems via ML. We expect that the techniques presented can be readily used by practitioners in the energy sector and adapted, by researchers in other fields, to other challenging operations research problems that are solved routinely.

Machine Learning↗