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Schematic of gas-electric system test case.

Project purpose

This project continues the fundamental research effort at LANL to model the dynamic behavior and interactions of these critical infrastructure systems, and develops techniques to analyze, coordinate, and optimize their operations. The objectives are to 1) advance gas pipeline physics and engineering models to improve dynamic pipeline optimization technology; 2) formulate gas and electricity transmission network optimization problems to include improved models, engineering economics, and resilience analysis support; and 3) develop methods for forecasting pipeline loads, state estimation, and management of uncertainty using real-time measurement data. In the short term, this project will develop models of intra-day behavior of coupled gas-electricity networks, to support resilience analysis of response to rapid changes in loads or other disruptions. In the long term, the developed methods will be transitioned to industry to create commercial decision support tools that will improve pipeline operations and wholesale natural gas markets to enable responsive delivery on the time-scales of decision-making for the power grid. Crucially, the developed algorithms and methods will be rooted in solid mathematics and physics foundations, and will be cross-validated using state-of-the-art commercial tools and data from real systems.


Technical approach

In past projects, LANL and collaborators have achieved breakthroughs in modeling and optimization of gas pipeline dynamics and coordination of gas pipeline and electric power delivery systems using market-based, optimization-driven approaches. First, these complex dynamics were analyzed to separate the key temporal scales to reveal the cross-infrastructure dynamical interactions of natural gas line-pack and underground storage with the multi-scale, time-linked, electrical constraints resulting from generator operations and control. Further dynamical analysis generated key results for advanced operational optimization and control of these coupled infrastructures: monotonicity of gas flows and gas pressure for both quasi-static and dynamical settings, which can be used for advanced cross-infrastructure security assessments. The pipeline dynamics and coupled gas-grid models were incorporated into optimization formulations beginning with quasi-static optimal gas flow, and advancing to dynamical optimal gas flow and optimal dynamic gas-grid operations and market-based coordination. Together with industry partners, we have examined business practices, operational realities, and regulatory environments of the wholesale gas and electricity transmission sectors. This led to explorations of optimization-based gas market designs and gas-electric coordination mechanisms. The modeling advances, computational methods, and coordination mechanisms that were developed have been validated in a number of studies on synthetic test cases, as well as back cast simulations using real data. The developed models were also adapted for state and parameter estimation, as preliminary work towards the data assimilation tools needed for fielding pipeline control systems. We have also developed methods for resilience analysis of electricity and coupled gas-electric systems.

The current project continues to extend our research to 1) solve fundamental applied mathematics problems arising from gas-electric system modeling, estimation, optimization, and control; 2) develop tools for efficient and computationally tractable gas-electric system resilience analysis that represents ambiguous and non-transparent human factors using optimization; 3) enable future development of pipeline transient optimization tools, gas pipeline market designs, and gas-electric coordination mechanisms that can be demonstrated in pilot projects by improving, extending, and providing solution guarantees on prototype models and algorithms.


Advanced gas dynamics modeling to improve pipeline transient optimization

Current pipeline transient models require relatively fine spatial discretization of the pipeline network, resulting in costly computation of solutions to optimization problems. Starting from the basic physics, we will develop models that admit much coarser spatial discretization and linear or quasi-linear representation to enable scaling up of dynamic optimization tools to provide solutions for very-large interconnected pipelines. To advance our progress towards acceptance by our long-term industry collaborators, we will account for how pipeline flows can control using current and emerging technology and business practices. Solutions will be benchmarked and validated on test cases synthesized using models and time-series data of real pipeline systems. The modeling development will be targeted specifically towards formulations that can be used in transient optimization tools.


Optimization formulations for gas and electricity transmission with improved models, engineering economics, and resilience support

We will develop new formulations for gas-electricity system intra-day optimization that address realistic decision-making and exchange of information between gas pipeline and electric grid operators within timely decision cycles. These formulations will incorporate our advanced dynamic gas pipeline models to improve computation speed while guaranteeing accurate physical and economic solutions (location-dependent hourly gas prices). The developed optimization tools will provide a guideline of how human operators would manage coupled gas-electricity delivery networks under normal and anomalous conditions, if they were able to do so optimally. These tools will serve as a proxy for operator response to N-k contingencies in resilience analysis. The developed tools will address practical business processes of pipeline markets and operations and contribute to new standards for coordination with the electrical grid. Based on how optimization is used to price wholesale electricity for the power grid, we will advance our theory of gas pipeline engineering economics to guarantee pricing stability, fairness, and market adequacy. We will also formulate transient optimization problems that can be used for pricing intra-day gas delivery nominations. The analysis will serve as a model for price formation in the national gas market, and will be a prototype for optimization tools that could be used by pipeline system operators for pricing gas delivery in the future.


Real-time measurements for forecasting loads, state estimation, and mitigation of uncertainty

We will develop models for forecasting gas pipeline loads based on historical data, power grid activity, and weather forecasts. We will then extend our optimal control formulations to moving-horizon, model-predictive methods that use state estimation to re-adjust control setpoints using measurements of the system and look-ahead predictions. Based on our preliminary work, the new estimation schemes will jointly learn the pipeline flow and pressure state and tune parameters using the sparse, noisy time-series data available at instruments on real supervisory control and data acquisition (SCADA) systems of gas pipeline networks. We will derive error bounds on the learned estimates, and apply our work on monotone system theory and stochastic models of dynamic gas flows and pressures to modify our decision support tools to be robust to uncertainty. This will enable recourse for pipeline operators to optimally prepare for sudden changes in gas flows caused by activation of gas-fired generators over the (hour-ahead) short term and respond to more significant power system contingencies, thereby improving the overall resilience of the gas system to extreme conditions arising from events on the power grid. This project component addresses a gap in effective tools that was highlighted by our industry partners.

  1. “Resilient Coordination of Electricity and Natural Gas Transmission Operations” Energy Resources Engineering Seminar, Stanford University, January 28, 2019
  2. "Model Based Management of Natural Gas Pipeline Systems for Coordination with the Power Grid", Systems Engineering Seminar, Colorado State University, March 7, 2019
  3. “Pipeline Transient Optimization for a Gas-Electric Coordination Decision Support System”, PSIG Annual Meeting, London, May 15, 2019
  4. “Resilient Coordination of Electricity and Natural Gas Transmission Operations”, Invenia Labs, Cambridge, UK, May 20 2019
  5. “Modeling and Optimization of Intraday Interaction of Natural Gas Pipelines and the Power Grid”, Military Operations Research Society 87th Symposium, U.S. Air Force Academy, Colorado Springs, CO, June 19, 2019
  6. “Hydraulic Models for Transient Optimization and Estimation in Natural Gas Networks”, International Congress on Industrial and Applied Mathematics, Valencia, Spain, July 16, 2019
  7. “Resilient Coordination of Electricity and Natural Gas Transmission Operations”, Department of Electrical and Electronic Engineering, The University of Hong Kong, August 16, 2019
  8. “Dynamic State and Parameter Estimation for Natural Gas Networks using Real Pipeline System Data", 3rd IEEE Conf. on Control Tech. & Applications, Hong Kong, August 19, 2019
  9. "Fuel Reliability for Electric Energy Delivery by Optimized Management of Gas-pipeline Automation Systems" GMLC Presentations, Washington, DC, August 22, 2019
  10. “Pipeline Transient Optimization for A Gas-Electric Coordination Decision Support System,” INFORMS Annual Meeting, Seattle, WA, October 23, 2019
  11. “Optimal Control for Scheduling and Pricing Intra-day Natural Gas Transport on Pipeline Networks,” 58th IEEE Conference on Decision and Control, Nice, France, December 11, 2019
  1. Gas Reliability Analysis Integrated Library (GRAIL). Release date: 2018-05-02. Code ID: 18546. Public Repository
  2. jl. Release date: 2018-09-12. Code ID: LA-CC-13-108. Public Repository
  1. Line A. Roald, Kaarthik Sundar, Anatoly Zlotnik, Sidhant Misra, Göran Andersson. “An Uncertainty Management Framework for Integrated Gas-Electric Energy Systems.” in Proceedings of the IEEE (to appear). arXiv preprint arXiv:2006.14561
  2. Misra, Sidhant, Marc Vuffray, and Anatoly Zlotnik. “Monotonicity Properties of Physical Network Flows and Application to Robust Optimal Allocation.” In Proceedings of the IEEE (to appear), 2020.
  3. Khlebnikova, Elena, Anatoly Zlotnik, Kaarthik Sundar, Mary Ewers, Byron Tasseff, and Russell Bent. "Optimization of Liquid Pipeline Control for Economic and Efficient Operations." In SPE Europec featured at 82nd EAGE Conference and Exhibition. Society of Petroleum Engineers, 2020.
  4. Beylin, Aleksandr, Aleksandr Rudkevich, and Anatoly Zlotnik. “Fast Transient Optimization of Gas Pipelines by Analytic Transformation to Linear Programs.” In Proc. 2020 Annual Meeting of the Pipeline Simulation Interest Group.
  5. Carreno, Ignacio Losada, Anna Scaglione, Anatoly Zlotnik, Deepjyoti Deka, and Kaarthik Sundar. "An Adversarial Model for Attack Vector Vulnerability Analysis on Power and Gas Delivery Operations." In Proc. XXI Power Systems Computation Conference. arXiv preprint arXiv:1910.03662. 2020
  6. Zlotnik, Anatoly, Kaarthik Sundar, Aleksandr M. Rudkevich, Aleksandr Beylin, and Xindi Li. “Optimal Control for Scheduling and Pricing Intra-day Natural Gas Transport on Pipeline Networks.” In Proc. 58th IEEE Conference on Decision and Control, Nice, France. 2019.
  7. Sundar, Kaarthik and Anatoly Zlotnik. “Dynamic State and Parameter Estimation for Natural Gas Networks using Real Pipeline System Data“ In Proc. 3rd IEEE Conf. on Control Tech. & Applications, Hong Kong, 2019.
  8. Zlotnik, Anatoly, Kaarthik Sundar, Aleksandr M. Rudkevich, Richard Tabors, and Xindi Li. "Pipeline Transient Optimization for a Gas-Electric Coordination Decision Support System." In PSIG Annual Meeting. Pipeline Simulation Interest Group, 2019.
  9. Rudkevich, Aleksandr, Anatoly Zlotnik, Xindi Li, Pablo Ruiz, Aleksandr Beylin, John Goldis, Richard Tabors, and Russ Philbrick. "Evaluating Benefits of Rolling Horizon Model Predictive Control for Intraday Scheduling of a Natural Gas Pipeline Market." In Proceedings of the 52nd Hawaii International Conference on System Sciences. 2019.
  10. Mak, Terrence WK, Pascal Van Hentenryck, Anatoly Zlotnik, and Russell Bent. "Dynamic compressor optimization in natural gas pipeline systems." INFORMS Journal on Computing 31, no. 1 (2019): 40-65.
  11. Gyrya, Vitaliy, and Anatoly Zlotnik. "An explicit staggered-grid method for numerical simulation of large-scale natural gas pipeline networks." Applied Mathematical Modelling 65 (2019): 34-51.
  12. Zhao, Bining, Anatoly Zlotnik, Antonio J. Conejo, Ramteen Sioshansi, and Aleksandr M. Rudkevich. "Shadow price-based co-ordination of natural gas and electric power systems." IEEE Transactions on Power Systems 34, no. 3 (2018): 1942-1954.
  13. Sundar, Kaarthik and Anatoly Zlotnik, "State and Parameter Estimation for Natural Gas Pipeline Networks Using Transient State Data," in IEEE Transactions on Control Systems Technology, vol. 27, no. 5, pp. 2110-2124, Sept. 2019.
  14. Rudkevich, Aleksandr, Anatoly Zlotnik, Pablo Ruiz, Evgeniy Goldis, Aleksandr Beylin, Richard Hornby, Richard Tabors, Scott Backhaus, Michael Caramanis, and Russ Philbrick. "Market Based Intraday Coordination of Electric and Natural Gas System Operation." In Proceedings of the 51st Hawaii International Conference on System Sciences. 2018.
  15. Zlotnik, Anatoly, Aleksandr M. Rudkevich, Evgeniy Goldis, Pablo A. Ruiz, Michael Caramanis, Richard Carter, Scott Backhaus, Richard Tabors, Richard Hornby, and Daniel Baldwin. "Economic Optimization of Intra-Day Gas Pipeline Flow Schedules using Transient Flow Models." In PSIG Annual Meeting. Pipeline Simulation Interest Group, 2017.
  16. Rudkevich, Alex, and Anatoly Zlotnik. "Vocational Marginal Pricing of Natural Gas subject to Engineering Constraints." In Proceedings of the 50th Hawaii International Conference on System Sciences. 2017.
  17. Dyachenko, Sergey A., Anatoly Zlotnik, Alexander O. Korotkevich, and Michael Chertkov. "Operator splitting method for simulation of dynamic flows in natural gas pipeline networks." Physica D: Nonlinear Phenomena 361 (2017): 1-11.
  18. Zlotnik, A. V., A. M. Rudkevich, R. Carter, P. A. Ruiz, S. Backhaus, and J. Taft. "Grid architecture at the gas-electric interface." Los Alamos Natl. Lab., Santa Fe, NM, USA, Rep. LA-UR-17-23662 (2017).
  19. Wu, Fei, Harsha Nagarajan, Anatoly Zlotnik, Ramteen Sioshansi, and Aleksandr M. Rudkevich. "Adaptive convex relaxations for gas pipeline network optimization." In 2017 American Control Conference (ACC), pp. 4710-4716. IEEE, 2017.
  20. Zlotnik, Anatoly, Line Roald, Scott Backhaus, Michael Chertkov, and Göran Andersson. "Control policies for operational coordination of electric power and natural gas transmission systems." In 2016 American Control Conference (ACC), pp. 7478-7483. IEEE, 2016.
  21. Mak, Terrence WK, Pascal Van Hentenryck, Anatoly Zlotnik, Hassan Hijazi, and Russell Bent. "Efficient dynamic compressor optimization in natural gas transmission systems." In 2016 American Control Conference (ACC), pp. 7484-7491. IEEE, 2016.
  22. Zlotnik, Anatoly, Sidhant Misra, Marc Vuffray, and Michael Chertkov. "Monotonicity of actuated flows on dissipative transport networks." In 2016 European Control Conference (ECC), pp. 831-836. IEEE, 2016.
  23. Carter, Richard, Scott Backhaus, Alex Hollis, Anatoly Zlotnik, Michael Chertkov, Anthony Giacomoni, and Andrew Daniels. "Impact of Regulatory Change to Coordinate Gas Pipelines and Power Systems." In PSIG Annual Meeting. Pipeline Simulation Interest Group, 2016.
  24. Zlotnik, Anatoly, Michael Chertkov, Richard Carter, Alex Hollis, Andrew Daniels, and Scott Backhaus. "Using power grid schedules in dynamic optimization of gas pipelines." In PSIG Annual Meeting. Pipeline Simulation Interest Group, 2016.
  25. Zlotnik, Anatoly, Line Roald, Scott Backhaus, Michael Chertkov, and Göran Andersson. "Coordinated scheduling for interdependent electric power and natural gas infrastructures." IEEE Transactions on Power Systems 32, no. 1 (2016): 600-610.
  26. Zlotnik, Anatoly, Michael Chertkov, and Konstantin Turitsyn. “Assessing risk of gas shortage in coupled gas-electricity infrastructures.” In Proc. 49th Hawaii International Conference on System Sciences (HICSS), 2519-2527, Kauai, HI, 2016.
  27. Zlotnik, Anatoly, Michael Chertkov, and Scott Backhaus. “Optimal control of transient flow in natural gas networks.” In Proc. 54th IEEE Conference on Decision and Control, 4563 - 4570, Osaka, Japan, 2015.
  28. Zlotnik, Anatoly, Sergey Dyachenko, Scott Backhaus, and Michael Chertkov. “Model reduction and optimization of natural gas pipeline dynamics.” in Proc. ASME Dynamic Systems and Control Conference, V003T39A002, Columbus, OH, 2015.