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2020 – today
- 2023
[i122]Hamidreza Behjoo, Michael Chertkov:
Exact Fractional Inference via Re-Parametrization & Interpolation between Tree-Re-Weighted- and Belief Propagation- Algorithms. CoRR abs/2301.10369 (2023)- [i121]Michael Chertkov:
Universality and Control of Fat Tails. CoRR abs/2303.09635 (2023) - [i120]Robert Ferrando, Laurent Pagnier, Robert Mieth, Zhirui Liang, Yury Dvorkin, Daniel Bienstock, Michael Chertkov:
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study. CoRR abs/2304.00062 (2023) - [i119]Criston Hyett, Laurent Pagnier, Jean Alisse, Lilach Sabban, Igal Goldshtein, Michael Chertkov:
Control of Line Pack in Natural Gas System: Balancing Limited Resources under Uncertainty. CoRR abs/2304.01955 (2023) - 2022
- [j27]Laurent Pagnier
, Julian Fritzsch, Philippe Jacquod, Michael Chertkov:
Toward Model Reduction for Power System Transients With Physics-Informed PDE. IEEE Access 10: 65118-65125 (2022) - [i118]Laurent Pagnier, Robert Ferrando, Yury Dvorkin, Michael Chertkov:
Machine Learning for Electricity Market Clearing. CoRR abs/2205.11641 (2022) - [i117]Lucas Fuentes Valenzuela, Lindell Williams, Michael Chertkov:
Statistical Mechanics of Thermostatically Controlled Multi-Zone Buildings. CoRR abs/2208.13099 (2022) - 2021
- [j26]Andrei Afonin, Michael Chertkov:
Which Neural Network to Choose for Post-Fault Localization, Dynamic State Estimation, and Optimal Measurement Placement in Power Systems? Frontiers Big Data 4: 692493 (2021) - [i116]Nikolay Stulov, Michael Chertkov:
Neural Particle Image Velocimetry. CoRR abs/2101.11950 (2021) - [i115]Laurent Pagnier, Michael Chertkov:
Physics-Informed Graphical Neural Network for Parameter & State Estimations in Power Systems. CoRR abs/2102.06349 (2021) - [i114]Francesco Concetti, Michael Chertkov:
Message Passing Descent for Efficient Machine Learning. CoRR abs/2102.08110 (2021) - [i113]Laurent Pagnier, Michael Chertkov:
Embedding Power Flow into Machine Learning for Parameter and State Estimation. CoRR abs/2103.14251 (2021) - [i112]Andrei Afonin, Michael Chertkov:
Which Neural Network to Choose for Post-Fault Localization, Dynamic State Estimation and Optimal Measurement Placement in Power Systems? CoRR abs/2104.03115 (2021) - [i111]Mikhail Krechetov, Amir Mohammad Esmaieeli Sikaroudi, Alon Efrat, Valentin Polishchuk, Michael Chertkov:
Prediction and Prevention of Pandemics via Graphical Model Inference and Convex Programming. CoRR abs/2109.04517 (2021) - [i110]Michael Woodward, Yifeng Tian, Criston Hyett, Chris Fryer, Daniel Livescu, Mikhail Stepanov, Michael Chertkov:
Physics Informed Machine Learning of SPH: Machine Learning Lagrangian Turbulence. CoRR abs/2110.13311 (2021) - [i109]Laurent Pagnier, Michael Chertkov, Julian Fritzsch, Philippe Jacquod:
Model Reduction of Swing Equations with Physics Informed PDE. CoRR abs/2110.14066 (2021) - 2020
- [j25]Saurav Talukdar, Deepjyoti Deka, Harish Doddi, Donatello Materassi, Michael Chertkov, Murti V. Salapaka:
Physics informed topology learning in networks of linear dynamical systems. Autom. 112 (2020) - [j24]Michael Chertkov, Göran Andersson:
Multienergy Systems. Proc. IEEE 108(9): 1387-1391 (2020) - [j23]Ali Hassan, Samrat Acharya, Michael Chertkov, Deepjyoti Deka, Yury Dvorkin:
A Hierarchical Approach to Multienergy Demand Response: From Electricity to Multienergy Applications. Proc. IEEE 108(9): 1457-1474 (2020) - [j22]Nikolay N. Novitsky, Zoya I. Shalaginova, Aleksandr A. Alekseev, Vyacheslav V. Tokarev, Oksana A. Grebneva, Aleksandr V. Lutsenko, Olga V. Vanteeva, Egor A. Mikhailovsky, Roman Pop, Petr Vorobev, Michael Chertkov:
Smarter Smart District Heating. Proc. IEEE 108(9): 1596-1611 (2020) - [j21]Deepjyoti Deka, Michael Chertkov, Scott Backhaus:
Joint Estimation of Topology and Injection Statistics in Distribution Grids With Missing Nodes. IEEE Trans. Control. Netw. Syst. 7(3): 1391-1403 (2020) - [j20]Sejun Park, Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Learning With End-Users in Distribution Grids: Topology and Parameter Estimation. IEEE Trans. Control. Netw. Syst. 7(3): 1428-1440 (2020) - [j19]Deepjyoti Deka, Saurav Talukdar, Michael Chertkov, Murti V. Salapaka:
Graphical Models in Meshed Distribution Grids: Topology Estimation, Change Detection & Limitations. IEEE Trans. Smart Grid 11(5): 4299-4310 (2020) - [i108]Ali Hassan, Deepjyoti Deka, Michael Chertkov, Yury Dvorkin:
Data-Driven Learning and Load Ensemble Control. CoRR abs/2004.09675 (2020) - [i107]Ali Hassan, Samrat Acharya, Michael Chertkov, Deepjyoti Deka, Yury Dvorkin:
A Hierarchical Approach to Multi-Energy Demand Response: From Electricity to Multi-Energy Applications. CoRR abs/2005.02339 (2020) - [i106]Ilia Luchnikov, David Métivier, Henni Ouerdane, Michael Chertkov:
Super-relaxation of space-time-quantized ensemble of energy loads. CoRR abs/2008.03118 (2020)
2010 – 2019
- 2019
- [j18]Michael Chertkov, Mihailo R. Jovanovic, Bernard C. Lesieutre, Steven H. Low, Pascal Van Hentenryck, Louis Wehenkel:
Guest Editorial Special Issue on Analysis, Control, and Optimization of Energy Networks. IEEE Trans. Control. Netw. Syst. 6(3): 922-924 (2019) - [j17]Vladimir Y. Frolov, Priyanko Guha Thakurta, Scott Backhaus, Janusz W. Bialek, Michael Chertkov:
Operations- and Uncertainty-Aware Installation of FACTS Devices in a Large Transmission System. IEEE Trans. Control. Netw. Syst. 6(3): 961-970 (2019) - [j16]Ali Hassan, Robert Mieth, Michael Chertkov, Deepjyoti Deka, Yury Dvorkin:
Optimal Load Ensemble Control in Chance-Constrained Optimal Power Flow. IEEE Trans. Smart Grid 10(5): 5186-5195 (2019) - [c59]Valerii Likhosherstov, Yury Maximov, Misha Chertkov:
Inference and Sampling of $K_33$-free Ising Models. ICML 2019: 3963-3972 - [c58]Yize Chen, Md Umar Hashmi, Deepjyoti Deka, Michael Chertkov:
Stochastic Battery Operations using Deep Neural Networks. ISGT 2019: 1-5 - [i105]Nikolay Stulov, Dejan J. Sobajic, Yury Maximov, Deepjyoti Deka, Michael Chertkov:
Learning a Generator Model from Terminal Bus Data. CoRR abs/1901.00781 (2019) - [i104]Roman Pop, Ali Hassan, Kenneth Bruninx, Michael Chertkov, Yury Dvorkin:
A Markov Process Approach to Ensemble Control of Smart Buildings. CoRR abs/1902.06866 (2019) - [i103]Deepjyoti Deka, Saurav Talukdar, Michael Chertkov, Murti V. Salapaka:
Graphical Models in Loopy Distribution Grids: Topology estimation, change detection and limitation. CoRR abs/1905.06550 (2019) - [i102]Valerii Likhosherstov, Yury Maximov, Michael Chertkov:
A New Family of Tractable Ising Models. CoRR abs/1906.06431 (2019) - [i101]Valerii Likhosherstov, Yury Maximov, Michael Chertkov:
Tractable Minor-free Generalization of Planar Zero-field Ising Models. CoRR abs/1910.11142 (2019) - 2018
- [j15]Colin Grudzien, Deepjyoti Deka, Michael Chertkov, Scott N. Backhaus:
Structure- and Physics-Preserving Reductions of Power Grid Models. Multiscale Model. Simul. 16(4): 1916-1947 (2018) - [j14]Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Structure Learning in Power Distribution Networks. IEEE Trans. Control. Netw. Syst. 5(3): 1061-1074 (2018) - [j13]Sungsoo Ahn, Michael Chertkov, Andrew E. Gelfand, Sejun Park, Jinwoo Shin:
Maximum Weight Matching Using Odd-Sized Cycles: Max-Product Belief Propagation and Half-Integrality. IEEE Trans. Inf. Theory 64(3): 1471-1480 (2018) - [c57]Sejun Park, Deepjyoti Deka, Michael Chertkov:
Learning in Power Distribution Grids under Correlated Injections. ACSSC 2018: 1863-1868 - [c56]Sungsoo Ahn, Michael Chertkov, Jinwoo Shin, Adrian Weller:
Gauged Mini-Bucket Elimination for Approximate Inference. AISTATS 2018: 10-19 - [c55]Saurav Talukdar, Deepjyoti Deka, Michael Chertkov, Murti V. Salapaka:
Topology Learning of Radial Dynamical Systems with Latent Nodes. ACC 2018: 1096-1101 - [c54]Andrii Riazanov, Yury Maximov, Michael Chertkov:
Belief Propagation Min-Sum Algorithm for Generalized Min-Cost Network Flow. ACC 2018: 6108-6113 - [c53]Andrey Y. Lokhov, Deepjyoti Deka, Marc Vuffray, Michael Chertkov:
Uncovering Power Transmission Dynamic Model from Incomplete PMU Observations. CDC 2018: 4008-4013 - [c52]Sungsoo Ahn, Michael Chertkov, Adrian Weller, Jinwoo Shin:
Bucket Renormalization for Approximate Inference. ICML 2018: 109-118 - [i100]Saurav Talukdar, Deepjyoti Deka, Michael Chertkov, Murti V. Salapaka:
Topology Learning of Radial Dynamical Systems with Latent Nodes. CoRR abs/1803.02793 (2018) - [i99]Sejun Park, Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Learning with End-Users in Distribution Grids: Topology and Parameter Estimation. CoRR abs/1803.04812 (2018) - [i98]Deepjyoti Deka, Michael Chertkov, Scott Backhaus:
Topology Estimation using Graphical Models in Multi-Phase Power Distribution Grids. CoRR abs/1803.06531 (2018) - [i97]Deepjyoti Deka, Michael Chertkov, Scott Backhaus:
Joint Estimation of Topology \& Injection Statistics in Distribution Grids with Missing Nodes. CoRR abs/1804.04742 (2018) - [i96]Ali Hassan, Robert Mieth, Michael Chertkov, Deepjyoti Deka, Yury Dvorkin:
Optimal Load Ensemble Control in Chance-Constrained Optimal Power Flow. CoRR abs/1805.09116 (2018) - [i95]David Métivier, Ilia Luchnikov, Michael Chertkov:
Power of Ensemble Diversity and Randomization for Energy Aggregation. CoRR abs/1808.09555 (2018) - [i94]Saurav Talukdar, Deepjyoti Deka, Harish Doddi, Donatello Materassi, Misha Chertkov, Murti V. Salapaka:
Physics Informed Topology Learning in Networks of Linear Dynamical Systems. CoRR abs/1809.10535 (2018) - [i93]David Métivier, Michael Chertkov:
Mean Field Control for Efficient Mixing of Energy Loads. CoRR abs/1810.00450 (2018) - [i92]Wenting Li, Deepjyoti Deka, Michael Chertkov, Meng Wang:
Real-time Fault Localization in Power Grids With Convolutional Neural Networks. CoRR abs/1810.05247 (2018) - [i91]Ryan King, Oliver Hennigh, Arvind Mohan, Michael Chertkov:
From Deep to Physics-Informed Learning of Turbulence: Diagnostics. CoRR abs/1810.07785 (2018) - [i90]Michael Chertkov, Yury Maximov:
Gauges, Loops, and Polynomials for Partition Functions of Graphical Models. CoRR abs/1811.04713 (2018) - [i89]Valerii Likhosherstov, Yury Maximov, Michael Chertkov:
Inference and Sampling of K33-free Ising Models. CoRR abs/1812.09587 (2018) - 2017
- [j12]Krishnamurthy Dvijotham, Michael Chertkov, Pascal Van Hentenryck, Marc Vuffray, Sidhant Misra:
Graphical models for optimal power flow. Constraints An Int. J. 22(1): 24-49 (2017) - [c51]Michael Chertkov, Yury Dvorkin:
Chance constrained optimal power flow with primary frequency response. CDC 2017: 4484-4489 - [c50]Michael Chertkov, Alexander Korotkevich:
Adiabatic approach for natural gas pipeline computations. CDC 2017: 5634-5639 - [c49]Saurav Talukdar, Deepjyoti Deka, Blake Lundstrom, Michael Chertkov, Murti V. Salapaka:
Learning Exact Topology of a Loopy Power Grid from Ambient Dynamics. e-Energy 2017: 222-227 - [c48]Deepjyoti Deka, Armin Zare, Andrey Y. Lokhov, Mihailo R. Jovanovic, Michael Chertkov:
State and noise covariance estimation in power grids using limited nodal PMUs. GlobalSIP 2017: 1075-1079 - [c47]Sungsoo Ahn, Michael Chertkov, Jinwoo Shin:
Gauging Variational Inference. NIPS 2017: 2881-2890 - [c46]Deepjyoti Deka, Michael Chertkov, Scott Backhaus:
Estimating topology and injection statistics in distribution grids with hidden nodes. SmartGridComm 2017: 71-76 - [c45]Emma M. Stewart, Philip Top, Michael Chertkov, Deepjyoti Deka, Scott Backhaus, Andrey Y. Lokhov, Ciaran M. Roberts, Val Hendrix, Sean Peisert, Anthony Florita, Thomas J. King, Matthew J. Reno:
Integrated multi-scale data analytics and machine learning for the distribution grid. SmartGridComm 2017: 423-429 - [i88]Michael Chertkov, Vladimir Y. Chernyak:
Ensemble of Thermostatically Controlled Loads: Statistical Physics Approach. CoRR abs/1701.04939 (2017) - [i87]Michael Chertkov, Vladimir Y. Chernyak:
Ensemble Control of Cycling Energy Loads: Markov Decision Approach. CoRR abs/1701.04941 (2017) - [i86]Michael Chertkov, Sidhant Misra, Marc Vuffray, Dvijotham Krishnamurty, Pascal Van Hentenryck:
Graphical Models and Belief Propagation-hierarchy for Optimal Physics-Constrained Network Flows. CoRR abs/1702.01890 (2017) - [i85]Michael Chertkov, Nikolai N. Novitsky:
Thermal Transients in District Heating Systems. CoRR abs/1702.07634 (2017) - [i84]Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov, Michael Chertkov:
Towards Optimal Sparse Inverse Covariance Selection through Non-Convex Optimization. CoRR abs/1703.04886 (2017) - [i83]Michael Chertkov, Alexander Korotkevich:
Adiabatic approach for natural gas pipeline computations. CoRR abs/1706.00523 (2017) - [i82]Deepjyoti Deka, Saurav Talukdar, Michael Chertkov, Murti V. Salapaka:
Topology Estimation in Bulk Power Grids: Guarantees on Exact Recovery. CoRR abs/1707.01596 (2017) - [i81]Colin Grudzien, Deepjyoti Deka, Michael Chertkov, Scott Backhaus:
Structure- & Physics- Preserving Reductions of Power Grid Models. CoRR abs/1707.03672 (2017) - [i80]Vladimir A. Frolov, Michael Chertkov:
Methodology for Multi-stage, Operations- and Uncertainty-Aware Placement and Sizing of FACTS Devices in a Large Power Transmission System. CoRR abs/1707.03686 (2017) - [i79]Art B. Owen, Yury Maximov, Michael Chertkov:
Importance sampling the union of rare events with an application to power systems analysis. CoRR abs/1710.06965 (2017) - [i78]Andrii Riazanov, Yury Maximov, Michael Chertkov:
Belief Propagation Min-Sum Algorithm for Generalized Min-Cost Network Flow. CoRR abs/1710.07600 (2017) - [i77]Ali Hassan, Yury Dvorkin, Deepjyoti Deka, Michael Chertkov:
Chance-Constrained ADMM Approach for Decentralized Control of Distributed Energy Resources. CoRR abs/1710.09738 (2017) - [i76]Michael Chertkov, Deepjyoti Deka, Yury Dvorkin:
Optimal Ensemble Control of Loads in Distribution Grids with Network Constraints. CoRR abs/1710.09924 (2017) - [i75]Andrey Y. Lokhov, Marc Vuffray, Dmitry Shemetov, Deepjyoti Deka, Michael Chertkov:
Online Learning of Power Transmission Dynamics. CoRR abs/1710.10021 (2017) - [i74]Sejun Park, Deepjyoti Deka, Michael Chertkov:
Exact Topology and Parameter Estimation in Distribution Grids with Minimal Observability. CoRR abs/1710.10727 (2017) - 2016
- [j11]Jason K. Johnson, Diane Oyen, Michael Chertkov, Praneeth Netrapalli:
Learning Planar Ising Models. J. Mach. Learn. Res. 17: 215:1-215:26 (2016) - [c44]Krishnamurthy Dvijotham, Michael Chertkov, Steven H. Low:
Monotone operator approach to power flow solutions. ACC 2016: 1769 - [c43]Anatoly Zlotnik, Line Roald, Scott Backhaus, Michael Chertkov, Göran Andersson:
Control policies for operational coordination of electric power and natural gas transmission systems. ACC 2016: 7478-7483 - [c42]Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Tractable structure learning in radial physical flow networks. CDC 2016: 6631-6638 - [c41]Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Learning topology of the power distribution grid with and without missing data. ECC 2016: 313-320 - [c40]Anatoly Zlotnik, Sidhant Misra, Marc Vuffray, Michael Chertkov:
Monotonicity of actuated flows on dissipative transport networks. ECC 2016: 831-836 - [c39]Anatoly Zlotnik, Michael Chertkov, Konstantin S. Turitsyn:
Assessing Risk of Gas Shortage in Coupled Gas-Electricity Infrastructures. HICSS 2016: 2519-2527 - [c38]Sungsoo Ahn, Michael Chertkov, Jinwoo Shin:
Synthesis of MCMC and Belief Propagation. NIPS 2016: 1453-1461 - [c37]Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov, Michael Chertkov:
Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models. NIPS 2016: 2595-2603 - [c36]Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Estimating distribution grid topologies: A graphical learning based approach. PSCC 2016: 1-7 - [c35]Line Roald, Göran Andersson, Sidhant Misra, Michael Chertkov, Scott Backhaus:
Optimal power flow with wind power control and limited expected risk of overloads. PSCC 2016: 1-7 - [c34]Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Learning topology of distribution grids using only terminal node measurements. SmartGridComm 2016: 205-211 - [i73]Line Roald, Sidhant Misra, Michael Chertkov, Scott Backhaus, Göran Andersson:
Chance Constrained Optimal Power Flow with Curtailment and Reserves from Wind Power Plants. CoRR abs/1601.04321 (2016) - [i72]Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Estimating Distribution Grid Topologies: A Graphical Learning based Approach. CoRR abs/1602.08509 (2016) - [i71]Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Learning Topology of the Power Distribution Grid with and without Missing Data. CoRR abs/1603.01650 (2016) - [i70]Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov, Michael Chertkov:
Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models. CoRR abs/1605.07252 (2016) - [i69]Sungsoo Ahn, Michael Chertkov, Jinwoo Shin:
MCMC assisted by Belief Propagaion. CoRR abs/1605.09042 (2016) - [i68]Krishnamurthy Dvijotham, Pascal Van Hentenryck, Michael Chertkov, Sidhant Misra, Marc Vuffray:
Graphical Models for Optimal Power Flow. CoRR abs/1606.06512 (2016) - [i67]Vladimir A. Frolov, Priyanko Guha Thakurta, Scott Backhaus, Janusz W. Bialek, Michael Chertkov:
Optimal Placement and Sizing of FACTS Devices to Delay Transmission Expansion. CoRR abs/1608.04467 (2016) - [i66]Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Learning Topology of Distribution Grids using only Terminal Node Measurements. CoRR abs/1608.05031 (2016) - [i65]Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Tractable Structure Learning in Radial Physical Flow Networks. CoRR abs/1608.05064 (2016) - [i64]Andrey Y. Lokhov, Marc Vuffray, Sidhant Misra, Michael Chertkov:
Optimal structure and parameter learning of Ising models. CoRR abs/1612.05024 (2016) - 2015
- [j10]Sidhant Misra, Michael W. Fisher, Scott Backhaus, Russell Bent, Michael Chertkov, Feng Pan:
Optimal Compression in Natural Gas Networks: A Geometric Programming Approach. IEEE Trans. Control. Netw. Syst. 2(1): 47-56 (2015) - [c33]Krishnamurthy Dvijotham, Michael Chertkov:
Convexity of structure preserving energy functions in power transmission: Novel results and applications. ACC 2015: 5035-5042 - [c32]Krishnamurthy Dvijotham, Michael Chertkov, Steven H. Low:
A differential analysis of the power flow equations. CDC 2015: 23-30 - [c31]Anatoly Zlotnik, Michael Chertkov, Scott Backhaus:
Optimal control of transient flow in natural gas networks. CDC 2015: 4563-4570 - [c30]Marc Vuffray, Sidhant Misra, Michael Chertkov:
Monotonicity of dissipative flow networks renders robust maximum profit problem tractable: General analysis and application to natural gas flows. CDC 2015: 4571-4578 - [c29]Line Roald, Sidhant Misra, Michael Chertkov, Göran Andersson:
Optimal Power Flow with Weighted chance constraints and general policies for generation control. CDC 2015: 6927-6933 - [c28]Changhong Zhao, Michael Chertkov, Scott Backhaus:
Optimal Sizing of Voltage Control Devices for Distribution Circuit with Intermittent Load. HICSS 2015: 2680-2689 - [c27]Michael Chertkov, Michael W. Fisher, Scott Backhaus, Russell Bent, Sidhant Misra:
Pressure Fluctuations in Natural Gas Networks Caused by Gas-Electric Coupling. HICSS 2015: 2738-2747 - [c26]Sungsoo Ahn, Sejun Park, Michael Chertkov, Jinwoo Shin:
Minimum Weight Perfect Matching via Blossom Belief Propagation. NIPS 2015: 1288-1296 - [i63]Deepjyoti Deka, Scott Backhaus, Michael Chertkov:
Structure Learning in Power Distribution Networks. CoRR abs/1501.04131 (2015) - [i62]Line Roald, Sidhant Misra, Michael Chertkov, Göran Andersson:
Optimal Power Flow with Weighted Chance Constraints and General Policies for Generation Control. CoRR abs/1504.00057 (2015) - [i61]Krishnamurthy Dvijotham, Marc Vuffray, Sidhant Misra, Michael Chertkov:
Natural Gas Flow Solutions with Guarantees: A Monotone Operator Theory Approach. CoRR abs/1506.06075 (2015) - [i60]Krishnamurthy Dvijotham, Steven H. Low, Michael Chertkov:
Solving the Power Flow Equations: A Monotone Operator Approach. CoRR abs/1506.08472 (2015) - [i59]Krishnamurthy Dvijotham, Michael Chertkov, Steven H. Low:
Solving the Power Flow Equations: A Monotone Operator Theory Approach. CoRR abs/1506.08814 (2015) - [i58]Misha Chertkov, Michael W. Fisher, Scott Backhaus, Russell Bent, Sidhant Misra:
Pressure Fluctuations in Natural Gas Networks caused by Gas-Electric Coupling. CoRR abs/1507.06601 (2015) - [i57]Sungsoo Ahn, Sejun Park, Michael Chertkov, Jinwoo Shin:
Minimum Weight Perfect Matching via Blossom Belief Propagation. CoRR abs/1509.06849 (2015) - 2014
- [j9]Daniel Bienstock, Michael Chertkov, Sean Harnett:
Chance-Constrained Optimal Power Flow: Risk-Aware Network Control under Uncertainty. SIAM Rev. 56(3): 461-495 (2014) - [c25]Krishnamurthy Dvijotham, Misha Chertkov, Scott Backhaus:
Storage Sizing and Placement through Operational and Uncertainty-Aware Simulations. HICSS 2014: 2408-2416 - [i56]