Journal and Preprints

  1. W. Cui, Y. Jiang, B. Zhang, and Y. Shi, “Structured Neural-PI Control for Networked Systems: Stability and Steady-State Optimality Guarantees,” arXiv preprint arXiv:2206.00261, 2022.
  2. S. Taheri, V. Kekatos, H. Veeramachaneni, and B. Zhang, “Data-Driven Modeling of Aggregate Flexibility under Uncertain and Non-Convex Load Models,” To Appear in IEEE Transaction on Smartgrid, 2022.
  3. S. Deng, L. Chen, B. Zhang, W. Yuan, and S. Mei, “Distributed Secondary Frequency Control and Optimal Power Sharing in Microgrids,” Submitted to IEEE PES Transactions on Energy Conversion, 2022.
  4. W. Cui, W. Yang, and B. Zhang, “Predicting Power System Dynamics and Transients: A Frequency Domain Approach,” Submitted to IEEE Transaction on Power Systems, 2022.
  5. W. Cui and B. Zhang, “Equilibrium-Independent Stability Analysis for Distribution Systems with Lossy Transmission Lines,” To Appear in IEEE Control Systems Letters, 2022.
  6. Y. Jiang, W. Cui, B. Zhang, and J. Cortés, “Stable Reinforcement Learning for Optimal Frequency Control: A Distributed Averaging-Based Integral Approach,” Submitted to IEEE Open Journal of Control Systems, 2022.
  7. H. Li, Y. Qiao, Z. Lu, and B. Zhang, “Power System Transition with Multiple Flexibility Resources: A Data-Driven Approach,” Sustainability, vol. 14, no. 5, 2022.
  8. Y. Chen, L. Zhang, and B. Zhang, “Learning to Solve DCOPF: A Duality Approach,” Electric Power Systems Research, 2022.
  9. W. Cui, J. Li, and B. Zhang, “Decentralized Safe Reinforcement Learning for Inverter-Based Voltage Control,” Electric Power Systems Research, 2022.
  10. W. Cui, Y. Jiang, and B. Zhang, “Reinforcement Learning for Optimal Frequency Control: A Lyapunov Approach,” To Appear in IEEE Transaction on Power Systems, 2022.
  11. K. Guddanti, Y. Weng, and B. Zhang, “A Matrix-Inversion-Free Fixed-Point Method for Distributed Power Flow Analysis,” IEEE Transactions on Power Systems, vol. 37, no. 1, pp. 653–665, 2022.
  12. A. Ademola-Idowu and B. Zhang, “Frequency Stability Using MPC-Based Inverter Power Control in Low-Inertia Power Systems,” IEEE Transactions on Power Systems, vol. 36, no. 2, pp. 1628–1637, 2021.
  13. N. Costilla-Enriquez, Y. Weng, and B. Zhang, “Combining Newton-Raphson and Stochastic Gradient Descent for Power Flow Analysis,” IEEE Transactions on Power Systems, vol. 36, no. 1, pp. 514–517, 2021.
  14. L. Zhang, Y. Chen, and B. Zhang, “A Convex Neural Network Solver for DCOPF with Generalization Guarantees,” IEEE Transactions on Control of Networked Systems, 2021.
  15. H. Li, Y. Qiao, Z. Lu, B. Zhang, and F. Teng, “Frequency Constrained Stochastic Planning Towards a High Renewable Target Considering Frequency Response Support from Wind Power,” IEEE Transactions on Power Systems, vol. 36, no. 5, pp. 4632–4644, 2021.
  16. L. Zhang and B. Zhang, “An Iterative Approach to Improving Solution Quality for AC Optimal Power Flow Problems,” Submitted to IEEE Transactions on Power Systems, 2021.
  17. H. Li, Y. Qiao, B. Zhang, Z. Lu, and L. Dong, “A two-step tie-line scheduling method considering variable renewable energy variations,” International Transactions on Electrical Energy Systems, 2021.
  18. W. Cui and B. Zhang, “Lyapunov-Regularized Reinforcement Learning for Power System Transient Stability,” IEEE Control Systems Letters, 2021.
  19. H. Li, Z. Lu, Y. Qiao, B. Zhang, and Y. Lin, “The Flexibility Test System for Studies of Variable Renewable Energy Resources,” IEEE Transactions on Power Systems, vol. 36, no. 2, pp. 1526–1536, 2021.
  20. S. Sekar, L. Zheng, L. J. Ratliff, and B. Zhang, “Uncertainty in Multicommodity Routing Networks: When Does It Help?,” IEEE Transactions on Automatic Control, vol. 65, no. 11, pp. 4600–4615, 2020.
  21. Y. Weng, R. Rajagopal, and B. Zhang, “A Geometric Analysis of Power System Loadability Regions,” IEEE Transactions on Smart Grid, vol. 11, no. 4, pp. 3580–3592, 2020.
  22. J. E. Contreras-Ocaña, Y. Chen, U. Siddiqi, and B. Zhang, “Non-Wire Alternatives: An Additional Value Stream for Distributed Energy Resources,” IEEE Transactions on Sustainable Energy, vol. 11, no. 3, pp. 1287–1299, 2020.
  23. P. Li, S. Sekar, and B. Zhang, “A Capacity-Price Game for Uncertain Renewables Resources,” IEEE Transactions on Sustainable Computing, 2020.
  24. L. Zhang and B. Zhang, “Scenario Forecasting of Residential Load Profiles,” IEEE Journal on Selected Areas in Communications, Special Issue on Communications and Data Analytics in Smart Grid, vol. 38, no. 1, pp. 84–95, 2020.
  25. Y. Cheng, N. Zhang, B. Zhang, C. Kang, W. Xi, and M. Feng, “Low-Carbon Operation of Multiple Energy Systems Based on Energy-Carbon Integrated Prices,” IEEE Transactions on Smart Grid, vol. 11, no. 2, pp. 1307–1318, 2020.
  26. Y. Yang, Z. Yang, J. Yu, and B. Zhang, “Fast Calculation of Probabilistic Power Flow: A Model-Based Deep Learning Approach,” IEEE Transactions on Smart Grid, vol. 11, no. 3, pp. 2235–2244, 2020.
  27. Y. Chen and B. Zhang, “Learning to Solve Network Flow Problems via Neural Decoding,” submitted to Electric Power Systems Research, 2020.
  28. Y. Chen, Y. Shi, and B. Zhang, “Data-Driven Optimal Voltage Regulation Using Input Convex Neural Networks,” Electric Power Systems Research, vol. 189, 2020.
  29. Q. He, Y. Yang, and B. Zhang, “Smart Energy Storage Management via Information Systems Design,” Energy Economics, vol. 85, p. 104542, 2020.
  30. P. Li, B. Jin, D. Wang, and B. Zhang, “Distribution System Voltage Control under Uncertainties using Tractable Chance Constraints,” IEEE Transactions on Power Systems, vol. 34, no. 6, pp. 5208–5216, 2019.
  31. C. Tang, J. Xu, Y. Tan, Y. Sun, and B. Zhang, “Lagrangian Relaxation with Incremental Proximal Method for Economic Dispatch with Large Numbers of Wind Power Scenarios,” IEEE Transactions on Power Systems, vol. 34, no. 4, pp. 2685–2695, 2019.
  32. B. Zhang, R. Johari, and R. Rajagopal, “Cournot Games with Uncertainty: Coalitions, Competition, and Efficiency,” IEEE Transaction on Control of Networked Systems, vol. 6, no. 2, pp. 884–896, 2019.
  33. J. E. Contreras-Ocaña, M. A. Ortega-Vazquez, and B. Zhang, “Participation of an Energy Storage Aggregator in Electricity Markets,” IEEE Transactions on Smargrid, vol. 10, no. 2, pp. 1171–1183, 2019.
  34. P. Li, H. Wang, and B. Zhang, “A Distributed Online Pricing Strategy for Demand Response Programs,” IEEE Transactions on Smartgrid, vol. 10, no. 1, pp. 350–360, 2019.
  35. Y. Shi, B. Xu, Y. Tan, and B. Zhang, “Optimal Battery Control Under Cycle Aging Mechanisms,” IEEE Transactions on Automatic Control, vol. 64, no. 6, pp. 2324–2339, 2019.
  36. A. Jaech, B. Zhang, M. Ostendorf, and D. S. Kirschen, “Real-Time Prediction of the Duration of Distribution System Outages,” IEEE Transactions on Power Systems, vol. 34, no. 1, pp. 773–781, 2019.
  37. J. E. Contreras-Ocana, M. A. Ortega-Vazquez, D. Kirschen, and B. Zhang, “Tractable and Robust Modeling of Building Flexibility Using Coarse Data,” IEEE Transactions on Power Systems, vol. 33, no. 5, pp. 5456–5468, 2018.
  38. Y. Shi, B. Xu, D. Wang, and B. Zhang, “Using Battery Storage for Peak Shaving and Frequency Regulation: Joint Optimization for Superlinear Gains,” IEEE Transaction on Power Systems, vol. 33, no. 3, pp. 2882–2894, 2018.
  39. C. P. Dowling, L. J. Ratliff, and B. Zhang, “Modeling Curbside Parking as a Network of Finite Capacity Queues,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 3, pp. 1011–1022, 2018.
  40. C. Tang, Y. Wang, J. Xu, Y. Sun, and B. Zhang, “Efficient Scenario Generation of Multiple Renewable Power Plants Considering Spatial and Temporal Correlations,” Applied Energy, vol. 221, pp. 348–357, 2018.
  41. Y. Chen, Y. Wang, D. Kirschen, and B. Zhang, “Model-Free Renewables Scenario Generation Using Generative Adversarial Networks,” IEEE Transaction on Power Systems, vol. 33, no. 3, pp. 3265–3275, 2018.
  42. Z. Wang, D. Kirschen, and B. Zhang, “Accurate Semidefinite Programming Models for Optimal Power Flow in Distribution Systems,” Submitted to IEEE Transactions on Power Systems, 2018.
  43. R. Pamula, X. Sun, S. Kim, F. ur Rahman, B. Zhang, and V. S. Sathe, “A 65nm CMOS 3.2-to-86 Mbps 2.58 pJ/b Highly Digital True Random-Number Generator with Integrated De-correlation and Bias Correction,” IEEE Solid-State Circuits Letters, vol. 1, no. 12, pp. 237–240, 2018.
  44. B. Xu, Y. Shi, D. S. Kirschen, and B. Zhang, “Optimal Battery Participation in Frequency Regulation Markets,” IEEE Transactions on Power Systems, vol. 33, no. 6, pp. 6715–6725, 2018.
  45. N. Mazzi, B. Zhang, and D. S. Kirschen, “An Online Optimization Algorithm for Alleviating Contingencies in Transmission Networks,” IEEE Transactions on Power Systems, vol. 33, no. 5, pp. 5572–5582, 2018.
  46. C. Dowling, T. Fiez, L. Ratliff, and B. Zhang, “How much urban traffic is searching for parking,” arXiv preprint arXiv:1702.06156, 2017.
  47. P. Li, B. Zhang, Y. Weng, and R. Rajagopal, “A Sparse Linear Model and Significance Test for Individual Consumption Prediction,” IEEE Transactions on Power Systems, vol. 32, no. 6, pp. 4489–4500, 2017.
  48. B. Zhang, R. Johari, and R. Rajagopal, “Competition and Coalition Formation of Renewable Power Producers,” IEEE Transactions on Power Systems, vol. 30, no. 3, pp. 1624–1632, May 2015.
  49. B. Zhang, A. Lam, A. D. Dominguez-Garcia, and D. Tse, “An optimal and distributed method for voltage regulation in power distribution systems,” Power Systems, IEEE Transactions on, vol. 30, no. 4, pp. 1714–1726, 2015.
  50. B. Zhang, R. Rajagopal, and D. Tse, “Network Risk Limiting Dispatch: Optimal Control and Price of Uncertainty,” IEEE Transactions on Automatic Control, vol. 59, no. 9, pp. 2442–2456, Sep. 2014.
  51. J. Lavaei, D. Tse, and B. Zhang, “Geometry of power flows and optimization in distribution networks,” IEEE Transactions on Power Systems, vol. 29, no. 2, pp. 572–583, 2014.
  52. B. Zhang and D. Tse, “Geometry of injection regions of power networks,” IEEE Transactions on Power Systems, vol. 28, no. 2, pp. 788–797, 2013.
  53. S. B. Kuntze, B. Zhang, L. Pavel, and J. S. Aitchison, “Impact of Feedback Delay on Closed-Loop Stability in Semiconductor Optical Amplifier Control Circuits,” Journal of Lightwave Technology, vol. 27, no. 9, pp. 1095–1107, May 2009.

Conference Proceedings

  1. D. Tabas and B. Zhang, “Computationally Efficient Safe Reinforcement Learning for Power Systems,” in American Control Conference (ACC), 2022.
  2. L. Zhang and B. Zhang, “An Iterative Approach to Improving Solution Quality for AC Optimal Power Flow Problems,” in ACM E-Energy, 2022.
  3. Y. Chan, L. Zhang, and B. Zhang, “Learning to Solve DCOPF: A Duality Approach,” in Power Systems Computation Conference (PSCC), 2022.
  4. Y. Chen and B. Zhang, “State-of-Charge Aware EV Charging,” in Power and Energy Society General Meeting, 2022.
  5. W. Cui, J. Li, and B. Zhang, “Decentralized Safe Reinforcement Learning for Voltage Control,” in Power Systems Computation Conference (PSCC), 2022.
  6. L. Zheng, Y. Shi, L. Ratliff, and B. Zhang, “Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks,” in Learning for Dynamics & Control Conference, 2021.
  7. W. Cui and B. Zhang, “Reinforcement Learning for Optimal Frequency Control: A Lyapunov Approach,” in ICML 2021 Workshop on Tackling Climate Change with Machine Learning, 2021.
  8. D. Tabas and B. Zhang, “A Set-Theoretic Approach to Safe Reinforcement Learning in Power Systems,” in ICML 2021 Workshop on Tackling Climate Change with Machine Learning, 2021.
  9. L. Zhang and B. Zhang, “An Iterative Approach to Finding Global Solutions of AC Optimal Power Flow Problems,” in ICML 2021 Workshop on Tackling Climate Change with Machine Learning, 2021.
  10. B. Zhang and E. Nasr, “Distributed Redundant Integration of Data Center Battery Storage with the Grid for Regulation Services,” in Power and Energy Society General Meeting, 2021.
  11. W. Cui, W. Yang, and B. Zhang, “Power System Dynamic Simulation Using Fourier Neural Operators,” in NeurIPS 2021 Workshop on Tackling Climate Change with Machine Learning, 2021.
  12. Y. Chen, Y. Tan, L. Zhang, and B. Zhang, “Vulnerabilities of Power System Operations to Load Forecasting Data Injection Attacks,” in IEEE Smartgrid Comm, 2021.
  13. A. Ademola-Idowu and B. Zhang, “MPC-Based Multi-Inverter Power Control in Low-Inertia Power Systems,” in Power and Energy Society General Meeting, 2021.
  14. W. Cui, J. Li, and B. Zhang, “Safe Learning for Voltage Control,” in NeurIPS 2021 Workshop on Tackling Climate Change with Machine Learning, 2021.
  15. Y. Shi and B. Zhang, “Multi-Agent Reinforcement Learning in Cournot Games,” in 2020 59th IEEE Conference on Decision and Control (CDC), 2020, pp. 3561–3566.
  16. C. P. Dowling and B. Zhang, “ Transfer Learning for HVAC System Fault Detection,” in American Control Conference (ACC), 2020.
  17. Y. Chen, Y. Shi, and B. Zhang, “Optimal Control Via Neural Networks: A Convex Approach,” in International Conference on Learning Representations (ICLR), 2019.
  18. P. Li, B. Jin, R. Xiong, D. Wang, A. L. Sangiovanni-Vincentelli, and B. Zhang, “A tractable ellipsoidal approximation for voltage regulation problems,” in American Control Conference (ACC), 2019, pp. 1301–1306.
  19. C. P. Dowling and B. Zhang, “Mitigation of Coincident Peak Charges via Approximate Dynamic Programming,” in IEEE Conf. Decision and Control (CDC), 2019, pp. 4202–4207.
  20. Y. Chen, Y. Tan, and B. Zhang, “Exploiting Vulnerabilities of Load Forecasting Through Adversarial Attacks,” in Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019, pp. 1–11.
  21. Y. Chen, X. Wang, and B. Zhang, “An Unsupervised Deep Learning Approach for Scenario Forecasts,” in Power Systems Computation Conference (PSCC), 2018, pp. 1–7.
  22. A. Ademola-Idowu and B. Zhang, “Optimal Design of Virtual Inertia and Damping Coefficients for Virtual Synchronous Machines,” in Power and Energy Society General Meeting, 2018.
  23. Y. Shi, B. Xu, Y. Tan, and B. Zhang, “A Convex Cycle-based Degradation Model for Battery Energy Storage Planning and Operation,” in Proceedings of American Control Conference, 2018.
  24. Y. Chen, P. Li, and B. Zhang, “Bayesian Renewables Scenario Generation via Deep Generative Networks,” in Conference on Information Sciences and Systems (CISS), 2018.
  25. H. Wang and B. Zhang, “Energy Storage Arbitrage in Real-Time Markets Via Reinforcement Learning,” in Power and Energy Society General Meeting, 2018.
  26. Y. Weng, A. Kumar, M. Saleem, and B. Zhang, “Big Data and Deep Learning Platform for Terabyte-Scale Renewable Datasets,” in Power Systems Computation Conference (PSCC), 2018.
  27. J. E. Contreras-Ocana, U. Siddiqi, and B. Zhang, “Non-Wire Alternatives to Capacity Expansion,” in Power and Energy Society General Meeting, 2018.
  28. T. Fiez, L. J. Ratliff, C. Dowling, and B. Zhang, “Data Driven Spatio-Temporal Modeling of Parking Demand,” in Proceedings of American Control Conference, 2018.
  29. V. R. Pamula, X. Sun, S. Kim, F. Rahman, B. Zhang, and V. Sathe, “An All‐Digital True‐Random‐Number Generator with Integrated De‐correlation and Bias‐Correction at 3.2‐to‐86 Mb/s, 2.58 pJ/bit in 65 nm CMOS,” in Symposia on VLSI Technology and Circuits, 2018.
  30. P. Li, S. Sekar, and B. Zhang, “A Capacity-Price Game for Uncertain Renewables Resources,” in Proceedings of ACM E-Energy, 2018.
  31. Y. Chen, Y. Shi, and B. Zhang, “Modeling and Optimization of Complex Building Energy Systems with Deep Neural Networks,” in Asilomar Conference, 2017.
  32. B. Xu, Y. Shi, D. Kirschen, and B. Zhang, “Optimal Regulation Response of Batteries Under Cycle Aging Mechanisms,” in IEEE Conference on Decision and Control, 2017.
  33. C. Dowling, T. Fiez, L. Ratliff, and B. Zhang, “Optimizing Curbside Parking Resources Subject to Congestion Constraints,” in IEEE Conference on Decision and Control, 2017.
  34. P. Li and B. Zhang, “Distribution System Voltage Control under Uncertainties,” in Asilomar Conference, 2017.
  35. C. Riquelme, R. Johari, and B. Zhang, “Online Active Learning Via Thresholding,” in Proceedings of AAAI Conference on Artificial Intelligence, 2017.
  36. P. Li and B. Zhang, “An Optimal Treatment Assignment Strategy to Evaluate Demand Response Effect,” in Proceedings of the Allerton Conference on Communication, Control and Computing, 2016.
  37. Y. Shi, B. Xu, B. Zhang, and D. Wang, “Leveraging energy storage to optimize data center electricity cost in emerging power markets,” in ACM E-Energy, 2016.
  38. P. Li, B. Zhang, Y. Weng, and R. Rajagopal, “Autoregressive model for individual consumption data - Sparsity recovery and significance test,” in Proc. IEEE Power and Energy Society General Meeting (PESGM), 2016, pp. 1–5.
  39. P. Li and B. Zhang, “Estimating treatment effects in demand response,” in Proc. IEEE Statistical Signal Processing Workshop (SSP), 2016, pp. 1–5.
  40. H. Hosseini, S. Kannan, B. Zhang, and R. Poovendran, “Learning Temporal Dependence from Time-Series Data with Latent Variables,” in Proc. IEEE Int. Conf. Data Science and Advanced Analytics (DSAA), 2016, pp. 253–262.
  41. L. J. Ratliff, C. Dowling, E. Mazumdar, and B. Zhang, “To Observe or Not to Observe: Queuing Game Framework for Urban Parking,” in IEEE Conference on Decision and Control (CDC), 2016.
  42. G. Cezar, R. Rajagopal, and B. Zhang, “Stability of interconnected DC converters,” in Proc. 54th IEEE Conf. Decision and Control (CDC), 2015, pp. 9–14.
  43. S. Patel, R. Sevlian, B. Zhang, and R. Rajagopal, “Aggregation for load servicing,” in PES General Meeting| Conference & Exposition, 2014 IEEE, 2014, pp. 1–5.
  44. Y. Yu, B. Zhang, and R. Rajagopal, “Do wind power producers have market power and exercise it?,” in IEEE PES General Meeting, 2014, pp. 1–5.
  45. B. Zhang, A. D. Dominguez-Garcia, and D. Tse, “A local control approach to voltage regulation in distribution networks,” in Proc. North American Power Symp. (NAPS), 2013, pp. 1–6.
  46. J. Qin, B. Zhang, and R. Rajagopal, “Risk limiting dispatch with ramping constraints,” in Proc. IEEE Int Smart Grid Communications (SmartGridComm) Conf, 2013, pp. 791–796.
  47. B. Zhang, R. Rajagopal, and D. Tse, “Risk limiting dispatch in congested networks,” in Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on, 2013, pp. 7568–7575.
  48. A. Lam, B. Zhang, and D. N. Tse, “Distributed algorithms for optimal power flow problem,” in Decision and Control (CDC), 2012 IEEE 51st Annual Conference on, 2012, pp. 430–437.
  49. J. Lavaei, D. Tse, and B. Zhang, “Geometry of power flows in tree networks,” in Power and Energy Society General Meeting, 2012 IEEE, 2012, pp. 1–8.
  50. R. Rajagopal, D. Tse, and B. Zhang, “Risk limiting dispatch in congested networks,” in Proc. 50th Annual Allerton Conf. Communication, Control, and Computing (Allerton), 2012, pp. 1900–1907.
  51. Y. Kanoria, A. Montanari, D. Tse, and B. Zhang, “Distributed storage for intermittent energy sources: Control design and performance limits,” in Communication, Control, and Computing (Allerton), 2011 49th Annual Allerton Conference on, 2011, pp. 1310–1317.
  52. B. Zhang and D. Tse, “Geometry of feasible injection region of power networks,” in Communication, Control, and Computing (Allerton), 2011 49th Annual Allerton Conference on, 2011, pp. 1508–1515.
  53. B. Zhang and M. D. Trott, “Reference-free audio matching for rendezvous,” in IEEE Conference on Acoustics Speech and Signal Processing (ICASSP), 2010.
  54. B. Zhang, S. B. Kuntze, L. Pavel, and J. S. Aitchison, “Delay-tolerant control design for Semiconductor Optical Amplifiers,” in American Control Conference, 2008, 2008, pp. 4154–4160.
  55. B. Zhang, E. Young, and C. Simmons, “3-D computational analysis of hemodynamic shear stresses on the aortic value,” in Canadian Congress of Applied Mechanics, 2007.

Thesis

  1. B. Zhang, “Control and Optimization of Power Systems with Renewables: Voltage Regulation and Generator Dispatch,” PhD thesis, University of California, Berkeley, 2013.