Research Interests

Our research interests span the areas of electrical, thermal, and transportation engineering. Our vision is to develop cutting-edge theories and technologies (majorly based on optimization, data analytics, and machine learning) to help policymakers, practitioners, and energy prosumers to make “smart decisions” in building and managing their energy systems. Currently, we have been focusing on power and transportation nexus, distributed energy resources, integrated energy systems, and  internet of things for smart energy.

Research Projects

  1. Chi Kong Wong (PI), and Hongcai Zhang (co-PI), “Multi-energy system coordination and carbon management in low-carbon park,” Macao Science and Technology Development Fund and Ministry of Science and Technology of China Joint Project, MOP 1,864,000, 2022-2025.
  2. Hongcai Zhang (PI), “Key technologies and applications of network-load-storage interaction of virtual power station in smart city,” Science and Technology Development Fund, Macao, China, MOP 1,100,000, 2022-2024.
  3. Yonghua Song (PI), Ningyi Dai (sub-task PI), Hongcai Zhang (sub-task PI), and Keng Weng Lao (sub-task PI), “Intelligent Coordinated Operation, Protection and Application on Integrated Energy IoT,” Science and Technology Development Fund, Macao, China, MOP 7,670,000, 2021-2024.
  4. Hongcai Zhang (PI), “Strategic operation of shared-use autonomous electric fleet considering synergy of power and transportation systems,” Natural Science Foundation of China, RMB 240,000, 2021-2023.
  5. Hongcai Zhang (PI), “Strategic operation and optimization of integrated energy systems in smart city,” Science and Technology Development Fund, Macao, China, MOP 1,165,000, 2020-2023.
  6. Hongcai Zhang (PI), “Strategic operation and optimization of autonomous electric fleet,” Guangdong Natural Science Foundation, China, RMB 100,000, 2020-2021.

Book Chapters

  1. Z. Hu, Y. Song, and H. Zhang, “Electric vehicle and vehicle-to-grid technology,” Energy Internet, edited by H. Sun et. al., China Science Publishing, Beijing, 2020. (in Chinese)
  2. Z. Hu, J. He, and H. Zhang, “Energy Internet and Plug-in Electric Vehicles,” Development of Energy Internet, edited by R. Zeng et. al., Tsinghua University Press, Beijing, 2017. (in Chinese)

Journal Papers

Preprint
  1. Z. Hu, and H. Zhang, “Optimal Power Flow Based on Physical-Model-Integrated Neural Network with Worth-Learning Data Generation,” arXiv:2301.03766, 2023.
  2. G. Chen, H. Zhang, and Y. Song, “Efficient constraint learning for data-driven active distribution network operation,” arXiv:2208.03940, 2022.
  3. L. He, N. Ke, W. Qi, and H. Zhang, “From Curtailed Renewable Energy to Green Hydrogen: Infrastructure Planning for Hydrogen Fuel-Cell Vehicles,” Available at SSRN, 2022. DOI: 10.2139/ssrn.4147663
In press
  1. P. Yu, H. Zhang, Y. Song, H. Hui, and G. Chen, “District Cooling System Control for Providing Operating Reserve based on Safe Deep Reinforcement Learning,” IEEE Transactions on Power Systems, pp. 1–14, 2023. DOI: 10.1109/TPWRS.2023.3237888
  2. G. Chen, H. Zhang, H. Hui, and Y. Song, “Scheduling HVAC loads to promote renewable generation integration with a learning-based joint chance-constrained approach,” CSEE Journal of Power and Energy Systems, 2022. Download: arXiv:2112.09827
  3. Z. Wang, P. Yu, and H. Zhang, “Privacy-Preserving Regulation Capacity Evaluation for HVAC Systems in Heterogeneous Buildings based on Federated Learning and Transfer Learning,” IEEE Transactions on Smart Grid, pp. 1–15, 2022. DOI: 10.1109/TSG.2022.3231592
  4. P. Yu, H. Zhang, Y. Song, H. Hui, and C. Huang, “Frequency Regulation Capacity Offering of District Cooling System: An Intrinsic-motivated Reinforcement Learning Method,” IEEE Transactions on Smart Grid, pp. 1–12, 2022. DOI: 10.1109/TSG.2022.3220732
  5. K. Li, C. Shao, H. Zhang, and X. Wang, “Strategic Pricing of Electric Vehicle Charging Service Providers in Coupled Power-Transportation Networks,” IEEE Transactions on Smart Grid, pp. 1–13, 2022. DOI: 10.1109/TSG.2022.3219109
  6. L. Kong, H. Zhang, W. Li, H. Bai, and N. Dai, “Spatial-temporal Scheduling of Electric Bus Fleet in Power-Transportation Coupled Network,” to appear in IEEE Transactions on Transportation Electrification, 2022. DOI: 10.1109/TTE.2022.3214335
  7. X. Yan, H. Zhang, C. Gu, N. Liu, F. Li, and Y. Song, “Truncated Strategy Based Dynamic Network Pricing for Energy Storage,” to appear in Journal of Modern Power Systems and Clean Energy, 2022. DOI: 10.35833/MPCE.2021.000631
  8. Q. Hou, G. Chen, N. Dai, and H. Zhang, “Distributionally Robust Chance-Constrained Optimization for Soft Open Points Operation in Active Distribution Networks,” to appear in CSEE Journal of Power and Energy Systems, 2022. DOI: 10.17775/CSEEJPES.2021.02110
Published
  1. X. Yan, C. Gu, H. Zhang, N. Liu, F. Li, and Y. Song, “Network Pricing with Investment Waiting Cost based on Real Options under Uncertainties,” IEEE Transactions on Power Systems, vol. 38, no. 1, pp. 427-435, 2023. DOI: 10.1109/TPWRS.2022.3158349
  2. G. Chen, H. Zhang, H. Hui, and Y. Song, “Deep-quantile-regression-based surrogate model for joint chance-constrained optimal power flow with renewable generation,” IEEE Transactions on Sustainable Energy, vol. 14, no. 1, pp. 657-672, 2023. DOI: 10.1109/TSTE.2022.3223764
  3. Y. Song, H. Zhang, C. Chen, “Typical Pathway to Carbon Neutrality for Urban Smart Energy Systems —Case Study of Macao,” Bulletin of Chinese Academy of Sciences, vol. 37, no. 11, pp. 1650-1663, 2022. (in Chinese) DOI: 10.16418/j.issn.1000-3045.20220125004 
  4. H. Hui, Y. Chen, S. Yang, H. Zhang, and T. Jiang, “Coordination control of distributed generators and load resources for frequency restoration in isolated urban microgrids,” Applied Energy, vol. 327, no. December, p. 120116, 2022. DOI: 10.1016/j.apenergy.2022.120116
  5. J. Hong, H. Hui, H. Zhang, N. Dai, and Y. Song, “Event-Triggered Consensus Control of Large-Scale Inverter Air Conditioners for Demand Response,” IEEE Transactions on Power Systems, vol. 37, no. 6, pp. 4954-4957, 2022. DOI: 10.1109/TPWRS.2022.3204215
  6. G. Chen, H. Zhang, H. Hui, and Y. Song, “Chance-constrained regulation capacity offering for HVAC systems under non-Gaussian uncertainties with mixture-model-based convexification,”IEEE Transactions on Smart Grid, vol. 13, no. 6, pp. 4379-4391, 2022. DOI: 10.1109/TSG.2022.3182000
  7. Y. Dong, S. Ma, H. Zhang, and G. Yang, “Wind Power Prediction Based on Multi-Class Autoregressive Moving Average Model with Logistic Function,” Journal of Modern Power Systems and Clean Energy, vol. 10, no. 5, pp. 1184-1193, 2022. DOI: 10.35833/MPCE.2021.000717
  8. H. Hui, P. Siano, Y. Ding, P. Yu, H. Zhang, N. Dai, and Y. Song, “A Transactive Energy Framework for Inverter-based HVAC Loads in a Real-time Local Electricity Market Considering Distributed Energy Resources,” IEEE Transactions on Industrial Informatics, vol. 18, no. 12, pp. 8409-8421, 2022. DOI: 10.1109/TII.2022.3149941
  9. G. Chen, B. Yan, H. Zhang, D. Zhang, and Y. Song, “Time-efficient strategic power dispatch for district cooling systems considering the spatial-temporal evolution of cooling load uncertainties,” CSEE Journal of Power and Energy Systems, vol. 8, no. 5, pp. 1457-1467, 2022. DOI: 10.17775/CSEEJPES.2020.06800
  10. J. Hong, H. Hui, H. Zhang, N. Dai, and Y. Song, “Distributed Control of Large-scale Inverter Air Conditioners for Providing Operating Reserve Based on Consensus With Nonlinear Protocol,” IEEE Internet of Things Journal, vol.9, no. 17, pp. 15847-15857, 2022. DOI: 10.1109/JIOT.2022.3151817
  11. S. Lv, S. Chen, Z. Wei, and H. Zhang, “Power-Transportation Coordination: toward a Hybrid Economic-Emission Dispatch Model,” IEEE Transactions on Power Systems, vol. 37, no. 5, pp. 3969-3981, 2022. DOI: 10.1109/TPWRS.2021.3131306
  12. H. Hui, P. Yu, H. Zhang, N. Dai, W. Jiang and Y. Song, “Regulation Capacity Evaluation of Large-scale Residential Air Conditioners for Improving Flexibility of Urban Power Systems,” International Journal of Electrical Power & Energy Systems, vol. 142,  part A, p. 108269, November 2022. DOI: 10.1016/j.ijepes.2022.108269
  13. C. Huang, H. Zhang, L. Wang, X. Luo, and Y. Song, “Mixed Deep Reinforcement Learning Considering Discrete-Continuous Hybrid Action Space for Smart Home Energy Management,” Journal of Modern Power Systems and Clean Energy, vol. 10, no. 3, pp. 743-754, 2022. DOI: 10.35833/MPCE.2021.000394
  14. Y. Liu, Z. Li, W. Wei, J. Zheng, and H. Zhang, “Data-Driven Dispatchable Regions with Potentially Active Boundaries for Renewable Power Generation: Concept and Construction,” IEEE Transactions on Sustainable Energy, vol. 13, no. 2, pp. 882-891, 2022. DOI: 10.1109/TSTE.2021.3138125
  15. D. Zhang, H. Zhu, H. Zhang, H. H. Goh, H. Liu, and T. Wu, “Multi-objective Optimization for Smart Integrated Energy System Considering Demand Responses and Dynamic Prices,” IEEE Transactions on Smart Grid, vol. 13, no. 2, pp. 1100-1112, 2022. DOI: 10.1109/TSG.2021.3128547
  16. D. Zhang, H. Zhu, H. Zhang, H. H. Goh, H. Liu, T. Wu, “An Optimized Design of Residential Integrated Energy System Considering the Power-to-Gas Technology with Multi-Functional Characteristics,” Energy, vol. 238, p. 121774, January 2022.  DOI: 10.1016/j.energy.2021.121774
  17. G. Chen, H. Zhang, H. Hui, N. Dai, and Y. Song, “Scheduling thermostatically controlled loads to provide regulation capacity based on a learning-based optimal power flow model,” IEEE Transactions on Sustainable Energy, vol. 12, no. 4, pp. 2459-2470, 2021.  DOI: 10.1109/TSTE.2021.3100846
  18. G. Chen, H. Zhang, H. Hui, and Y. Song, “Fast Wasserstein-distance-based distributionally robust chance-constrained power dispatch for multi-zone HVAC systems,” IEEE Transactions on Smart Grid, vol. 12, no. 5, pp. 4016-4028, 2021.  DOI: 10.1109/TSG.2021.3076237
  19. D. Zhang, H. Li, H. Zhu, H. Zhang, H. H. Goh, M. C. Wong, and T. Wu, “Impact of COVID-19 on Urban Energy Consumption of Commercial Tourism City,” Sustainable Cities and Society, vol. 73, p. 103133, October 2021. DOI: 10.1016/j.scs.2021.103133
  20. B. Yan, G. Chen, H. Zhang, and M. C. Wong,  “Strategical district cooling system operation with accurate spatiotemporal consumption modeling,” Energy and Buildings, vol. 247, p. 111165, September 2021. DOI: 10.1016/j.enbuild.2021.111165
  21. C. Huang, H. Zhang, Y. Song, L. Wang, T. Ahmad, and X. Luo, “Demand response for industrial micro-grid considering photovoltaic power uncertainty and battery operational cost,” IEEE Transactions on Smart Gridvol. 12, no. 4, pp. 3043-3055, July 2021. DOI: 10.1109/TSG.2021.3052515
  22. X. Yan, C. Gu, H. Zhang, F. Li and Y. Song, “Waiting Cost based Long-Run Network Investment Decision-making under Uncertainty,” IEEE Transactions on Power Systemsvol. 36, no. 4, pp. 3340-3348, July 2021. DOI: 10.1109/TPWRS.2020.3045723
  23. S. Hu, Y. Xiang, H. Zhang, S. Xie, J. Li, C. Gu, W. Sun, and J. Liu, “Hybrid forecasting method for wind power integrating spatial correlation and corrected numerical weather prediction,” Applied Energy, vol. 293, no. March, p. 116951, 2021. DOI: 10.1016/j.apenergy.2021.116951
  24. Z. Zhou, S. J. Moura, H. Zhang, X. Zhang, Q. Guo, and H. Sun, “Power-Traffic Network Equilibrium Incorporating Behavioral Theory: A Potential Game Perspective,” Applied Energy, vol. 289, p. 116703, 2021. DOI: 10.1016/j.apenergy.2021.116703
  25. T. Ahmad, D. Zhang, C. Huang, H. Zhang, N. Dai, Y. Song, and H. Chen, “Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities,” Journal of Cleaner Production, V. 289, p. 125834, March 2021. DOI: 10.1016/j.jclepro.2021.125834
  26. R. Brito, M. C. Wong, H. Zhang, M. G. Da Costa Junior, C. S. Lam, and C. K. Wong, “Instantaneous active and reactive load signature applied in non‐intrusive load monitoring systems,” IET Smart Grid, vol. 5, no. 1, pp. 121-133, 2021. DOI: 10.1049/stg2.12008
  27. Y. Zhao, Y. Guo, Q. Guo, H. Zhang and H. Sun, “Deployment of the Electric Vehicle Charging Station Considering Existing Competitors,” IEEE Transactions on Smart Gridvol. 11, no. 5, pp. 4236-4248,  September 2020. DOI: 10.1109/TSG.2020.2991232
  28. H. Zhang, C. J. R. Sheppard, T. E. Lipman, and S. J. Moura, “Joint Fleet Sizing and Charging System Planning for Autonomous Electric Vehicles,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 11, pp. 4725-4738,  November 2020. DOI: 10.1109/TITS.2019.2946152
  29. T. Ahmad and H. Zhang, “Novel deep supervised ML models with feature selection approach for large-scale utilities and buildings short and medium-term load requirement forecasts,” Energy, vol. 209, p. 118477, 2020. DOI: 10.1016/j.energy.2020.118477
  30. H. Zhang, Z. Hu, and Y. Song, “Power and Transport Nexus: Routing Electric Vehicles to Promote Renewable Power Integration,” IEEE Transactions on Smart Gridvol. 11, no. 4, pp. 3291-3301, July 2020. DOI: 10.1109/TSG.2020.2967082
  31. J. Li, J. Lin, H. Zhang, Y. Song, G. Chen, and L. Ding, “Optimal Investment of Electrolyzers and Seasonal Storages in Hydrogen Supply Chains Incorporated with Renewable Electric Networks,” IEEE Transactions on Sustainable Energy, vol. 11, no. 3, pp. 1773-1784, July 2020. DOI: 10.1109/TSTE.2019.2940604
  32. T. Ahmad, H. Chen, D. Zhang, and H. Zhang, “Smart energy forecasting strategy with four machine learning models for climate-sensitive and non-climate sensitive conditions,” Energy, vol. 198, p. 117283, 2020. DOI: 10.1016/j.energy.2020.117283
  33. T. Zeng, H. Zhang, and S. J. Moura, “Solving Overstay and Stochasticity in PEV Charging Station Planning with Real Data,” IEEE Transactions on Industrial Informatics, vol. 16, no. 5, pp. 3504-3514, May 2020. DOI: 10.1109/TII.2019.2955997
  34. T. Ahmad, H. Zhang, B. Yan, “A review on renewable energy and electricity requirement forecasting models for smart grid and buildings,” Sustainable Cities and Society, vol. 55, no. April 2019, pp. 102052, 2020. DOI: 10.1016/j.scs.2020.102052
  35. H. Zhang, C. J. R. Sheppard, T. E. Lipman, T. Zeng, and S. J. Moura, “Charging Infrastructure Demands of Shared-Use Autonomous Electric Vehicles in Urban Areas,” Transportation Research Part D: Transport and Environment, vol. 78, p. 102210, 2020. DOI: 10.1016/j.trd.2019.102210
  36. Z. Lin, Z. Hu, H. Zhang, and Y. Song, “Optimal ESS allocation in distribution network using accelerated generalized Benders decomposition,” IET Generation, Transmission & Distribution, vol. 13, no. 13, pp. 2738-2746, 2019. DOI: 10.1049/iet-gtd.2018.5863
  37. H. Luo, Z. Hu, H. Zhang, and H. Chen, “Coordinated Active Power Control Strategy for Deloaded Wind Turbines to Improve Regulation Performance in AGC,” IEEE Transactions on Power Systems, vol. 34, no. 1, pp. 98-108, 2019. DOI: 10.1109/TPWRS.2018.2867232
  38. B. Zhao, Z. Hu, Q. Zhou, H. Zhang, and Y. Song, “Optimal transmission switching to eliminate voltage violations during light-load periods using decomposition approach,” Journal of Modern Power Systems and Clean Energy, vol. 7, no. 2, pp. 297-308, 2019. DOI: 10.1007/s40565-018-0422-4
  39. H. Zhang, Z. Hu, E. Munsing, S. J. Moura, and Y. Song, “Data-driven Chance-constrained Regulation Capacity Offering for Distributed Energy Resources,” IEEE Transactions on Smart Grid, vol. 10, no. 3, pp. 2713-2725, 2019. DOI: 10.1109/TSG.2018.2809046
  40. H. Chen, Z. Hu, H. Luo, J. Qin, R. Rajagopal, and H. Zhang, “Design and Planning of a Multiple-charger Multiple-port Charging System for PEV Charging Station,” IEEE Transactions on Smart Grid, vol. 10, no. 1, pp. 173-183, 2019. DOI: 10.1109/TSG.2017.2735636
  41. X. Chen, H. Zhang, Z. Xu, C. P. Nielsen, M. B. McElroy, and J. Lv, “Impacts of Fleet Types and Charging Modes for Electric Vehicles on Emissions under Different Penetrations of Wind Power,” Nature Energy, vol. 3, pp. 413-421, 2018. DOI: 10.1038/s41560-018-0133-0 (equal contribution)
  42. H. Zhang, S. J. Moura, Z. Hu, W. Qi, and Y. Song, “Joint PEV Charging Network and Distributed PV Generation Planning Based on Accelerated Generalized Benders Decomposition,” IEEE Transactions on Transportation Electrification, vol. 4, no. 3, pp. 789-803, 2018. DOI: 10.1109/TTE.2018.2847244
  43. H. Chen, Z. Hu, H. Zhang and H. Luo, “Coordinated Charging and Discharging Strategies for Plug-in Electric Bus Fast Charging Station with Energy Storage System.” IET Generation, Transmission & Distribution, vol. 12, no. 9, pp. 2019-2028, 2018. DOI: 10.1049/iet-gtd.2017.0636
  44. H. Zhang, S. J. Moura, Z. Hu, W. Qi, and Y. Song, “A Second Order Cone Programming Model for Planning PEV Fast-Charging Stations,” IEEE Transactions on Power Systems, vol. 33, no. 3, pp. 2763-2777, 2018. DOI: 10.1109/TPWRS.2017.2754940
  45. H. Zhang, S. J. Moura, Z. Hu, and Y. Song, “PEV Fast-Charging Station Siting and Sizing on Coupled Transportation and Power Networks,” IEEE Transactions on Smart Grid, vol. 9, no. 4, pp. 2595-2605, 2018. DOI: 10.1109/TSG.2016.2614939
  46. W. Qi, B. Shen, H. Zhang, and Z. M. Shen, “Sharing Demand-Side Energy Resources – A Conceptual Design,” Energy, vol. 135, pp. 455-465, 2017. DOI: 10.1016/j.energy.2017.06.144
  47. H. Zhang, Z. Hu, Z. Xu, and Y. Song, “Optimal Planning of PEV Charging Station with Single Output Multiple Cables Charging Spots,” IEEE Transactions on Smart Grid, vol. 8, no. 5, pp. 2119-2128, 2017. DOI: 10.1109/TSG.2016.2517026
  48. H. Zhang, Z. Hu, Z. Xu, and Y. Song, “Evaluation of Achievable Vehicle-to-Grid Capacity Using Aggregate PEV Model,” IEEE Transactions on Power Systems, vol. 32, no. 1, pp. 784-794, 2017. DOI: 10.1109/TPWRS.2016.2561296
  49. Z. Hu, K. Zhan, H. Zhang, and Y. Song, “Pricing Mechanisms Design for Guiding Electric Vehicle Charging to Fill Load Valley,” Applied Energy, vol. 178, pp. 155-163, 2016. DOI: 10.1016/j.apenergy.2016.06.025
  50. H. Zhang, Z. Hu, Z. Xu, and Y. Song, “An Integrated Planning Framework for Different Types of PEV Charging Facilities in Urban Area,” IEEE Transactions on Smart Grid, vol. 7, no. 5, pp. 2273-2284, 2016. DOI: 10.1109/TSG.2015.2436069
  51. Z. Xu, W. Su, Z. Hu, Y. Song, H. Zhang, “A Hierarchical Framework for Coordinated Charging of Plug-in Electric Vehicles in China,” IEEE Transactions on Smart Grid, vol. 7, no. 1, pp. 428-438, 2016. DOI: 10.1109/TSG.2014.2387436
  52. K. Zhan, Z. Hu, Y. Song, Z. Xu, L. Jia, H. Zhang, “A Coordinated Charging Strategy for Electric Vehicle Three-phase Load Balance,” Automation of Electric Power Systems, vol. 39, no. 17, pp. 201-207, 2015. DOI: 10.7500/AEPS20150402012 (in Chinese)
  53. Y. Guo, Z. Hu, H. Zhang, W. Su, K. Zhan, Z. Xu, “A Statistical Method to Evaluate the Capability of Residential Distribution Network for Accommodating Electric Vehicle Charging Load,” Power System Technology, vol. 39, no. 9, pp. 2458-246, 2015. DOI: 10.13335/j.1000-3673.pst.2015.09.013 (in Chinese)
  54. Z. Hu, K. Zhan, Z. Xu, D. Xiang, H. Zhang, “Analysis and Outlook on the Key Problems of Electric Vehicle and Power Grid Interaction,” Electric Power Construction, vol. 36, no. 7, pp. 6-13, 2015. DOI: 10.3969/j.issn.1000-7229.2015.07.001 (in Chinese)
  55. H. Luo, Z. Hu, H. Zhang, “Effect Analysis of Ambient Temperature on Electric Vehicle Charging Load,” Electric Power Construction, vol. 36, no. 7, pp. 69-74, 2015. DOI: 10.3969/j.issn.1000-7229.2015.07.009 (in Chinese)
  56. Y. Zhang, W. Zhao, Y. Xiao, G. Lin, X. Chen, Z. Hu, H. Zhang, Z. Xu, “A Hierarchical Architecture Based Simulation Platform for Coordinated Charging of Large-Scale Electric Vehicles,” Power System Technology, vol. 39, no. 1, pp. 55-62, 2015. DOI: 10.13335/j.1000-3673.pst.2015.01.009 (in Chinese)
  57. Z. Xu, Z. Hu, Y. Song, H. Zhang, X. Chen, “Coordinated Charging Strategy for PEV Charging Stations Based on Dynamic Time-of-use Tariffs,” Proceedings of the CSEE, vol. 33, no. 22, pp. 3638-3646, 2014. DOI: 10.13334/j.0258-8013.pcsee.2014.22.008 (in Chinese)
  58. H. Zhang, Z. Hu, Y. Song, Z. Xu, L. Jia, “A Prediction Method for Electric Vehicle Charging Load Considering Spatial and Temporal Distribution,” Automation and Electric Power Systems, vol. 38, no. 1, pp. 13-20, 2014. DOI: 10.7500/AEPS20130613009 (in Chinese)

Conference Papers

  1. Z. Wang, and H. Zhang, “Consumer Baseline Load Estimation in Demand Response: A Generative Adversarial Networks Approach,” 6th IEEE Conference on Energy Internet and Energy System Integration (EI2), Chengdu, China, Oct 2022. (Best Paper Award)
  2. P. Yu, H. Zhang, and Y. Song, “Smoothing Tie-line Power for Microgrids by Controlling District Cooling System based on Soft Actor-Critic Reinforcement Learning,” 6th IEEE Conference on Energy Internet and Energy System Integration (EI2), Chengdu, China, Oct 2022.
  3. L. Kong, H. Zhang, and N. Dai, “Spatial-temporal Scheduling of Commercial EVs for System Restoration of a Damaged Power-transportation Coupled Network,” 6th IEEE Conference on Energy Internet and Energy System Integration (EI2), Chengdu, China, Oct 2022.
  4. G. Chen, H. Zhang, and Y. Song, “Chance-constrained DC Optimal Power Flow with Non-Gaussian Distributed Uncertainties,” 2022 IEEE Power & Energy Society General Meeting (PESGM), 2022, pp. 1-5. DOI:10.1109/PESGM48719.2022.9916658
  5. Y. Liu, H. Hui, H. Zhang, and L. Gao, “Risk Assessment of Offshore Wind Farm Outages Under Typhoon Conditions,” 2022 IEEE Power & Energy Society General Meeting (PESGM), 2022, pp. 1-5. DOI:10.1109/PESGM48719.2022.9916685
  6. P. Yu, H. Hui, H. Zhang, C. Huang, and Y. Song, “Frequency Regulation Capacity Offering of District Cooling System based on Reinforcement Learning,” 2022 IEEE Power & Energy Society General Meeting (PESGM), 2022, pp. 1-5. DOI:10.1109/PESGM48719.2022.9916851
  7. H. Hui, P. Yu, H. Zhang, N. Dai, W. Jiang and Y. Song, “Regulation Capacity Evaluation of Large-scale Heterogeneous Residential Air Conditioning Loads,” the 3rd IEEE Conference on Sustainable Power and Energy (iSPEC 2021), Nanjing, China, Dec. 2021. DOI: 10.1109/iSPEC53008.2021.9735739 (Best Paper Award)
  8. B. Zou, H. Zhang, G. Chen, and Y. Song, “Optimal Power Scheduling of Data Centers with Deferrable Computation Requests,” the 5th IEEE Conference on Energy Internet and Energy System Integration (EI2), Taiyuan, China, Oct 2021. DOI:10.1109/EI252483.2021.9713121
  9. D. Liu, H. Zhang, and Y. Song, “Robust Transmission Expansion Planning Considering Massive N-1 Contingencies with High Proportion of Renewable Energy,” the 5th IEEE Conference on Energy Internet and Energy System Integration (EI2), Taiyuan, China, Oct 2021. DOI:10.1109/EI252483.2021.9713305
  10. H. Hui, Q. Yang, N. Dai, H. Zhang, Y. Ding and Y. Song, “Anticipatory Control of Flexible Loads for System Resilience Enhancement Facing Accidental Outages,” the 2021 International Conference on Power System Technology (POWERCON), Haikou, China, Dec. 2021. DOI:10.1109/POWERCON53785.2021.9697825
  11. C. Huang, L. Wang, X. Luo, H. Zhang, and Y. Song, “Evolutionary computing assisted deep reinforcement learning for multi-objective integrated energy system management,” the 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2021, pp. 506-511. DOI:10.1109/ICTAI52525.2021.00082
  12. G. Chen, H. Zhang, N. Dai, and Y. Song, “Topology-free optimal power dispatch for distribution network considering security constraints and flexible building thermal inertia,” 2021 IEEE PES General Meeting (PESGM), 2021, pp. 1-5. DOI:10.1109/PESGM46819.2021.9638204
  13. Y. Li, H. Gao, S. He, H. Li, H. Zhang, K. Lao, J. Zhang, “Multi-stage Planning Method for Distribution Network Considering Building Integrated Energy Station,” in 2021 Power System and Green Energy Conference (PSGEC), Shanghai, China, August 2021, pp. 45-50. DOI:10.1109/PSGEC51302.2021.9541986
  14. H. Gao, S. He, H. Li, H. Zhang, and K. W. Lao, “Energy Management for Building Integrated Energy System Considering Generalized Energy Storage,” in 2021 4th International Conference on Energy, Electrical and Power Engineering (CEEPE), Chongqing, China, July 2021, pp. 886-891. DOI:10.1109/CEEPE51765.2021.9475752
  15. Y. Zhao, H. Gao, H. Li, H. Zhang, and K. W. Lao, “Stackelberg Game Based Optimal Multi-energy Man- agement for Commercial Building Operators,” in 2021 4th International Conference on Energy, Electrical and Power Engineering (CEEPE), Chongqing, China, July 2021, no. 1, pp. 1200-1204. DOI:10.1109/CEEPE51765.2021.9475764
  16. G. Chen, B. Yan, H. Zhang, Y. Song, “Optimal Power Dispatch for District Cooling System Considering Cooling Water Transport Delay,” IEEE PES Asia-Pacific Power & Energy Engineering Conference (APPEEC), Nanjing, China, 2020, pp. 1-5. DOI:10.1109/APPEEC48164.2020.9220450
  17. Z. Zhou, S. Moura, H. Zhang, X. Zhang, Q. Guo, H. Sun, “A Game-Theoretic Approach to Analyzing Equilibria in Coupled Power and Transportation Networks,” IEEE PES General Meeting 2019, Atlanta, GA, 2019, pp. 1-5. DOI: 10.1109/PESGM40551.2019.8974036
  18. H. Zhang, S. J. Moura, Z. Hu, W. Qi, and Y. Song, “Joint PEV Charging Station and Distributed PV Generation Planning,” IEEE PES General Meeting 2017, Chicago, IL, 2017, pp. 1-5. DOI: 10.1109/PESGM.2017.8274111
  19. H. Zhang, W. Qi, Z. Hu, and Y. Song, “Planning Hydrogen Refueling Stations with Coordinated On-Site Electrolytic Production,” IEEE PES General Meeting 2017, Chicago, IL, 2017, pp. 1-5. DOI: 10.1109/PESGM.2017.8274203
  20. S. Bae, H. Zhang, D. Wang, C. Sheppard, and S. Saxena, “Optimal Bidding Strategy for V2G Regulation Services under Uncertainty,” IEEE PES General Meeting 2017, Chicago, IL, 2017, pp. 1-5. DOI: 10.1109/PESGM.2017.8274706
  21. H. Zhang, Z. Hu, S. J. Moura, Y. Song, “Coordination of V2G and Distributed Wind Power Using the Storage-like Aggregate PEV Model,” 2016 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Minneapolis, MN, 2016, pp. 1-5. DOI: 10.1109/ISGT.2016.7781246
  22. H. Zhang, W. Tang, Z. Hu, Y. Song, Z. Xu, L. Wang, “A Method for Forecasting the Spatial and Temporal Distribution of PEV Charging Load,” 2014 IEEE PES General Meeting – Conference & Exposition, National Harbor, MD, 2014, pp. 1-5. DOI: 10.1109/PESGM.2014.6939167