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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

Government projects
  1. Hongcai Zhang (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.
Industrial projects
  1. PI, “Non-parametric modeling and safe artificial intelligence technology for urban energy system operation and control,” Guangdong Power Grid, 2023-2026.
  2. PI, “Research on forecasting and coordinated operation technology of multi-energy systems in low-carbon parks,” China Southern Power Grid Research Institute, 2023-2024.
  3. PI, “Operation strategy of district cooling system with ice storage systems,” State Power Investment Corporation — Zhuhai Hengqin Energy Development Corporation, 2022.
  4. Co-PI, “Macao EV and charging infrastructure development plan,” Companhia de Electricidade de Macau (CEM), 2021.

PhD thesis

  1. Hongyi Li, “Blockchain-Assisted Distributed Coordination of Heterogeneous Demand-Side Flexible Resources,” University of Macau, 2024.
  2. Peipei Yu (co-advise), “District Cooling System Control for Providing Power Grid Services Based on Safe Reinforcement Learning,” University of Macau, 2024.
  3. Ge Chen (co-advise), “Data-driven Operation of Active Distribution Networks with Incomplete Network Information,” University of Macau, 2023.
  4. Jiatu Hong (co-advise), “Distributed Control of Large-scale Thermostatically Controlled Loads for Improving the Flexibility of Urban Power Systems,” University of Macau, 2023.
  5. Hongcai Zhang, “Planning and Operation of Plug-in Electric Vehicle Charging Infrastructure Considering Transportation Network Constraints,” Tsinghua University, 2018.

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. P. Yu, Z. Wang, H. Zhang, and Y. Song, “Safe Reinforcement Learning for Power System Control: A Review,” 2024. Download: arXiv:2407.00681
In press
  1. G. Chen, J. Qin, and H. Zhang, “Model-Free Self-Supervised Learning for Dispatching Distributed Energy Resources,” to appear in IEEE Transactions on Smart Grid, 2024. DOI: 10.1109/TSG.2024.3471492
  2. Z. Wang, H. Zhang, R. Yang, and Y. Chen, “Improving Model Generalization for Short-Term Customer Load Forecasting with Causal Inference,” to appear in IEEE Transactions on Smart Grid, 2024. DOI: 10.1109/TSG.2024.3452490
  3. Y. Liu, D. Xie, and H. Zhang, “Frequency-Constrained Unit Commitment Considering Typhoon-Induced Wind Farm Cutoff and Grid Islanding Events,” to appear in Journal of Modern Power Systems and Clean Energy, 2024. DOI: 10.35833/MPCE.2024.000067
  4. Z. Hu, H. Zhang, R. Yang, Y. Chen, and H. Wu, “Optimal Power Flow Based on Physical-Model-Integrated Neural Network with Worth-Learning Data Generation,” to appear in CSEE Journal of Power and Energy Systems, 2024. Download: arXiv:2301.03766
  5. L. Kong, H. Zhang, D. Xie, and N. Dai, “Leveraging Electric Vehicles to Enhance Resilience of Interconnected Power-Transportation System Under Natural Hazards,” IEEE Transactions on Transportation Electrification, 2024. DOI: 10.1109/TTE.2024.3400289
  6. Z. Yang, H. Liu, and H. Zhang, “Dynamic Collaborative Pricing for Managing Refueling Demand of Hydrogen Fuel Cell Vehicles,” IEEE Transactions on Transportation Electrification, 2024. DOI: 10.1109/TTE.2024.3381236
  7. B. Zou, G. Chen, H. Zhang, and Y. Song, “Improved Divergence-based Distributionally Robust Chance-Constrained Scheduling for Geo-distributed Internet Data Centers,” CSEE Journal of Power and Energy Systems, 2024. DOI: 10.17775/CSEEJPES.2023.05550
  8. D. Liu, M. Zhou, Q. Wu, H. Zhang, and Y. Wang, “Inverse function-based DC power flow model considering network loss and voltage magnitudes,” CSEE Journal of Power and Energy Systems, 1-9, 2024. DOI: 10.17775/CSEEJPES.2023.02500
  9. P. Yu, H. Zhang, and Y. Song, “Equivalent System Model of District Cooling System in Frequency Domain to Provide Primary Frequency Regulation,” CSEE Journal of Power and Energy Systems, 1-10, 2023. DOI: 10.17775/CSEEJPES.2023.02350
  10. 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. DOI: 10.17775/CSEEJPES.2022.06580
  11. Q. Hou, G. Chen, N. Dai, and H. Zhang, “Distributionally Robust Chance-Constrained Optimization for Soft Open Points Operation in Active Distribution Networks,” CSEE Journal of Power and Energy Systems, 2022. DOI: 10.17775/CSEEJPES.2021.02110
Published
  1. P. Yu, H. Zhang, and Y. Song, “Adaptive Tie-line Power Smoothing with Renewable Generation Based on Risk-aware Reinforcement Learning,” IEEE Transactions on Power Systems, vol. 39, no. 6, pp. 6819-6832, 2024. DOI: 10.1109/TPWRS.2024.3379513
  2. G. Chen, H. Zhang, J. Qin, and Y. Song, “Replicating Power Flow Constraints Using Only Smart Meter Data for Coordinating Flexible Sources in Distribution Network,” IEEE Transactions on Sustainable Energy, vol. 15, no. 4, pp. 2428-2443, 2024. DOI: 10.1109/TSTE.2024.3421929
  3. L. Yang, H. Li, H. Zhang, Q. Wu, and X. Cao, “Stochastic-Distributionally Robust Frequency-Constrained Optimal Planning for an Isolated Microgrid,” IEEE Transactions on Sustainable Energy, vol. 15, no. 4, pp. 2155-2169, 2024. DOI: 10.1109/TSTE.2024.3404434.
  4. J. Su, H. Zhang, H. Liu, and D. Liu, “Lyapunov-based distributed secondary frequency and voltage control for distributed energy resources in islanded microgrids with expected dynamic performance improvement,” Applied Energy, vol. 377, Part C, No. January, p. 124539, 2025. DOI: 10.1016/j.apenergy.2024.124539
  5. H. Li, H. Zhang, J. Zhang, Q. Wu, and C. K. Wong, “A frequency-secured planning method for integrated electricity-heat microgrids with virtual inertia suppliers,” Applied Energy, vol. 377, Part B, No. January, p. 124540, 2025. DOI: 10.1016/j.apenergy.2024.124540
  6. P. Yu, H. Zhang, Z. Hu, and Y. Song, “Voltage control of distribution grid with district cooling systems based on scenario-classified reinforcement learning,” Applied Energy, vol. 377, Part B, No. January, p. 124415, 2025. DOI: 10.1016/j.apenergy.2024.124415
  7. S. Chen, H. Cheng, H. Zhang, S. Lv, Z. Wei, and Y. Jin, “Privacy-preserving coordination of power and transportation networks using spatiotemporal GAT for predicting EV charging demands,” Applied Energy, vol. 377, Part A, No. January, p. 124391, 2025. DOI: 10.1016/j.apenergy.2024.124391
  8. L. He, N. Ke, R. Mao, W. Qi, and H. Zhang, “From Curtailed Renewable Energy to Green Hydrogen: Infrastructure Planning for Hydrogen Fuel-Cell Vehicles,” Manufacturing & Service Operations Management, vol. 26, no. 5, pp. 1587-1979, 2024. DOI: 10.1287/msom.2022.0381
  9. T. Qian, Z. Liang, C. Shao, H. Zhang, Q. Hu, and Z. Wu, “Offline DRL for Price-Based Demand Response: Learning From Suboptimal Data and Beyond,” IEEE Transactions on Smart Grid, vol. 15, no. 5, pp. 4618-4635, 2024. DOI: 10.1109/TSG.2024.3382293
  10. J. Su, H. Zhang, C. K. Wong, L. Yu, and Z. Tan, “Hierarchical Control of Inverter Air Conditioners for Frequency Regulation Service of Islanded Microgrids with Fair Power Participation,” IEEE Transactions on Smart Grid, vol. 15, no. 5, pp. 4602-4617, 2024. DOI: 10.1109/TSG.2024.3382247
  11. Z. Wang, and H. Zhang, “Customized Load Profiles Synthesis for Electricity Customers Based on Conditional Diffusion Models,” IEEE Transactions on Smart Grid, vol. 15, no. 4, pp. 4259-4270, 2024. DOI: 10.1109/TSG.2024.3366212
  12. H. Li, Q. Wu, L. Yang, H. Zhang, and S. Jiang, “Distributionally Robust Negative-Emission Optimal Energy Scheduling for Off-grid Integrated Electricity-Heat Microgrid,” IEEE Transactions on Sustainable Energy, vol. 15, no. 2, pp. 803-818, 2024. DOI: 10.1109/TSTE.2023.3306360
  13. R. Han, Q. Hu, H. Zhang, Y. Ge, X. Quan, and Z. Wu, “Robust allocation of distributed energy storage systems considering locational frequency security,” International Journal of Electrical Power & Energy Systems, vol. 157, p. 109903, 2024. DOI: 10.1016/j.ijepes.2024.109903
  14. Y. Liu, D. Liu, and H. Zhang, “Stochastic Unit Commitment with High-penetration Offshore Wind Power Generation in Typhoon Scenarios,” Journal of Modern Power Systems and Clean Energy, vol. 12, no. 2, pp. 535-546, 2024. DOI: 10.35833/MPCE.2023.000019
  15. T. Zeng, H. Zhang, S. J. Moura, and Z. M. Shen, “Economic and Environmental Benefits of Automated Electric Vehicle Ride-Hailing Services in New York City,” Scientific Reports, vol. 14, p. 4180, 2024.  DOI: 10.1038/s41598-024-54495-x
  16. Y. Song, G. Chen, and H. Zhang, “Constraint learning-based optimal power dispatch for active distribution networks with extremely imbalanced data,” CSEE Journal of Power and Energy Systems, vol. 10, no. 1, pp. 51-65, 2024. DOI: 10.17775/CSEEJPES.2023.05970
  17. H. Zhang, X. Hu, Z. Hu, and S. J. Moura, “Sustainable plug-in electric vehicle integration into power systems,” Nature Reviews Electrical Engineering, vol. 1, pp. 35-52, 2024. DOI: 10.1038/s44287-023-00004-7 (Invited, cover page paper)
  18. Z. Wang, and H. Zhang, “Customer baseline load estimation for virtual power plants in demand response: An attention mechanism-based generative adversarial networks approach,” Applied Energy, vol. 357, no. March, p. 122544, 2024. DOI: 10.1016/j.apenergy.2023.122544
  19. G. Chen, H. Zhang, and Y. Song, “Efficient constraint learning for data-driven active distribution network operation,” IEEE Transactions on Power Systems, vol. 39, no. 1, pp. 1472–1484, 2024. DOI: 10.1109/TPWRS.2023.3251724
  20. 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, vol. 39, no. 1, pp. 40–52, 2024. DOI: 10.1109/TPWRS.2023.3237888 (ESI highly cited)
  21. Y. Song, P. Yu, and H. Zhang, “Optimal Reinforcement Learning Control of a District Cooling System based on Compound Secondary Sampling under Real-time Electricity Prices,” Sci Sin Tech, vol. 53, pp. 1699–1712, 2023. (in Chinese) DOI: 10.1360/SST-2022-0362
  22. J. Su, H. Zhang, H. Liu, L. Yu, and Z. Tan, “Membership-function-based Secondary Frequency Regulation for Distributed Energy Resources in Islanded Microgrids with Communication Delay Compensation,” IEEE Transactions on Sustainable Energy, vol. 14, no. 4, pp. 2274–2293, 2023. DOI: 10.1109/TSTE.2023.3266295
  23. H. Li, H. Hui, and H. Zhang, “Decentralized Energy Management of Microgrid Based on Blockchain-Empowered Consensus Algorithm with Collusion Prevention,” IEEE Transactions on Sustainable Energy, vol. 14, no. 4, pp. 2260–2273, 2023. DOI: 10.1109/TSTE.2023.3258452
  24. H. Li, H. Hui, and H. Zhang, “Consensus-based Energy Management of Microgrid with Random Packet Drops,” IEEE Transactions on Smart Grid, vol. 14, no. 5, pp. 3600–3613, 2023. DOI: 10.1109/TSG.2023.3241653
  25. 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, vol. 14, no. 5, pp. 3535–3549, 2023. DOI: 10.1109/TSG.2022.3231592
  26. J. Zhang, J. Cai, H. Zhang, and T. Chen, “NSGA-III integrating eliminating strategy and dynamic constraint relaxation mechanism to solve many-objective optimal power flow problem,” Applied Soft Computing, vol. 146, no. October, p. 110612, 2023. DOI: 10.1016/j.asoc.2023.110612
  27. H. Li, H. Hui, and H. Zhang, “Blockchain-assisted Virtual Power Plant Framework for Providing Operating Reserve with Various Distributed Energy Resources,” iEnergy, vol. 2, no. 2, pp. 133-142, 2023. DOI: 10.23919/IEN.2023.0013 (Highlight Paper)
  28. 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, vol. 14, no. 4, pp. 2762-2773, 2023. DOI: 10.1109/TSG.2022.3220732
  29. X. Shen, Q. Wu, H. Zhang, and L. Wang, “Optimal Planning for Electrical Collector System of Offshore Wind Farm with Double-sided Ring Topology,” IEEE Transactions on Sustainable Energy, vol. 14, no. 3, pp. 1624-1633, 2023. DOI: 10.1109/TSTE.2023.3241357
  30. L. Kong, H. Zhang, W. Li, H. Bai, and N. Dai, “Spatial-temporal Scheduling of Electric Bus Fleet in Power-Transportation Coupled Network,” IEEE Transactions on Transportation Electrification, vol. 9, no. 2, pp. 2969-2982, 2023. DOI: 10.1109/TTE.2022.3214335
  31. P. Yu, H. Zhang, and Y. Song, “District Cooling System Control for Providing Regulation Services based on Safe Reinforcement Learning with Barrier Functions,” Applied Energy, vol. 347, no. October, p. 121396, 2023. DOI: 10.1016/j.apenergy.2023.121396
  32. 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, vol. 14, no. 3, pp. 2189-2201, 2023. DOI: 10.1109/TSG.2022.3219109
  33. X. Yan, H. Zhang, C. Gu, N. Liu, F. Li, and Y. Song, “Truncated Strategy Based Dynamic Network Pricing for Energy Storage,” Journal of Modern Power Systems and Clean Energy, vol. 11, no. 2, pp. 544-552, 2023. DOI: 10.35833/MPCE.2021.000631
  34. 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
  35. 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
  36. 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 
  37. 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
  38. 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
  39. 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
  40. 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
  41. 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
  42. G. Chen, B. Yan, H. Zhang, D. Zhang, and Y. Song, “Time-efficient strategic power dispatch for district cooling systems considering 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
  43. 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
  44. 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
  45. 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
  46. 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 (Best paper award)
  47. 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
  48. 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 (ESI highly cited)
  49. 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
  50. 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
  51. 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
  52. 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
  53. 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
  54. 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 Grid, vol. 12, no. 4, pp. 3043-3055, July 2021. DOI: 10.1109/TSG.2021.3052515
  55. 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 Systems, vol. 36, no. 4, pp. 3340-3348, July 2021. DOI: 10.1109/TPWRS.2020.3045723
  56. 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
  57. 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
  58. 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 (ESI highly cited)
  59. 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
  60. 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 Grid, vol. 11, no. 5, pp. 4236-4248,  September 2020. DOI: 10.1109/TSG.2020.2991232
  61. 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
  62. 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
  63. H. Zhang, Z. Hu, and Y. Song, “Power and Transport Nexus: Routing Electric Vehicles to Promote Renewable Power Integration,” IEEE Transactions on Smart Grid, vol. 11, no. 4, pp. 3291-3301, July 2020. DOI: 10.1109/TSG.2020.2967082
  64. 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
  65. 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
  66. 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
  67. 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 (ESI highly cited)
  68. 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
  69. Z. Lin, Z. Hu, H. Zhang, and Y. Song, “Optimal ESS allocation in distribution network using accelerated generalised Benders decomposition,” IET Generation, Transmission & Distribution, vol. 13, no. 13, pp. 2738-2746, 2019. DOI: 10.1049/iet-gtd.2018.5863
  70. 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
  71. 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
  72. 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
  73. 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
  74. 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)
  75. 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
  76. 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
  77. 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
  78. 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
  79. 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
  80. 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
  81. 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
  82. 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
  83. 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
  84. 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
  85. 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)
  86. 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)
  87. 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)
  88. 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)
  89. 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)
  90. 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)
  91. 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. L. Pan, and H. Zhang, “Competitive Pricing of Electric Vehicle Charging in Coupled Power and Transportation Network,” 2024 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific), Xi’an, China, 2024, pp. 83-88. DOI:10.1109/ITECAsia-Pacific63159.2024.10738577 (Best Paper Award)
  2. Z. Wang, H. Zhang, B. Zhao, W. Zhao, and T. Mao, “When Pre-Training Model Meets Smart Meter Data Applications: A Preliminary Trial of General Way,” 2024 IEEE Power & Energy Society General Meeting (PESGM), pp. 1-5, Seattle, WA, USA, July 2024. DOI:10.1109/PESGM51994.2024.10688647
  3. L. Kong, H. Zhang, and N. Dai, “Resilience Evaluation of Power-transportation Coupled Network with Electric Vehicles’ Restoration Service,” 2024 IEEE Transportation Electrification Conference and Expo (ITEC), Chicago, IL, USA, June 2024. DOI: 10.1109/ITEC60657.2024.10599080
  4. H. Li, H. Hui, and H. Zhang, “Consensus-based Coordination of Battery Energy Storage Systems for Frequency Regulation Service,” 7th IEEE Conference on Energy Internet and Energy System Integration (EI2), Hangzhou, China, Dec 2023. DOI:10.1109/EI259745.2023.10513161
  5. J. Zhang, L. Kong, and H. Zhang, “Coordinated Ride-hailing Order Scheduling and Vehicle to Grid for Autonomous Electric Vehicles Based on Independent Proximal Policy Optimization,” 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific), Chiang Mai, Thailand, 2023, pp. 1-6. DOI: 10.1109/ITECAsia-Pacific59272.2023.10372331
  6. J. Zhang, L. Kong, and H. Zhang, “Coordinated Ride-hailing Order Scheduling and Charging for Autonomous Electric Vehicles Based on Deep Reinforcement Learning,” 2023 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia), Chongqing, China, 2023. DOI: 10.1109/ICPSAsia58343.2023.10294915
  7. H. Li, H. Zhang, J. Zhang, and C. K. Wong, “Frequency-Constrained Dispatching Method for an Integrated Electricity-Heat Microgrid with Synergic Primary Frequency Regulation Resources,” 2023 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia), Chongqing, China, 2023. DOI: 10.1109/ICPSAsia58343.2023.10294867
  8. T. Wu, H. Hui and H. Zhang, “Hardware-in-the-loop Towards Frequency Regulation Service by HVACs with Real-time Digital Simulator,” 2023 8th Asia Conference on Power and Electrical Engineering (ACPEE), Tianjin, China, 2023, pp. 1052-1057. DOI: 10.1109/ACPEE56931.2023.10135956 (Best Presentation Award)
  9. Z. Wang, H. Li, H. Hui and H. Zhang, “A Local Energy Market for Industrial Parks Considering Carbon Emission Quota,” 2023 8th Asia Conference on Power and Electrical Engineering (ACPEE), Tianjin, China, 2023, pp. 1118-1123. DOI: 10.1109/ACPEE56931.2023.10135954
  10. Z. Liu, D. Liu and H. Zhang, “Research on the Maximum Proportion of Renewable Energy Considering Frequency Security under Different Disturbance Events,” 2023 Panda Forum on Power and Energy (PandaFPE), Chengdu, China, 2023, pp. 49-54. DOI: 10.1109/PandaFPE57779.2023.10140889
  11. 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. DOI:10.1109/EI256261.2022.10116339 (Best Paper Award)
  12. 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. DOI:10.1109/EI256261.2022.10117280
  13. 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. DOI:10.1109/EI256261.2022.10117220
  14. 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
  15. 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
  16. 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
  17. 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)
  18. 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
  19. 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
  20. 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
  21. 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
  22. 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
  23. 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
  24. 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
  25. Y. Zhao, H. Gao, H. Li, H. Zhang, and K. W. Lao, “Stackelberg Game Based Optimal Multi-energy Management 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
  26. 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
  27. 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
  28. 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
  29. 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
  30. 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
  31. 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
  32. 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
State Key Laboratory of Internet of Things for Smart City
University of Macau
Department of Electrical and Computer Engineering
Faculty of Science and Technology
Copyright ©2022 Hongcai Zhang