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PERFORMANCES

  • International Journals (SCIE)

[10] S. Lee, P. Prabawa and D.-H. Choi, “Joint peak power and carbon emission shaving in active distribution systems using carbon emission flow-based deep reinforcement learning,” Applied Energy, vol. 379, Feb. 2025, doi: 10.1016/j.apenergy.2024.124944 (Top 10% Journal in JCR, IF: 10.1).

[9] S. Lee and D.-H. Choi, “Learning and unlearning to operate profitable secure electric vehicle charging,” IEEE Transactions on Industrial Informatics, vol. 20, no. 9, pp. 11213-11223, Sept. 2024, doi: 10.1109/TII.2024.3396524 (Top 5% Journal in JCR, IF: 11.7).

[8] S. Lee and D.-H. Choi, “Multilevel deep reinforcement learning for secure reservation-based electric vehicle charging via differential privacy and energy storage system,” IEEE Transactions on Vehicular Technology, vol. 73, no. 8, pp. 11097-11109, Aug. 2024, doi: 10.1109/TVT.2024.3372517 (Top 20% Journal in JCR, IF: 6.8).

[7] S. Lee and D.-H. Choi, “Three-stage deep reinforcement learning for privacy-and safety-aware smart electric vehicle charging station scheduling and volt/VAR control,” IEEE Internet of Things Journal, vol. 11, no. 5, pp.8578-8589, Mar. 2024, doi:10.1109/JIOT.2023.3319588 (Top 5% Journal in JCR, IF: 10.6).

[6] S. Lee and D.-H. Choi, “Two-stage scheduling of smart electric vehicle charging stations and inverter-based volt-VAR control using a prediction error-integrated deep reinforcement learning method,” Energy Reports, vol. 10, pp. 1135-1150, Nov. 2023, doi:10.1016/j.egyr.2023.07.054 (IF: 5.2).

[5] S. Lee and D.-H. Choi, “Federated reinforcement learning for energy management of multiple smart homes with distributed energy resources,” IEEE Transactions on Industrial Informatics, vol. 18, no. 1, pp. 488-497, Jan. 2022, doi:10.1109/TII.2020.3035451 (Top 5% Journal in JCR, IF: 12.3, Highly Cited Paper in Web of Science).

[4] S. Lee and D.-H. Choi, “Dynamic pricing and energy management for profit maximization in multiple smart electric vehicle charging stations: A privacy-preserving deep reinforcement learning approach,” Applied Energy, vol. 304, pp. 117754, Dec. 2021, doi:10.1016/j.apenergy.2021.117754 (Top 10% Journal in JCR, IF: 11.4).

[3] S. Lee, L. Xie and D.-H. Choi, “Privacy-preserving energy management of a shared energy storage system for smart buildings: A federated deep reinforcement learning approach,” Sensors, vol. 21, no. 14, Jul. 2021, doi:10.3390/s21144898 (IF: 3.8).

[2] S. Lee and D.-H. Choi, “Energy management of smart home with home appliances, energy storage system and electric vehicle: A hierarchical deep reinforcement learning approach,” Sensors, vol. 20, no. 7, Apr. 2020, doi:10.3390/s20072157 (IF: 3.5).

[1] S. Lee and D.-H. Choi, “Reinforcement learning-based energy management of smart home with rooftop solar photovoltaic system, energy storage system, and home appliances,” Sensors, vol. 19, no. 18, Sept. 2019, doi:10.3390/s19183937 (IF: 3.2).

  • Domestic Conferences

[13] S. Lee and D.-H. Choi, “Robust deep reinforcement learning-based privacy and safety-aware smart energy management system” in 2023 Fall Smart Grid Workshop.

[12] Y. Choi, S. Lee and D.-H. Choi, “An energy cost minimization algorithm considering peak shaving under energy uncertainties: A distributionally robust optimization approach” in 2nd Korea Energy Conference 2023 (Best Paper Award).

[11] S. Lee and D.-H. Choi, “Discrete differential privacy and deep reinforcement learning-based privacy-preserving algorithm for electric vehicles” in 54th KIEE Summer Conference 2023.

[10] U.-K. Kim, S. Lee and D.-H. Choi, “Distributionally robust optimization-based energy management system for peak shaving and energy cost minimization” in 54th KIEE Summer Conference 2023 (Best Paper Award).

[9] Y. Choi, S. Lee and D.-H. Choi, “Distributionally robust optimization-based cost-efficient and privacy-preserving energy management system using energy storage system” in 54th KIEE Summer Conference 2023.

[8] S. Lee and D.-H. Choi, “Cost-efficient target estimation coordinated deep reinforcement learning-based privacy-preserving energy management system for energy storage system” in 2023 Spring Smart Grid Workshop.

[7] Y. Choi, S. Lee and D.-H. Choi, “Privacy leakage from energy consumption data: A machine learning-based investigation” in 2023 Spring Smart Grid Workshop.

[6] S. Lee and D.-H. Choi, “A Differential privacy and deep reinforcement learning-based energy privacy management system” in 1st Korea Energy Conference 2022.

[5] S. Lee and D.-H. Choi, “Safe deep reinforcement learning for electric vehicle charging station energy management system” in 53rd KIEE Summer Conference 2022.

[4] S. Lee and D.-H. Choi, “Energy management system of smart home prosumer: A deep reinforcement learning approach” in 2021 Spring Smart Grid Workshop (Best Paper Award).

[3] S. Lee and D.-H. Choi, “Pricing and energy management system for smart electric vehicle charging stations: A deep reinforcement learning approach” in 52nd KIEE Summer Conference 2021.

[2] S. Lee and D.-H. Choi, “Privacy-preserving energy management system for shared energy storage system of smart buildings with deep reinforcement learning” in 2020 Fall Smart Grid Workshop.

[1] S. Lee and D.-H. Choi, “Energy management system of energy storage system in heterogeneuos environments using federated reinforcement learning” in 51st KIEE Summer Conference 2020.

  • Patents

3. “Multi-smart home energy management method and system based on federated reinforcement learning”, D.-H. Choi. and S. Lee, Korea Patent 10-2715322 (2024).

2. “HEMS optimization method and device using reinforcement learning”, D.-H. Choi. and S. Lee, Korea Patent 10-2480521 (2022).

1. “HEMS optimization method and apparatus using hierarchical deep reinforcement learning”, D.-H. Choi. and S. Lee, Korea Patent 10-2463146 (2022).

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