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PERFORMANCES

  • Ongoing works

1) "Distributionallty robust scheduling for carbon-aware operarion of electric/hydrogen vehicle charging station" (Under review)

2) "Multi-agent deep reinforcement learning for safety-constrained energy storage system operation"

3) "Cyber/Physical safety-aware Volt/VAR control algorithm using multi-agent deep reinforcement learning"

4) "Low-carbon EV charging using mobile energy storage system"

  • International Journals (SCIE)

[12] H. Kim, S. Lee  and D.-H. Choi ,  “Energy management of PV-enabled battery charging swapping stations for electric vehicles in active power distribution systems under uncertainty, ” Energies, vol. 19, no. 5, Feb. 2026, doi: 10.3390/en19051223 (IF: 3.2). 

[11] M. M. I. Mahin, S. Lee  and D.-H. Choi ,  “Optimal scheduling of multi-storage tank-based hydrogen refueling stations in distribution systems via joint power and hydrogen peak shaving, ” IEEE Access, vol. 13, pp. 115533-115547, 2025, doi: 10.1109/ACCESS.2025.3584881 (IF: 3.6). 

[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).

  • SCOPUS

[3] M.-G. Lee and S. Lee, “Optimal carbon-aware operation of distribution networks considering PV uncertainty via Wasserstein-based chance-constrained programming,” The Transactions of the Korean Institute of Electrical Engineering, vol. 74, no. 12, pp. 2163-2172, Dec. 2025, doi:10.5370/KIEE.2025.74.12.2163.

[2] M.-G. Lee, C. Moon and S. Lee, “Energy management system for smart electric vehicle charging stations under multiple uncertainties: A Wasserstein metric-based distributionally robust optimization approach,” The Transactions of the Korean Institute of Electrical Engineering, vol. 74, no. 11, pp. 1935-1943, Nov. 2025, doi:10.5370/KIEE.2025.74.11.1935.

[1] M.-G. Lee and S. Lee, “Analysis of carbon-aware optimal power flow in distribution system under objective function variations,” The Transactions of the Korean Institute of Electrical Engineering, vol. 74, no. 11, pp. 1775-1783, Nov. 2025, doi:10.5370/KIEE.2025.74.11.1775. 

  • Domestic Conferences

[18] J.-H. Park, G.-Y. Seong and S. Lee, "Impact analysis of photovoltaic generation variability on the energy operation strategy of electric vehicle battery charging swapping station" in 2026 Korea Institute of Electrical Engineers (KIEE) Spring Conference for Society A.

[17] S. Lee, M.-G. Lee, J. Cha, “Cyber/Physical-aware safe electric vehicle charging station scheduling algorithm using robust deep reinforcement learning” in 56th KIEE Summer Conference 2025 (Best Paper Award).

[16] S. Park and S. Lee, “Distributionally robust smart home energy management system under PV uncertainties” in 56th KIEE Summer Conference 2025.

[15] J. Cha and S. Lee, “Distributionally robust low-carbon smart distribution system operation under PV uncertainties” in 56th KIEE Summer Conference 2025 (Best Paper Award).

[14] J. Cha and S. Lee, "Peak shaving algorithm based on low-carbon smart distribution system operation" in 2025 Korea Institute of Electrical Engineers (KIEE) Spring Conference for Society A.

[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

4. “Management method and apparatus for maximizing profits in multiple EVCS”, D.-H. Choi. and S. Lee, Korea Patent 10-803358 (2025).

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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