Keon Baek | Data analysis | Best Researcher Award

Keon Baek | Chosun University | South Korea

Keon Baek is a dedicated Data Scientist and Electrical Engineer based in Gwangju, South Korea ¹ 🇰🇷. With a strong academic background and practical experience, he focuses on power market analysis, policy design, and technology development through insightful data analysis 📊. His research interests include consumer behavior 💡, demand flexibility 🔄, market and policy implications 🏛️, and the growing field of vehicle electrification 🚗⚡. Keon’s passion lies in leveraging data to shape the future of sustainable energy.

Professional profile : 

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Summary of Suitability : 

Keon Baek, a dedicated Data Scientist and Electrical Engineer from Gwangju, South Korea, is an excellent candidate for the Best Researcher Award. With a robust academic foundation and a wealth of hands-on experience, Keon has demonstrated significant contributions to the fields of power market analysis, policy design, and technology development. His expertise lies in using data to inform decisions around sustainable energy, which aligns perfectly with the award’s criteria for groundbreaking research that drives innovation and societal impact.

Education :

• Ph.D. (Power System & Economics) – Gwangju Institute of Science and Technology (2020.03 – 2023.02) ⚡💰
• M.S. (Power System & Economics) – Gwangju Institute of Science and Technology (2018.03 – 2020.02) 💡📈
• B.S. (Electrical Engineering) – Korea Advanced Institute of Science and Technology (2004.03 – 2011.02) ⚙️🔌

Experience :

• Assistant Professor, Dept. of Electrical Engineering – Chosun University (2023. 09 – 2023. 08) 👨‍🏫💡
• Post-doc., Research Institute for Solar and Sustainable Energies (RISE) – Gwangju Institute of Science and Technology (2023. 02 – 2023.08) ☀️🌱
• Electric Engineer, Distribution Transformer Division – Hyundai (2017. 04 – 2018. 07) 🏭⚡
• Engineer, Offshore Plant Engineering Center – Korea Shipbuilding & Offshore Engineering (2015. 02 – 2017. 03) 🚢🌊
• Associate Researcher, Wind Power System Research Center – Korea Shipbuilding & Offshore Engineering (2011. 02 – 2015. 01)
• Publication Top NOTES :
  

  Resident Behavior Detection Model for Environment Responsive Demand Response :

  • Authors: K. Baek, E. Lee, J. Kim

  • Published in: IEEE Transactions on Smart Grid, 2021, Vol. 12, Issue 5, Pages 3980-3989

  • Citations: 35

  • Summary: This paper proposes a model for detecting resident behavior in smart grid environments, aiming to optimize demand response (DR) mechanisms. The approach focuses on adjusting electricity usage patterns by predicting and responding to residents’ behavior, enhancing both energy efficiency and grid reliability. This model is crucial for increasing the responsiveness and flexibility of demand response programs in residential areas.

  Evaluation of Demand Response Potential Flexibility in the Industry Based on a Data-Driven Approach :

  • Authors: E. Lee, K. Baek, J. Kim

  • Published in: Energies, 2020, Vol. 13, Issue 23, Article 6355

  • Citations: 28

  • Summary: This study assesses the potential flexibility of demand response programs in industrial settings using a data-driven approach. It evaluates how various industrial processes can be adjusted to provide flexibility in energy consumption without negatively impacting production efficiency. The research also explores the use of real-time data to enhance decision-making in demand response strategies, enabling more effective integration of renewable energy sources.

  Multi-Objective Optimization of Home Appliances and Electric Vehicles Considering Customer’s Benefits and Offsite Shared Photovoltaic Curtailment :

  • Authors: Y. Kwon, T. Kim, K. Baek, J. Kim

  • Published in: Energies, 2020, Vol. 13, Issue 11, Article 2852

  • Citations: 22

  • Summary: This paper discusses a multi-objective optimization approach for managing home appliances and electric vehicles (EVs) while considering customer benefits and photovoltaic (PV) energy curtailment. It focuses on maximizing the benefits to consumers by coordinating the use of home appliances and EVs with the availability of solar energy while reducing the waste of excess PV power. The study is significant for improving the efficiency of residential energy management systems.

  Stochastic Optimization-Based Hosting Capacity Estimation with Volatile Net Load Deviation in Distribution Grids : 

  • Authors: Y. Cho, E. Lee, K. Baek, J. Kim

  • Published in: Applied Energy, 2023, Vol. 341, Article 121075

  • Citations: 13

  • Summary: The research proposes a stochastic optimization method to estimate hosting capacity in distribution grids, accounting for the volatile nature of net load deviation. The study addresses challenges related to integrating renewable energy sources, such as solar and wind, into existing power grids. It develops a model that quantifies the grid’s capacity to absorb additional renewable energy without compromising stability, providing valuable insights for grid operators managing increasing renewable penetration.

  Datasets on South Korean Manufacturing Factories’ Electricity Consumption and Demand Response Participation :

  • Authors: E. Lee, K. Baek, J. Kim

  • Summary: This dataset publication presents detailed information on electricity consumption patterns and the participation of South Korean manufacturing factories in demand response programs. It provides real-world data that can be used to evaluate the effectiveness of demand response strategies and analyze consumption behaviors in industrial sectors. Researchers and energy managers can leverage this dataset to optimize industrial demand response programs and improve grid reliability.