Education

• Ph.D in Information Science, Japan Advanced Institute of Science and Technology, Japan 

• Ph.D in Engineering and Technology, Sirindhorn International Institute of Technology, Thammasat University

• M.Eng. in Information and Communication Technology for Embedded Systems, Sirindhorn International Institute of Technology, Thammasat University (TAIST-Tokyo Tech Full-Scholarship)

• B.Eng. in Electrical Engineering, Kasetsart University (PEA Full-Scholarship)

Research Experience 

• Optimal Design of Distributed Energy Resources System; Japan Advanced Institute of Science and Technology (JAIST),  Ishikawa, Japan — Doctoral Student in Information Science — 2018-present 

• Energy Management in Cyber-Physical System using Artificial Intelligence Techniques; Sirindhorn International Institute of Technology (SIIT), — Doctoral Student in Engineering and Technology — 2018-present 

• Impact of Power Consumption Stock Price Prediction in Industrial Sector by Artificial Neural Network (ANN); — M.Eng., Information and Communication Technology for Embedded System (ICTES) — 2015-2017 

• Machine Learning (Internship) at Japan Advance Institute of Science and Technology (JAIST), Ishikawa, Japan — May-Aug, 2016 

Experience 

• Data Engineering for Energy Management — 2015-present 

• Power Substation Design — Electrical Engineer — 2013-present 

• ได้รับรางวัล The best paper award ในงานวิชาการ KICSS2016 ณ ประเทศอินโดนีเซีย

• ได้รับรางวัล บทความดีเด่น ในงานวิชาการ PEACON & INNOVATION 2019 และ ได้นำเสนอบทความเดียวกัน ที่งาน MEPS2019 ณ ประเทศโปแลนด์

• เป็นวิทยากรรับเชิญบรรยายหัวข้อเกี่ยวกับ Data Science สำหรับ Energy Management ในงาน Future Energy 2019 ที่ อิมแพคฯ 

Teaching Experience

• Course "Python for Data Science" for PEA's innovators - Special Group 1 -- Jun, 2023

• Instructor of "Understanding Blockchain Technology" online course in FutureSkill.co — 2019 - present 

• Instructor of "Data Science for Everyone" online course in FutureSkill.co — 2019 - present 

• Instructor of "Basic Skill for Python" course provided by FutureSkill.co — 2020 

• Lecturer of Computational Tools in Electrical Engineering (MATLAB)— October - December, 2019

• Lecturer of High School Mathematics— 2015 - 2017

• Lecturer of Mathematics and Physics for IGCSE—  2017

Publications 

• A. Kwangkaew, S. Skolthanarat, C. Charoenlarpnopparut and M. Kaneko, "Optimal Location and Sizing of Renewable Distributed Generators for Improving Robust Voltage Stability Against Uncontrollable Reactive Compensation," in IEEE Access, vol. 11, pp. 52260-52274, 2023, doi: 10.1109/ACCESS.2023.3279716.

• Kwangkaew, A.; Javaid, S.; Charoenlarpnopparut, C.; Kaneko, M. Optimal Location and Sizing of Renewable Distributed Generators for Improving Voltage Stability and Security Considering Reactive Power Compensation. Energies 2022, 15, 2126. https://doi.org/10.3390/en15062126 

• A. Kwangkaew, W. Viriyavit, and C. Charoenlarpnopparut, “Optimal Size Of Energy Storage Systems In Grid-Integrated Renewable Energy Systems,” The 34th International Conference on Information Modelling and Knowledge Bases (EJC2024), June 2024, Tokyo, Japan. 

• A. Kwangkaew, S. Javaid, C. Charoenlarpnopparut, and Mineo Kaneko, “A New Approach to Renewable Energy Sources Allocation  considering Robustness against Fluctuations,” International Conference on Smart Grids and Energy Systems (SGES2020), 23-26 November 2020, Perth, Australia.

• A. Kwangkaew, T. Racharak, and C. Charoenlarpnopparut, “Toward Forecast Techniques in Optimal Sizing of Energy Storage System with Volatile Energy Sources for Hybrid Renewable Energy System,” International Conference on Smart Grids and Energy Systems (SGES2020), 23-26 November 2020, Perth, Australia.

• A. Kwangkaew, “Forecast Techniques Evaluation for Optimal Energy Storage System Sizing of Hybrid Renewable Energy System,” in Provincial Electricity Authority Conference 2020 (PEACON2020).

• A. Kwangkaew, S. Javaid, C. Charoenlarpnopparut, and Y. Tan, “Hybrid Approach for Short-term Wind Power Prediction to Increase Flexibility of Renewable Integration in Power System,” in Modern Electric Power Systems 2019 (MEPS2019), 9-12 September 2019, Wroclaw, Poland.

• A. Kwangkaew, “Developing Deep Learning for Short-term Wind Prediction of Renewable Integration in Power System,” in Provincial Electricity Authority Conference 2019 (PEACON2019).

• A. Kwangkaew and G. Pongthanisorn, “Approach for Estimating Cost of Control Cables in Substation using Artificial Intelligence Techniques,” in Provincial Electricity Authority Conference 2018 (PEACON2018).

• A. Kwangkaew, and C. Charoenlarpnopparut, “A Novel Hybrid Approach for Estimating Cost of Power Substation for Electricity Utility Sectors,” Conference of Power and Electricity Supply Industry 2018 (CEPSI2018), 17-19 September 2018, Kuala Lumpur, Malaysia.

• A. Kwangkaew, V. Sornlertlamvanich, I. Kumazawa, and S. Skolthanarat, “ANN approach for predicting economic trends based on electric energy consumption during natural disaster period,” in Proceedings - 11th 2016 International Conference on Knowledge, Information and Creativity Support Systems (KICSS2016), Yogyakarta, Indonesia, pp. 200-204.

• Akanit Kwangkaew; Virach Sornlertlamvanich; Yukari Shirota; and Takako Hashimoto (2016). Electricity consumption in industrial segment on time series analysis. In Proceedings of the 2016 International Workshop on Smart Info- Media Systems in Asia (SISA2016), 14-17 September 2016, Phranakhon Si Ayutthaya, Thailand, pp. 1-5. [link]