E-mail : shryu_at_sogang.ac.kr
Biography
Seunghyoung Ryu received the B.S. and M.S. degree in the Electronic Engineering from Sogang University, South Korea in 2014 and 2016, respectively. He is working toward the Ph.D. degree in Electronic Engineering at the same university.
His research interests are transactive energy, energy data analysis, energy forecasting, machine learning and artificial intelligence in smart grid.
Publications
Journal papers
Gaussian Residual Bidding based Coalition for Two-settlement Renewable Energy Market
S. Ryu, S. Bae, J. Lee and H. Kim, IEEE Access, pp.43029 - 43038, Aug. 2018
Robust Operation of Energy Storage System with Uncertain Load Profiles
J. K. Kim, Y. Choi, S. Ryu, and H. Kim, Energies, pp.1-15, Mar. 2017.
Deep Neural Network based Demand Side Short-Term Load Forecasting
S. Ryu, J. Noh, and H. Kim, Energies, pp.1-20, Jan. 2017.
Customer Load Pattern Analysis using Clustering Techniques
S. Ryu, D. Oh, J. Noh and H.Kim, KEPCO Journal on Electric Power and Energy, pp.61-69, 2016
Data-Driven Baseline Estimation of Residential Buildings for Demand Response
S. Park, S. Ryu, Y. Choi, J. Kim and H. Kim, Energies, pp.10239-10259, 2015.
Selected Conference Proceeding
Short-Term Load Forecasting based on ResNet and LSTM
H. Choi, S. Ryu and H. Kim, IEEE SmartGridComm, 2018, pp.1-6.
Residential Load Profile Clustering via Deep Convolutional Autoencoder
S.Ryu, H. Choi, H. Lee, H. Kim, and V. W.S. Wong, IEEE SmartGridComm, 2018, pp 1-6.
Convolutional Autoencoder 기반 소규모 수용가 부하 프로파일 클러스터링에 대한 연구
류승형, 최현근, 이효섭, 김홍석, 한국통신학회 학술대회논문집, 22-24, 2017
Coalition-based Bidding Strategies for Integrating Renewable Energy Sources in Electricity Market
S. Bae, S. Ryu and H. Kim, IEEE Power and Energy Society General Meeting (PES-GM), 2017, pp.1-5.
시간 지연을 고려한 소규모 수용가 부하 프로파일 클러스터링
류승형, 김홍석, JCCI, 2017
Deep Neural Network Based Demand Side Short Term Load Forecasting
S. Ryu, J. Noh and H. Kim, IEEE SmartGridComm, 2016, pp.1-6
심층신경망 기반 전력수요예측 모델에 대한 연구
류승형, 노재구, 김홍석, 한국통신학회 학술대회논문집, 488-489, 2016
Hierarchical Clustering of Load Profile Database in Understanding of Korean Standard Industrial Classification
S. Ryu, H. Kim, D. Oh, J.-i. Lee and J. Noh, International Smart Grid Conference (ISGC), Oct. 2015
A Framework for Baseline Load Estimation in Demand Response: Data Mining Approach
S. Park, S. Ryu, Y. Choi and H. Kim, IEEE SmartGridComm, 2014, pp.1-6
Projects
Optimal Control of Virtual Power Plant for Smart City (2016.10 ~ 2019.5)
funded by KEPCO KEPRI.
Community Energy Service Microgrid (2016.5 ~ 2018.12)
funded by KETEP.
National Demand Response (2016.5 ~ 2018.12)
funded by KETEP.
Korean Energy Storage System for Cellular Networks (2014.5 ~ 2017.4)
funded by NRF.
Peer to Peer Energy Prosumer Transaction (2016.9~2017.1)
funded by ETRI.
IoT and Optimal Network Design (2014.6~2015.5)
funded by LG Electronics.
ESS Optimal Control and Hardware Development (2014.9~2015.2)
funded by NRF and Blue Kite.
Energy ICT Convergence Platform based on Fast Demand Response (2013.9~2014.8)
funded by NIPA.
D2D System Assisted by Base Stations (2013.6~2014.5)
funded by LG Electronics.
Awards
2018 / Qualcomm & Sogang University / Qualcomm Best Paper Award / 최우수
2018 / Qualcomm & Sogang University / Qualcomm Best Paper Award / 장려
2016 / 전력 거래소 / 에너지데이터를 활용한 사업모델 경진 대회 / 우수상
서강대학교 창업 경진 대회
전자공학과 최우수 조교