Multi-Site Photovoltaic Forecasting Exploiting Space-Time Convolutional Neural Network J Jeong, H Kim Energies 12 (23), 4490, 2019 | 54 | 2019 |
Missing-insensitive short-term load forecasting leveraging autoencoder and LSTM K Park, J Jeong, D Kim, H Kim IEEE Access 8, 206039-206048, 2020 | 24 | 2020 |
Stochastic optimization of home energy management system using clustered quantile scenario reduction M Kim, T Park, J Jeong, H Kim Applied Energy 349, 121555, 2023 | 23 | 2023 |
DeepComp: Deep reinforcement learning based renewable energy error compensable forecasting J Jeong, H Kim Applied Energy 294, 116970, 2021 | 23 | 2021 |
Deep reinforcement learning based real-time renewable energy bidding with battery control J Jeong, SW Kim, H Kim IEEE Transactions on Energy Markets, Policy and Regulation 1 (2), 85-96, 2023 | 13 | 2023 |
DTTrans: PV Power Forecasting Using Delaunay Triangulation and TransGRU K Song, J Jeong, JH Moon, SC Kwon, H Kim Sensors 23 (1), 144, 2022 | 11 | 2022 |
Convolutional Autoencoder-Based Anomaly Detection for Photovoltaic Power Forecasting of Virtual Power Plants T Park, K Song, J Jeong, H Kim Energies 16 (14), 5293, 2023 | 9 | 2023 |
Autoencoder-Based Recommender System Exploiting Natural Noise Removal H Park, J Jeong, KW Oh, H Kim IEEE Access 11, 30609-30618, 2023 | 6 | 2023 |
Denoising Masked Autoencoder-Based Missing Imputation within Constrained Environments for Electric Load Data J Jeong, TY Ku, WK Park Energies 16 (24), 7933, 2023 | 3 | 2023 |
Deep reinforcement learning based renew-able energy error compensable forecasting J Jeong, H Kim ICLR 2020 Workshop: Tackling Climate Change with Machine Learning, 1-5, 2020 | 2 | 2020 |
Time-Varying Constraint-Aware Reinforcement Learning for Energy Storage Control J Jeong, TY Ku, WK Park ICLR 2024 Workshop: Tackling Climate Change with Machine Learning, 1-6, 2024 | 1 | 2024 |
Exploring the Preference for Discrete over Continuous Reinforcement Learning in Energy Storage Arbitrage J Jeong, TY Ku, WK Park Energies 17 (23), 5876, 2024 | | 2024 |