7 papers
Crossing-Free Probabilistic K-Line Forecasts Without Retraining
Runyao Yu, Yuchen Tao, Yujie Chen +2
Probabilistic K-line forecasting describes uncertainty in four complementary prices, namely open--high--low--close (OHLC). However, it introduces two consistency problems: quantile…
A Market-Rule-Informed Neural Network for Efficient Imbalance Electricity Price Forecasting
Runyao Yu, Julia Lin, Derek W. Bunn +6
Accurate and efficient imbalance electricity price forecasting is critical for industrial energy trading systems, especially as battery assets and automated bidding pipelines incre…
Probabilistic Hysteresis Factor Prediction for Electric Vehicle Batteries with Graphite Anodes Containing Silicon
Runyao Yu, Viviana Kleine, Philipp Gromotka +5
Batteries with silicon-graphite-based anodes, which offer higher energy density and improved charging performance, introduce pronounced voltage hysteresis, making state-of-charge (…
Deep Learning for Electricity Price Forecasting: A Review of Day-Ahead, Intraday, and Balancing Electricity Markets
Runyao Yu, Derek W. Bunn, Julia Lin +8
Electricity price forecasting (EPF) plays a critical role in power system operation and market decision making. While existing review studies have provided valuable insights into f…
Orderbook Feature Learning and Asymmetric Generalization in Intraday Electricity Markets
Runyao Yu, Ruochen Wu, Yongsheng Han +1
Accurate probabilistic forecasting of intraday electricity prices is critical for market participants to inform trading decisions. Existing studies rely on specific domain features…
PriceFM: Foundation Model for Probabilistic Electricity Price Forecasting
Runyao Yu, Chenhui Gu, Jochen Stiasny +4
Electricity price forecasting in Europe presents unique challenges due to increasing renewable generation variability, market integration, and the continent's physically interconne…