From the 1 of 7 linked papers with an AI index.
7 papers
Crossing-Free Probabilistic K-Line Forecasts Without Retraining
Runyao Yu, Yuchen Tao, Yujie Chen +2
The paper proposes K-line–Quantile Sequential Projection (KQSP), a parameter‑free, training‑free method that adjusts probabilistic open‑high‑low‑close forecasts to eliminate quanti…
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…
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…
OrderFusion: Encoding Orderbook for End-to-End Probabilistic Intraday Electricity Price Forecasting
Runyao Yu, Yuchen Tao, Fabian Leimgruber +6
Probabilistic intraday electricity price forecasting is becoming increasingly important for short-term power-system operation. With increasing renewable generation, demand-side fle…
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…
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 (…