From the 1 of 4 linked papers with an AI index.
4 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…