6 papers
Sensitivity Quantification for Distribution System State Estimation
Betül Mamudi, Jochen Stiasny, Jochen Cremer
Pseudo-measurements are the dominant source of uncertainty in distribution system state estimation (DSSE), yet their distributional assumptions are treated as fixed inputs by exist…
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…
Data driven approach towards more efficient Newton-Raphson power flow calculation for distribution grids
Shengyuan Yan, Farzad Vazinram, Zeynab Kaseb +8
Power flow (PF) calculations are fundamental to power system analysis to ensure stable and reliable grid operation. The Newton-Raphson (NR) method is commonly used for PF analysis…