3 papers
cs.LG2025
Marginalize, Rather than Impute: Probabilistic Wind Power Forecasting with Incomplete Data
Honglin Wen, Pierre Pinson, Jie Gu +1
Machine learning methods are widely and successfully used for probabilistic wind power forecasting, yet the pervasive issue of missing values (e.g., due to sensor faults or communi…
eess.SY2024
Efficient Demand Response Location Targeting for Price Spike Mitigation by Exploiting Price-demand Relationship
Yufan Zhang, Honglin Wen, Tao Feng +1
Demand response (DR) leverages demand-side flexibility, offering a promising approach to enhance market conditions like mitigating wholesale price spikes. However, poorly chosen DR…
stat.AP2024
Probabilistic wind power forecasting resilient to missing values: an adaptive quantile regression approach
Honglin Wen
Probabilistic wind power forecasting approaches have significantly advanced in recent decades. However, forecasters often assume data completeness and overlook the challenge of mis…