Probabilistic Load Forecasting via Quantile Regression Averaging on Sister Forecasts

By Bidong Liu, Jakub Nowotarski, Tao Hong, Rafal Weron. IEEE Transactions on Smart Grid, 2017

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Energy Forecasting: A Review and Outlook (2020, methodology): “Researchers have proposed various forecast combination strategies to generate and improve probabilistic load forecasts [37], [76], [77].”
Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges (2018, unknown): “GEFCom 2012 [45] Zonal load data; Temperature data; 20 Hourly 2003/1-2008/6 [46][47][48][49] [50][51][52][53]”
On the importance of the long-term seasonal component in day-ahead electricity price forecasting (2016, background): “, 2016), not only in the area of EPF (Liu et al., 2017; Zhang et al., 2016).”
Recent advances in electricity price forecasting: A review of probabilistic forecasting (2016, background): “Note that pinball loss is the function to be minimized in quantile regression [6, 34] and is similar to Eqn.”
Short-Term Load Forecasting With Deep Residual Networks (2018, methodology): “In Table VI, we present the values of pinball loss and Winkler scores for the proposed model and the models in [23] and [51] for the year of 2011 in the GEFCom2014”