19 citations · 83 across the 11 of their papers we have counts for
11 papers
Statistical and economic evaluation of forecasts in electricity markets: beyond RMSE and MAE
Katarzyna Maciejowska, Arkadiusz Lipiecki, Bartosz Uniejewski
Electricity price forecasts are typically evaluated using accuracy measures such as RMSE and MAE, although these metrics often fail to reflect their economic value in operational d…
Variance Stabilizing Transformations for Electricity Price Forecasting in Periods of Increased Volatility
Bartosz Uniejewski
Accurate day-ahead electricity price forecasts are critical for power system operation and market participation, yet growing renewable penetration and recent crises have caused unp…
Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market
Katarzyna Chęć, Bartosz Uniejewski, Rafał Weron
Recent studies provide evidence that decomposing the electricity price into the long-term seasonal component (LTSC) and the remaining part, predicting both separately, and then com…
The role of probabilistic load and renewable prediction in enhancing day-ahead electricity price forecasts
Bartosz Uniejewski, Florian Ziel
The increasing penetration of renewable energy sources (RES) has amplified volatility in electricity markets, while demand variability continues to challenge system stability. Trad…
Ranking probabilistic forecasting models with different loss functions
Tomasz Serafin, Bartosz Uniejewski
In this study, we introduced various statistical performance metrics, based on the pinball loss and the empirical coverage, for the ranking of probabilistic forecasting models. We…
Regularization for electricity price forecasting
Bartosz Uniejewski
The most commonly used form of regularization typically involves defining the penalty function as a L1 or L2 norm. However, numerous alternative approaches remain untested in pract…
Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression
Arkadiusz Lipiecki, Bartosz Uniejewski, Rafał Weron
Operational decisions relying on predictive distributions of electricity prices can result in significantly higher profits compared to those based solely on point forecasts. Howeve…
Probabilistic forecasting with a hybrid Factor-QRA approach: Application to electricity trading
Katarzyna Maciejowska, Tomasz Serafin, Bartosz Uniejewski
This paper presents a novel hybrid approach for constricting probabilistic forecasts that combines both the Quantile Regression Averaging (QRA) method and the factor-based averagin…
Smoothing Quantile Regression Averaging: A new approach to probabilistic forecasting of electricity prices
Bartosz Uniejewski
Accurate short-term price forecasting is essential for daily operations in electricity markets. This article introduces a new method, called Smoothing Quantile Regression (SQR) Ave…
LASSO Principal Component Averaging -- a fully automated approach for point forecast pooling
Bartosz Uniejewski, Katarzyna Maciejowska
This paper develops a novel, fully automated forecast averaging scheme, which combines LASSO estimation method with Principal Component Averaging (PCA). LASSO-PCA (LPCA) explores a…
Forecasting Electricity Prices
Katarzyna Maciejowska, Bartosz Uniejewski, Rafał Weron
Forecasting electricity prices is a challenging task and an active area of research since the 1990s and the deregulation of the traditionally monopolistic and government-controlled…