This paper presents a new privacy-preserving framework for the short-term (multi-horizon) probabilistic forecasting of nodal voltages in local energy communities. task is indeed becoming increasingly important cost-effectively managing network constraints context massive integration distributed resources. However, traditional tasks are carried out centrally, by gathering raw data end-users sing...

Abstract The current research on probabilistic load forecasting models mostly combines machine learning algorithms and quantile regression methods to construct models. This paper first summarizes combs the commonly used forecast Combined with actual data, we analyzed main factors affecting performance of attempted elaborate influencing mechanism. Then, a strategy based sample weight is designed...

Probabilistic forecasting of electricity demand (load) facilitates the efficient management and operations energy systems. Weather is a key determinant load. However, modelling load using weather challenging because relationship cannot be assumed to linear. Although numerous studies have focussed on forecasting, literature uncertainty in while estimating probability distribution scarce. In this...

Ensemble prediction systems (EPSs) serve as a popular technique to provide probabilistic precipitation in short- and medium-range forecasting. However, numerical models still suffer from imperfect configurations associated with data assimilation physical parameterization, which can lead systemic bias. Even state-of-the-art often fail high-quality forecasting, especially for extreme events. In t...

Abstract Quantile Regression Averaging (QRA) has sparked interest in the electricity price forecasting community after its unprecedented success Global Energy Forecasting Competition 2014, where top two winning teams track used variants of QRA. However, recent studies have reported method's vulnerability to low quality predictors when set regressors is larger than just a few. To address this is...

The most common method of verifying multicategory probabilistic forecasts such as are used in probabilistic quantitative precipitation forecasting is through the use of the ranked probability score. This single number description of forecast accuracy can never capture the multidimensional nature of forecast quality and does not inform the forecaster about the sources of forecast deficiencies. A...