Renewable energy penetration increases the power grid's operational uncertainty,
threatening the economic effectiveness and reliability of the grid. In this article, we examine …

Accurate electric load forecasting at various time periods is considered a necessary
challenge for electricity consumers and generators to maximize their economic efficiency in …

The accurate forecasting of electrical loads is essential for optimizing energy dispatch and
reducing expenses. In this study, a novel ensemble model of a temporal convolutional …

This work proposes a procedure for the multi-objective design of a robust forecasting
ensemble of data-driven models. Starting with a data-selection algorithm, a multi-objective …

Accurate forecasts of the impact of spatial weather and pan-European socio-economic and
political risks on hourly electricity demand for the mid-term horizon are crucial for strategic …

This paper proposes a new load pattern recognition method for probabilistic short-term load
forecasting to facilitate the management of low voltage networks and account for future load …

Probabilistic forecasting can characterize the uncertainties and the dynamic trends of the
future residential load, while massive data are required for popular forecasting methods. In …

Accurate load forecasting is crucial for efficient power system management. Yet, it is
particularly challenging during critical days, such as weekends and holidays, due to limited …

Probabilistic peak load forecasting has garnered significant interest due to its ability to
provide detailed statistical insights, surpassing the utility of traditional point predictions …

With the growing integration of wind power into the energy supply, the grid's stability faces
heightened challenges due to the unpredictable nature of wind energy. For the wind farms …