The use of physics-based models for the development and optimization of energy systems is
popular due to their versatility. However, their inherent complexity often makes these …

Meeting the goal of zero emissions in the energy sector by 2050 requires accurate
prediction of energy consumption, which is increasingly important. However, conventional …

To achieve net zero emissions by 2050, the world economy needs to be significantly
decarbonized. Among all sectors, the decarbonization of heat is likely to incorporate a …

The production of precisely the required quantity of goods at precisely the correct moment is
the objective of every sector. A forecast is formed through the utilization of information from …

Using the heating demand of the final customer as the heat supply input time series in
investment or dispatch models of district heating systems could lead to erroneous results …

A large proportion of the energy consumed by private households is used for space heating
and domestic hot water. In the context of the energy transition, the predominant aim is to …

This paper compares machine learning models for short-term heat demand forecasting in
residential and multi-family buildings, evaluating model suitability, data impact on accuracy …

This work proposes and evaluates a method for the nowcasting of solar irradiance variability
in multiple time horizons, namely 5, 10, and 15 min ahead. The method is based on a …

One of the most critical issues for wind energy exploitation is the high variability of the
resource, resulting in very difficult forecasting of the power that wind farms can grant. A vast …

To improve the accuracy of short-term multi-energy load prediction models for integrated
energy systems, the historical development law of the multi-energy loads must be …