Abstract
To facilitate the transition of residential buildings towards decarbonized energy sources, various energy systems are currently being investigated within the scientific community. The accurate sizing and performance evaluation of these systems heavily rely on the quality of input profiles. Addressing this necessity, a method for generating diverse, high-resolution, continuous, consistent demand and production profiles for a whole year is proposed. This method is structured in a modular fashion and draws upon a widely recognized demand model from literature. Each module of the method is systematically presented, and the parametrization process is detailed through a case study focusing on single-family houses in temperate climate. This comprehensive description facilitates the replication of the method in different geographical regions. Subsequently, a Monte Carlo simulation is employed, incorporating variations in weather conditions, building properties, and occupant behaviors. This simulation generates an openly accessible dataset comprising thermal, electrical and photovoltaic profiles for 3500 configurations. The generated weather and electricity demand profiles exhibit trends and variations that closely match the measured data. Photovoltaic production profiles were validated against PVGIS data, showing similar monthly variations and diversity. The generated dataset includes houses with energy consumption profiles that correspond to Energy Performance Certificates ranging from A to E.
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