With electric powered heat pumps substituting for fossil-fueled options, the temporal variability with their electrical power consumption will become more and more important to the electricity system. To simply consist of this variability in energy system analyses, this papers introduces the dataset comprising synthetic nationwide time combination of both warmth need and the coefficient of overall performance (COP) of heat pumps. It addresses 16 European countries, consists of time 2008 to 2018, and has a per hour resolution. Demand profiles for space and water home heating are computed by mixing gasoline regular load user profiles with spatial temperature and blowing wind speed reanalysis data in addition to populace geodata. COP time collection for different warmth sources – atmosphere, ground, and groundwater – and various warmth sinks – flooring home heating, radiators, and water home heating – are calculated based on COP and heating shape using reanalysis heat information. The dataset, as well as the scripts and input guidelines, are openly readily available below a wide open resource permit in the Open Power System Information platform.
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Because in the global energy transition, open up power information tend to be more important than ever1. This includes information on electric powered building heat pumps, which constitute a foundation of sustainable energy scenarios2. Their energy consumption is of course extremely adjustable. On one side, there are variances within the heat demand to become satisfied by the heat pumps. On the other hand, the COP of the heat pumps, which is defined as the different proportion with their warmth generation and electric power utilization, modifications as time passes. This variability will be essential for future years electrical energy program balance and has to be considered in associated system and marketplace analyses.
Towards this background, this papers introduces the dataset comprising the first prepared-to-use national time series of both the heat demand and also the COP of building heat pumps. The strong points from the dataset include:
Credibility: Historic time series are introduced, therefore not including uncertain assumptions on future developments. The warmth demand is calculated using standard weight profiles, which can be permanently utilized by German gasoline suppliers, and worldwide validated with measurements from your United kingdom along with developing information from your EU. The COP computation is parametrized on manufacturer data and additionally validated with field dimensions.
Precision: The dataset considers particularities of numerous warmth demands (room and water heating), different warmth resources (air, ground, and groundwater), and various warmth sinks (flooring heating, radiators, and water home heating).
Comprehensiveness: Enough time series cover a big geographical part of 16 cold-warm-environment EU nations (Fig. 1), which can be appropriate for modelling the total amount from the increasingly more incorporated European electricity system. Moreover, eleven many years (2008-2018) are provided to permit weather conditions year sensitivity analyses.
The dataset is really a participation towards the Open Energy Program Information task and follows the frictionless information principles6. Centering on the representation of heat pumps, the goal would be to improve effectiveness, visibility, and reproducibility of electric power market designs, which might be a part of much more basic incorporated nggazy energy program analyses. Moreover, it might work as a beneficial standard for option heat demand and heat pump modelling approaches in the nationwide degree. Current restrictions from the dataset are critically talked about in the Use Information area.