With electric heat pumps replacing for fossil-powered alternatives, the temporal variability with their energy utilization becomes increasingly vital that you the electricity program. To simply include this variability in power system analyses, this paper introduces the dataset comprising artificial national time combination of both the warmth need as well as the coefficient of performance (COP) of heat pumps. It addresses 16 European countries, includes the years 2008 to 2018, and has a per hour quality. Need user profiles for room and water heating are computed by mixing gasoline standard load profiles with spatial heat and wind velocity reanalysis data along with populace geodata. COP time collection for many different warmth resources – atmosphere, ground, and groundwater – and different heat sinks – floor heating, radiators, and water home heating – are calculated based on COP and heating curves using reanalysis heat data. The dataset, as well as the scripts and input guidelines, are openly available below an open resource license in the Open up Power System Data platform.
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In view of the global power transition, open power information are definitely more important than ever1. This can include information on electric powered building heat pumps, which make up a foundation of sustainable power scenarios2. Their energy consumption is of course highly variable. On one side, you can find variances within the warmth demand to get fulfilled from the heat pumps. On the other hand, the COP of the heat pumps, which is defined as the different ratio of their heat generation and electrical energy usage, changes over time. This variability is going to be important in the future electrical energy system balance and has to be considered in associated system and marketplace analyses.
Towards this background, this paper presents the dataset comprising the very first prepared-to-use nationwide time combination of the heating demand as well as the COP of building heat pumps. The strengths in the dataset include:
Validity: Historic time series are introduced, therefore not including uncertain assumptions on future advancements. The heat demand is calculated using regular load profiles, which can be permanently utilized by German gasoline providers, and worldwide validated with dimensions from your United kingdom as well as developing information from the EU. The COP computation is parametrized on manufacturer data not to mention validated with area dimensions.
Precision: The dataset considers particularities of numerous warmth demands (space and water heating), various heat resources (air, ground, and groundwater), and other heat sinks (floor heating, radiators, and water heating).
Comprehensiveness: Time series include a large geographical area of 16 chilly-temperate-climate EU countries (Fig. 1), that is relevant for modelling the total amount of the a lot more integrated European electric power system. Furthermore, 11 years (2008-2018) are provided to permit weather conditions year level of sensitivity analyses.
The dataset is a contribution to the Open Electrical power System Information project and comes after the frictionless data principles6. Focusing on the representation of heat pumps, the aim is to enhance efficiency, transparency, and reproducibility of electric power market models, which might be element of much more general incorporated nggazy power system analyses. Moreover, it might serve as a beneficial standard for alternative warmth need and heat pump modelling methods on the nationwide degree. Existing restrictions in the dataset are critically talked about within the Usage Information section.