Browsing by Type "dataset"

This dataset contains measurements from real operation of a hybrid photovoltaic-thermal solar collector. The data is from a summer period, when the collector works at its higher temperature limit, with low thermal efficiency. The dataset characterizes the output of the collector: thermal (heat transfer fluid flowrate, inlet and outlet temperatures) and electrical (raw current and voltage, Hampel filtered power). Further information on the collector are the PV cell temperature and the back surface temperature (in three points). Detailed weather information are included: ambient temperature, solar resource (direct normal, global and diffuse horizontal, global tilted in the collector plane), equivalent radiative sky temperature (calculated from a pyrgeometer), wind speed and direction both horizontal and in the tilted collector plane. The calculated sun position with Duffie and Beckmann method is also given (elevation and azimuth) . The dataset covers 58 summer days from 11th July to 6th September, with a 5 second time step. The data is available as .mat file (MATLAB) and .csv file. This dataset is presented in details in a dedicated article [1]. A selection of variables from this dataset has already been used in the development of a data-driven model [2]. References: [1] F. Veynandt, F. Inschlag, C. Seidl, C. Heschl, Measurement data from real operation of a hybrid photovoltaic-thermal solar collectors, used for the development of a data-driven model, Data in Brief. 49 (2023) 109417. https://doi.org/10.1016/j.dib.2023.109417. [2] F. Veynandt, P. Klanatsky, H. Plank, C. Heschl, Hybrid photovoltaic-thermal solar collector modelling with parameter identification using operation data, Energy and Buildings. 295 (2023) 113277. https://doi.org/10.1016/j.enbuild.2023.113277.

To support open science, monitoring data from the living laboratory ENERGETIKUM in Pinkafeld, Austria, is shared here. The dataset provided is especially suitable for data-driven energy modelling of an office room. This can be for model predictive control strategies useful. The dataset provides all necessary variables over a period of sixteen months, with a time step of one minute or fifteen minutes, in MATLAB format (.mat) or in tabs-separated format (.txt). Some variables are raw measurements: ambient (T_Amb) and room (T_Air_Measured) air temperatures, ventilation air flowrate (V_dot_Vent) and supply temperature (T_Vent_In). Other variables are calculated from measurements: heat flows for floor heating (Q_dot_FBH), ceiling cooling (Q_dot_DE) and from internal loads (Q_dot_Int_LO). For the incoming solar irradiance, two façade models using measurements (solar irradiance, movable shading settings) and building characteristics (geometry, glazing and shading optical properties) are used: the simple model (q_dot_Solar_SF) and the enhanced model (Q_dot_Solar_EF). To the background of the façade models, see [1,2]. References: [1] F. Veynandt, C. Heschl, P. Klanatsky, H. Plank, Complex glass facade modelling for Model Predictive Control of thermal loads: impact of the solar load identification on the state-space model accuracy, Leykam, 2020. http://hdl.handle.net/20.500.11790/1396 (accessed January 31, 2022). [2] Veynandt, F., Heschl, C., MODELING OF SOLAR RADIATION TRANSMISSION THROUGH TRIPLE GLAZING BASED ONLY ON ON-SITE MEASUREMENTS, in: Verlag der Technischen Universität Graz, Online Conference, 2020. https://doi.org/10.3217/978-3-85125-786-1-03.