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Klanatsky, Peter
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Official Name
Klanatsky, Peter
Main Affiliation
Akademische Titel
DI(FH)
Email
peter.klanatsky@fh-burgenland.at
Scopus Author ID
39461478500
Status
staff
Research Outputs
Now showing 1 - 10 of 31
- Publication
171 - Publication
115 379 - PublicationSystem efficiency of PVT-collector driven heat pumpsStandard heat pump (HP) systems with horizontal ground heat exchangers (HGHE) are commonly designed based on arbitrary knowledge gained over time and the use of the rule of thumb. Where an undersizing of the HGHE occurs, the HP efficiencies are lowered. Undersizing could result as a consequence of underestimating the soils thermal conductivity. Therefore, this paper considers the combined photovoltaic and solar thermal (PVT) collectors as an extension to standard HP heating systems with a HGHE in single-family houses with the possibility of improving the COP of the HP at a later stage and effortlessly. With the implemented hydronic scheme, the PVT-collector is also used to regenerate the soil around the ground to increase the temperature level of the heat source resulting in improved performance. However, the efficiency potential of the PV-Cells due to active cooling of the modules is analyzed. The results show an increase of the seasonal performance factor (SPF) of 4.1 % and higher electric energy output of 4.4% due to active cooling of the PV-Cells while energy consumption of the regeneration pump is covered.
437 767 - PublicationDevelopment of an innovative blind control strategy to increase the thermal comfort of an office building(Konferenzbeitrag zur internationalen Konferenz „Indoor Climate of Buildings 2019“, 2019)
; ; 2 2 - ProductMonitoring dataset from an office room in a real operating building, suitable for state-space energy modelling(2023-07-21)
; ; ; 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/10.3217/978-3-85125-786-1-03.150 83