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Renovation of existing buildings is fundamental to reduce greenhouse gas emissions of the building sector and to ensure the efficient operation of renewable heating systems. In multi-family houses, the suitability of heat pumps is limited by high required temperatures for the hot water preparation, which can be mitigated by hybrid heat pump systems. In this study, the energetic performance of a hybrid heat pump in a multi-family house, built in 1964, is investigated based on field data before and after a renovation. Multiple months are measured and mapped to a full year period. The combination of different renovation measures in the heating system and building envelope is rated w.r.t. their ecological and economical impact by taking into account the actual investment costs. The evaluation shows that the installation of a hybrid heat pump can achieve an accumulated greenhouse gas emissions reduction of 45%, which is similar to a building renovation to a new-build standard, which reduces the space heating demand by up to 62%. Nevertheless, only a combination of both measures can substantially reduce the emissions, which in this case are 81% lower compared to a gas boiler in 1990, which is still below the German climate target for 2040. Due to the low investment costs of a hybrid heat pump system, tenants are more likely to profit from a renting costs reduction, while a building renovation is especially economically beneficial at high energy prices. The results therefore emphasize that the insulation level should be selected carefully, as heat pumps already prepare space heating efficiently and that the heat pump must be able to support the hot water preparation to reach high emission reduction targets. [ABSTRACT FROM AUTHOR]

Unrenovated multifamily houses in Germany are mostly heated by fossil heat generators; therefore, measures are required for CO2 emission reduction. The use of air–water heat pumps is restricted by high required flow temperatures and heat output but can be mitigated by hybrid heat pumps. To limit additional operation costs by the heat pump, a new operation strategy is introduced in this study, which allows to maintain a target CO2 emission. The operation strategy is applied in a field trial in a small unrenovated multifamily house built in 1964. A thermohydraulic simulation model is verified and is used in full-year simulations to apply improvement measures and compare the new control strategy with existing optimizing strategies. The results show that the control onto target emissions is possible and limits additional costs but can also result in higher CO2 mitigation costs, making it less favorable. The hybrid heat pump reduces the direct fossil CO2 emissions by 61% (in total by 22%); thus, it is a relevant solution for multifamily houses, especially within a further decarbonized electrical grid. [ABSTRACT FROM AUTHOR]

The alternative control concept using emission from the machine has the potential to reduce energy consumption in HVAC systems. This paper reports on a study of alternative inputs for a control system of HVAC using machine learning algorithms, based on data that are gathered in a welding area of an automotive factory. A data set of CO 2 , fine dust, temperatures and air velocity was logged using continuous and gravimetric measurements during two typical production weeks. The HVAC system was reduced gradually each day to trigger fluctuations of emission. The data were used to train and test various machine learning models using different statistical indices, consequently to choose a best fit model. Different models were tested and the Long Short-Term Memory model showed the best result, with 0.821 discrepancy on R 2 . The gravimetric samples proved that the reduction of air exchange rate does not correlate to escalation of fine dust linearly, which means one cannot rely on just gravimetric samples for HVAC system optimization. Furthermore, by using machine learning algorithms, this study shows that by using commonly available low cost sensors in a production hall, it is possible to correlate fine dust data cost effectively and reduce electricity consumption of the HVAC. [ABSTRACT FROM AUTHOR]