The recent H2020 IDEAS project is oriented to the study of multi-source heat pump systems by investigating their behavior through dynamic simulations and on-field experiments in real small and large-scale prototypes respectively. One of the main aims of the project is the exploitation of available free energy sources, solar, air and ground using the heat pump technology. The key point in the investigated multi-source heat pump system is the optimal management of the renewable sources and the keeping of the ground storage available also in case of undersize of it and in case of buildings with unbalanced thermal load profile. In the last year of the project the algorithm for the control of sources and devices in the IDEAS system has been developed to maximize the use of renewable energies and at the same time to minimize the consumption of auxiliary energy. The present paper shows the details of this part of the project highlighting limits, potential and properties of the management system with a discussion of the results obtained from the on-field experiments. In the last part of the project, the implementation of weather forecast and artificial intelligence in the algorithm is planned.

A Management Strategy for Multi-Source Heat Pump Systems

Emmi, Giuseppe
;
2022-01-01

Abstract

The recent H2020 IDEAS project is oriented to the study of multi-source heat pump systems by investigating their behavior through dynamic simulations and on-field experiments in real small and large-scale prototypes respectively. One of the main aims of the project is the exploitation of available free energy sources, solar, air and ground using the heat pump technology. The key point in the investigated multi-source heat pump system is the optimal management of the renewable sources and the keeping of the ground storage available also in case of undersize of it and in case of buildings with unbalanced thermal load profile. In the last year of the project the algorithm for the control of sources and devices in the IDEAS system has been developed to maximize the use of renewable energies and at the same time to minimize the consumption of auxiliary energy. The present paper shows the details of this part of the project highlighting limits, potential and properties of the management system with a discussion of the results obtained from the on-field experiments. In the last part of the project, the implementation of weather forecast and artificial intelligence in the algorithm is planned.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11578/374051
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