Abstract
Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of environmental sustainability and user comfort. This work presents a distributed sensor-processor-communication decision-making architecture to improve the acquisition, storage and transfer of thermal energy in buildings. The developed system is implemented in a near Zero-Energy Building (nZEB) prototype equipped with a built-in thermal solar collector, where optical properties are analysed; a low enthalpy geothermal accumulation system, segmented in different temperature zones; and an envelope that includes a dynamic thermal barrier. An intelligent control of this dynamic thermal barrier is applied to reduce the thermal energy demand (heating and cooling) caused by daily and seasonal weather variations. Simulations and experimental results are presented to highlight the nZEB thermal energy reduction.
Highlights
Buildings produce high CO2 emissions as they consume almost 40% of worldwide energy, and a remarkable percentage of this energy is used for achieving thermal comfort conditions, both in heating and cooling
The main contributions of current work is summarized as follows: the analysis of the solar collector simulation and experimental results for different parameters; the flow of the thermal energy when a dynamic thermal barrier is integrated in a building; the whole thermal energy transfer model of the experimental building; the developed of an architecture to control, using virtual sensors, context information, and computational intelligence techniques, the thermal flow between the energy subsystems of the nearly zero energy buildings (nZEB) building; experimental validation in the building prototype by temperature and presence sensor measurements and wall thermal images
The three thermal subsystems that have been designed and integrated to better use the thermal energy in a building are described in detail
Summary
Buildings produce high CO2 emissions as they consume almost 40% of worldwide energy, and a remarkable percentage of this energy is used for achieving thermal comfort conditions, both in heating and cooling. In this work a decision-making architecture to manage the capture, storage and use of solar thermal energy is presented It includes the monitoring and control of the roof solar system, the ground heat exchanger, and the dynamic envelope (thermal barrier) using virtual sensors. The main contributions of current work is summarized as follows: the analysis of the solar collector simulation and experimental results for different parameters; the flow of the thermal energy when a dynamic thermal barrier is integrated in a building; the whole thermal energy transfer model of the experimental building; the developed of an architecture to control, using virtual sensors, context information, and computational intelligence techniques (decision trees and fuzzy logic), the thermal flow between the energy subsystems of the nZEB building; experimental validation in the building prototype by temperature and presence sensor measurements and wall thermal images.
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