• Energy Research
• 2021-2025close

Current and best practices for hybridGEOTABS design and control around Europe are described in this report. It provides an overview of the design of a hybridGEOTABS building and the core modules, and an overview of the latest developments for controlling integrated building systems using MPC. The report provides an overview of the state-of-the-art hybridGEOTABS design and control during the hybridGEOTABS project and allows to understand the issues various stakeholders are facing, for which solutions are developed in the hybridGEOTABS project. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 723649

Abstract In recent years, the increasing occurrence of heatwaves raises the cooling need of residential buildings in Scandinavian countries, which are traditionally not equipped with active cooling systems. Indoor overheating caused by such heatwaves leads to severe consequences for occupants, especially kids and seniors. Efficient and economical cooling solutions are urgently needed to cope with frequent heatwaves. The present study investigated the novel usage of the geothermal-assisted mechanical ventilation with heat recovery (GEO-MVHR) system for cooling purposes in typical Swedish multi-family dwellings. The cooling potential of the system and its contributions to thermal comfort were evaluated. Dynamic simulations were conducted to assess the system's cooling performance under two climate scenarios: the climate of 2018 representing an extreme year with excessively hot summer and the climate of a typical meteorological year. The GEO-MVHR system shows great potential in mitigating indoor overheating with improved thermal comfort. A ventilation airflow rate of 0.50–0.70 l/s/m2 is suggested for multi-family dwellings to maximize the cooling potential of the GEO-MVHR system. The indoor operative temperature could be reduced by up to 3 °C with the GEO-MVHR system operating for cooling. Modulating the supply air temperature of the GEO-MVHR system based on indoor thermal conditions is recommended, as it shows the advantage of avoiding unnecessary overcooling and energy saving.

Building energy management systems (BEMSs), dedicated to sustainable buildings, may have additional duties, such as hosting efficient energy management systems (EMSs) algorithms. This duty can become crucial when operating renewable energy sources (RES) and eventual electric energy storage systems (ESSs). Sophisticated EMS approaches that aim to manage RES and ESSs in real time may need high computing capabilities that BEMSs typically cannot provide. This article addresses and validates a fuzzy logic-based EMS for the optimal management of photovoltaic (PV) systems with lead-acid ESSs using an edge computing technology. The proposed method is tested on a real smart grid prototype in comparison with a classical rule-based EMS for different weather conditions. The goal is to investigate the efficacy of islanding the building local network as a control command, along with ESS power control. The results show the implementation feasibility and performance of the fuzzy algorithm in the optimal management of ESSs in both operation modes: grid-connected and islanded modes.

In the face of green energy initiatives and progressively increasing shares of more energy-efficient buildings, there is a pressing need to transform district heating towards low-temperature district heating. The substantially lowered supply temperature of low-temperature district heating broadens the opportunities and challenges to integrate distributed renewable energy, which requires enhancement on intelligent heating load prediction. Meanwhile, to fulfill the temperature requirements for domestic hot water and space heating, separate energy conversion units on user-side, such as building-sized boosting heat pumps shall be implemented to upgrade the temperature level of the low-temperature district heating network. This study conducted hybrid heating load prediction methods with long-term and short-term prediction, and the main work consisted of four steps: (1) acquisition and processing of district heating data of 20 district heating supplied nursing homes in the Nordic climate (2016–2019); (2) long-term district heating load prediction through linear regression, energy signature curve in hourly resolution, providing an overall view and boundary conditions for the unit sizing; (3) short-term district heating load prediction through two Artificial Neural Network models, f72 and g120, with different precdiction input parameters; (4) evaluation of the predicted load profiles based on the measured data. Although the three prediction models met the quality criteria, it was found that including the historical hourly heating loads as the input to the forecasting model enhanced the prediction quality, especially for the peak load and low-mild heating season. Furthermore, a possible application of the heating load profiles was proposed by integrating two building-sized heat pumps in low-temperature district heating, which may be a promising heat supply method in low-temperature district heating.

The European Commission aims to reduce the greenhouse gas emissions of the European Union's building stock by 60% by 2030 compared with 1990. Meanwhile, the global demand for cooling is projected to grow 3% yearly between 2020 and 2050. High-temperature cooling systems provide cooling with lower exergy use than conventional cooling systems and enable the integration of renewable energy sources, and can play a crucial role in meeting the growing cooling demand with less energy use. The aim of this study is to analyse and critically evaluate two high-temperature cooling systems in terms of their energy and exergy use in a case study. We also consider thermal comfort performance, CO2 emissions, and sensitivity to changing operating conditions. The two systems considered are a mechanical ventilation system with heat recovery combined with geothermal cooling (GeoMVHR) and a radiant cooling system with ceiling panels connected to the same geothermal cooling (GeoRadiant) system. The study is conducted using building energy models of a typical office building belonging to a three-building school complex located in Sant Cugat near Barcelona, Spain. IDA ICE 4.8 simulation software was used for the simulations. The results show that the two different installations can produce near-identical thermal comfort conditions for the occupants. The GeoRadiant system achieves this result with 72% lower electricity use and 60% less exergy destruction than the GeoMVHR system. Due to the higher electricity use, the CO2 emissions caused by the GeoMVHR system are 3.5 times the emissions caused by the GeoRadiant system. Datasets: "Building energy simulation data results" and "Acquired data from existing and/or new installed meters or from existing BEMS (pre intervention EcoSCADA monitoring data)" - Raw data is available upon request. Follow the link and fill the request form.