Ground-source heat pump systems are energy-efficient solutions for buildings located in cold, heating-dominated climates. This study explores how incorporating additional heat sources or regeneration techniques can improve the ground thermal imbalance, either by reducing the reliance on the borehole field or by injecting heat into the ground, respectively. The contribution of this study lies in conducting a comprehensive, long-term techno-economic comparison of six hybrid ground-source heat pump system layouts, including regeneration-based and bivalent configurations, under identical boundary conditions for a Nordic climate. The configurations evaluated in this study integrate ground-source heat pump systems with either solar thermal collectors, photovoltaicthermal collectors, dry cooler (in series or parallel configurations), or an air source heat pump. Using TRNSYS simulations over a 20-year period for a multi-family house in Oslo, Norway, the results indicate that solarassisted ground-source heat pump configurations, including those integrated with photovoltaic-thermal or solar thermal collectors, significantly reduce the annual net ground heat extraction, with solar thermal achieving the highest regeneration capability by reducing net heat extraction by up to 73.8 %. Similarly, the dry cooler in a series configuration demonstrated strong performance, reducing net ground heat extraction by 57.7 %. In contrast, layouts that primarily reduce the ground dependence, such as the dry cooler in a parallel configuration and the air source heat pump, exhibited lower ground thermal stability, with the air source heat pump showing the least effective ground thermal balance. From the total cost perspective, the dry cooler in a series configuration appears to be one of the most cost-effective solutions. For example, it can reduce the total costs by up to 9.91 % over 20 years while approximately maintaining the system's energy efficiency. Photovoltaic-thermal shows benefits, but with lower performance than solar thermal, due to higher investment costs and lower thermal efficiency, not compensated by its electricity production. In contrast, the air source heat pump and the dry cooler in a parallel configuration showed minor economic benefits. In large-scale installations, where the borehole field is more compact and the thermal interaction increases, the results show that layouts incorporating regeneration strategies achieve better performance and cost-effectiveness compared to those that only reduce the reliance on ground extraction.

The research analyzes the performance of a simple rule-based control to perform demand response (DR) using the building thermal mass (BTM) in non-residential buildings. The DR schedule-based controller is implemented and tested for two months in a highly-insulated school located in Trondheim (Norway). Simple DR control can be considered as an intermediate step before implementing more advanced controls, such as model predictive control (MPC). In addition, there is a lack of knowledge and field experiments on thermal comfort during transient indoor thermal environments, especially in educational buildings. Firstly, the experiments show that a simple schedule-based controller in a recent building can still experience basic faults during operation. Secondly, the simple DR control decreases the delivered space-heating energy by 27

Understanding occupant heating behavior is essential for reliable building energy modeling and effective energy policy. This study investigates the role of wood-burning stoves in Norwegian households, focusing on their impact on electricity demand, indoor thermal conditions, and occupant comfort in different rooms. A nationwide questionnaire with 437 responses was analyzed using generalized linear models and cumulative link models, complemented by descriptive analysis. The study investigates wood stove usage patterns, user motivations, indoor temperatures, and thermal comfort in both bedrooms and living areas. The results reveal substantial variability in stove operation across households, building characteristics, and space-heating systems, along with a pronounced seasonal dependence. Peak usage occurs in the evening, coinciding with periods of highest electricity demand, thereby highlighting a significant potential for peak load reduction during cold days. Distinct differences are also observed between weekdays and weekends, across heating systems, and in relation to the underlying motivations for wood stove use. Living rooms in dwellings equipped with wood stoves exhibit greater temperature variability, alongside improved thermal comfort during stove operation, particularly in homes relying on electric panels as the main heating system. This highlights the importance of the primary heating system and its interaction with wood stoves. Overheating is reported in approximately 25% of homes and up to 50% of highly insulated buildings, providing empirical confirmation of concerns previously identified in simulation studies and highlighting the need for appropriate stove sizing and the integration of thermal storage. Overall, these empirical findings deliver robust, policy-relevant insights for energy planning, building performance simulation, and wood stove design and manufacturing.

In this study, the design and development of an optimal control strategy for the operation of an innovative bio-wax phase change material based pillow plate thermal energy storage unit delivering space heating to a four-storey-high research building is presented. The hydronic heating system in the ZEB-laboratory comprises an electric driven heat pump, the thermal storage unit and hydronic radiators. Numerical control-oriented dynamic models to simulate the phase-change dynamics of the thermal system are developed and validated. To predict the hourly heating load of the building reliably and accurately, a 14-node Resistance-Capacitance thermal network model is developed to be employed as a decision support tool. An optimal model-based predictive control strategy based on the validated system models is developed for application in real-time operation of the thermal storage unit. The control strategy is designed to optimally utilize the energy storage capability of the thermal energy storage unit to generate demand flexibility in response to time-varying electricity price signals. In comparison to a rule based control, the developed optimal control demonstrates a high degree of flexibility - as quantified by values of flexibility factor close to 1 being obtained - indicating a system operating with maximum flexibility, during one month of operation. Further, results demonstrate the availability of storage capacity of 100 kW h-200 kWh per day on average, indicating the capability of the optimized operation of the thermal energy storage unit to provide grid ancillary services. In addition to being demand flexible, the optimal charging schedule reduces the energy consumption and cost by about 40% - 50% on average. Thus, the developed optimal control strategy demonstrates a significant capability to generate and maximize demand flexibility to shift loads intelligently, provide grid services, and reduce energy cost and consumption.

Ground Source Heat Pump (GSHP) systems are an energy-efficient solution for meeting heating demands in buildings. However, in cold climates with heating-dominated loads, the net extraction of heat from the ground causes a thermal imbalance, reducing ground temperature and the seasonal performance factor (SPF) of the heat pump over time. Photovoltaic-thermal (PVT) panels can help regenerate ground temperature, improving energy efficiency and potentially reducing the required borehole field size. While the scientific literature has recently clarified the design and potential of GSHP + PVT, limited research has been done on the use of pre-heating tanks to improve the system performance. This study evaluates three GSHP + PVT system layouts using TRNSYS simulations for a multi-family house in Oslo over a 50-year period. The results show that integrating a preheating tank on the condenser side increases the 50-year-averaged system SPF4 from 3.85 (baseline) to 4.11 (+6.8 %), demonstrating enhanced energy efficiency. However, the SPF4 reduction over time is larger with the pre-heating tank (-7.47 %) due to reduced ground regeneration. In contrast, placing the pre-heating tank on the evaporator side yields a moderate SPF4 increase to 3.95 (+2.6 %). Additionally, the optimal configurations lead to a 3.6 % reduction in electricity import from the grid, while the impact on PVT electricity generation remains minimal. These findings highlight that pre-heating tanks can effectively enhance GSHP + PVT efficiency, but their placement must be carefully considered to balance short-term efficiency gains with long-term performance.

Laminar airflow (LAF) is essential for maintaining a sterile environment in operating rooms, but its rapid unidirectional flow decay leads to low airflow efficiency and increases energy consumption. The objective of this study is to investigate the energy-saving and air quality benefits of using a low-turbulence air curtain around laminar airflow, which is referred to as protective laminar airflow (PLAF). Numerical simulations were used to model airflow and particle transport, and a series of experiments were conducted in a real operating room at St. Olavs Hospital, Norway, to validate the simulation results. The findings indicate that when the unidirectional airflow supply velocity is maintained at 0.25 m/s, combined with an air curtain that has the width of 2 cm and the velocity of 1.5 m/s, the PLAF system outperforms the conventional LAF system operating at a unidirectional airflow supply velocity of 0.30 m/s. This configuration results in a 17.3% energy saving, showing the potential of this airflow distribution strategy to enhance both cleanliness and energy efficiency.

Wood stoves are commonly used for the space heating of residential buildings, especially in Norway. While their influence on building energy consumption has been extensively studied, the contribution of wood stoves to building power consumption has barely been addressed in the scientific literature. Wood stoves typically have a relatively high nominal power (6-8 kW) and are common in most Norwegian homes. Thus, the effect of wood stoves on the heating power of households is expected to be large. However, this effect has never been demonstrated using measurement data. For this purpose, the paper compares the aggregated hourly electricity use of detached residential houses with and without wood stoves. The baseline space-heating system is electric panels, but air-to-air heat pumps are also considered. The results confirm that the contribution of wood stoves to the reduction of electric power is large (that is, up to similar to 10W/m2 at-10 degrees C), especially during peak hours when the occupants are present and active. However, wood stoves also decrease electrical power in the middle of the night, when occupants are not expected to operate the wood stove. This suggests that the ownership of a wood stove could also influence user behavior, such as the desired indoor temperature. These findings highlight the critical role of wood stoves in alleviating the stress of power demand on the electricity grid by replacing electricity with biomass heating. In conclusion, wood stoves play an important role in household energy use and have broader implications for power grid management and peak load reduction.

Large eddy simulation (LES) can be performed using general-purpose flow solvers such as Fluent or OpenFOAM. These solvers typically require regular grids with high orthogonality and low skewness for explicit LES. Consequently, most existing LES studies of indoor airflows rely on structured grids. Given this grid constraint, this paper presents a novel framework that demonstrates how the unique characteristics of indoor airflows make orthogonal, non-body-conformal grids a suitable choice for high-fidelity explicit LES in buildings. First, orthogonal grids enable more accurate spatial discretization than general-purpose flow solvers, enhancing the precision of scale-resolving simulations. Second, staggered grid arrangements ensure pressure–velocity coupling without introducing artificial numerical dissipation. Third, indoor airflow simulations often involve relatively moderate Reynolds numbers and localized geometrical complexity, making the immersed boundary method (IBM) particularly suitable for handling solid boundaries. IBM eliminates the need for complex re-meshing techniques required for body-conformal grids, thereby facilitating simulations of airflow disturbances caused by moving objects, such as doors or human movement. Our main contribution is to define and validate this framework, as well as to test it by modifying an existing incompressible flow solver, REEF3D, originally designed for hydrodynamics. We evaluate the performance of this method through a series of benchmark tests relevant to indoor airflows, including assessments of airflows generated by sliding doors.

Behind-the-meter data were collected in three residential buildings in Trondheim, Norway, heated with direct electric panels and a wood stove, as part of the SusWoodStoves research project, which aimed to investigate the influence of wood stove operation on electric power consumption. The dataset is characterized by high resolution in time, space (that is, room level), and the number of recorded physical quantities, allowing for a wide range of investigations related to indoor climate, energy use, and building-grid interaction. Specifically, the dataset includes indoor and outdoor environmental variables such as air temperature, CO2, TVOC, radon concentrations, and particulate matter; global solar irradiation has been recorded from a nearby meteorological station; electric power is measured for each heat emitter and on the main meter; and the surface temperature of the wood stove is recorded to monitor its operation. Measurements were sampled every 5 min, with periods ranging from two to six months.

A cavity flow consists of one air inlet and one outlet slot. The inlet slot is positioned in the upper left corner of the cavity, whereas the outlet slot is located in the lower right. This cavity flow is representative of mixing ventilation. The literature shows that the prevalent two-equation RANS turbulence models can reproduce the measured velocity field in the cavity for the transitional and fully turbulent flow regimes. However, a single turbulence model cannot perform equally well at these two flow regimes: k-ε models perform well for the fully turbulent regime, while the k-ω models perform best in the transitional regime. In general, this dependence on the flow regime can make the use of RANS less reliable during the ventilation design phase. By definition, LES is expected to be suited for transitional and fully turbulent flow regimes. Therefore, it is worth investigating and comparing the performance of LES and RANS on two isothermal cavity flow benchmarks, which differ by their geometry (i.e., the aspect ratio of the room) and flow regimes. Simulations are performed on structured grids using the Dynamic Smagorinsky subgrid-scale (SGS) model for LES and the standard k-ε, standard k-ω and BSL k-ω turbulence models for RANS. In addition, the performance of DES is also investigated and compared using the Spalart-Allmaras and realizable k-ε DES. Results show that the LES using the Dynamic Smagorinsky is indeed able to reproduce the velocity field for both flow regimes, making the model more universal than RANS. However, results are strongly dependent on the turbulence level at the inlet. In addition, it is shown that spatial-developing synthetic turbulence at the inlet gives comparable results as a separate LES simulation, leading to simpler and less computationally expensive simulations. Regarding DES, the realizable k-ε DES gives fairly good results for the fully turbulent case. However, the DES has numerical stability issues when adding considerable synthetic turbulence at the inlet and suffers from the depletion of turbulent structures under the transition from RANS to LES. In conclusion, LES can be more universal to predict the ventilation performance of mixing ventilation in buildings, but it requires a good knowledge of the turbulence intensity at the air inlets, which may not be a straightforward task during design. Regarding DES, it has the potential to decrease computational costs compared to LES, but it requires further research for the cavity flow.

Accurate long-term forecasts of aggregate energy load profiles are crucial for effective energy system planning at regional and national scales. This study aims to validate PROFet, a flexible load profile modeling tool. PROFet forecasts weather-dependent heating and electrical load profiles at an hourly resolution for both residential and non-residential buildings connected to district heating systems. Given that the tool’s accuracy for residential buildings has been demonstrated in previous studies, further validation is needed for non-residential buildings. To achieve this, our study evaluates PROFet’s extrapolation performance using an out-of-sample test dataset from Trondheim municipality. The results show that PROFet accurately forecasts the hourly heating load during the space-heating season but is less accurate during periods when domestic hot water needs dominate. The tool exhibits nearly identical performance across the three cases, except for efficient kindergartens, where the estimation accuracy is lower.

In scale-resolving simulations such as Large Eddy Simulations (LES), the spatial discretization scheme of the convective term plays a crucial role in avoiding interference between the numerical errors and the subgrid-scale model. Accurate schemes lead to lower truncation errors and better predictions of turbulent flows without the need for an excessively refined grid. To this end, a new second-order finite-difference scheme (HCDS6) has been developed for incompressible flows and orthogonal staggered grids. Compared to the standard second-order scheme, the new scheme has significantly lower dispersion errors. Compared to existing high-order schemes, the numerical stencil of HCDS6 is more compact, which makes it easier to implement, especially considering boundary conditions around complex geometries using Immersed Boundary Methods (IBM). The HCDS6 scheme conserves the discrete momentum with limited production or dissipation of discrete kinetic energy, which guarantees its numerical stability. Its performance is evaluated using an open-source CFD package called REEF3D. Three benchmarks demonstrate the key properties and performance of the scheme: the convection of an isentropic vortex, the Taylor-Green vortex flow, and turbulent channel flow. Its relatively low dispersion errors, combined with ease of implementation, make the HCDS6 scheme a promising candidate for efficient scale-resolving simulations of turbulent flows.

The present work introduces a novel yet smart energy system to decarbonize the energy mix, provide cost-effective green energy, and help to achieve sustainable energy production/storage/usage. Smart hydronic units and multiple controllers are the backbone of this idea, which aims to monitor energy conversion among components, the grid, and users through an innovative rule-based framework. This clever integration results in smaller components, bidirectional grid connection, and increased penetration of renewable energy sources into the local energy network. The system is driven by photovoltaic thermal panels and a biomass heater integrated with a heat pump and internal combustion engine. The TRNSYS-MATLAB framework evaluates the system's practicality from all aspects. Multi-objective optimization based on the grey wolf approach equipped with artificial intelligence is added to find the most optimal state. Compared to the conventional system in Norway (hydropower+wind), the proposed smart integration achieves up to 55% and 5.4% reduction in energy costs and emission index. In particular, the carbon emission index is lowered to 36.3 g/kWh, and the energy cost is decreased to 38.4 $/MWh. Also, the parametric analysis indicates a conflictive change among key metrics when altering a variable, necessitating the multi-objective optimization to achieve a balancing trade-off. The optimization reduces the emission index, investment cost, and energy cost by about 1.8 g/kWh (5%), 156,000 $/year (2.5%), and 1.5 $/MWh (4%) while improving the efficiency by about 1.7% compared to the design condition. The suggested system generates 17,830 MW/year of clean energy and can mitigate carbon dioxide emissions by 552,000 kg per year compared to the Norwegian energy mix.

Maintaining acceptable indoor air quality within operating rooms (ORs) in healthcare facilities is vital to prevent surgical site infections (SSIs). Two prevalent ventilation systems, laminar airflow (LAF) and mixing ventilation (MV), are widely used in ORs for various surgical operations. However, several studies have stated that these systems have slightly different SSI rate controls. Earlier studies discovered the airflow velocity above the surgical incision in LAF-equipped ORs to be twice as high as in MV-equipped ones. In addition, the placement of surgical lamps and different airflow patterns add complexity to the study of the surgical microenvironment. The objective of this study is to characterize the airflow pattern in the surgical microenvironment by computational fluid dynamics (CFD) simulations and experimental measurements in the newly built operating room lab at NTNU. The findings may provide new guidelines for standards development ensuring safer surgeries in healthcare facilities. The research project is called: Reduction of postoperative surgical site infection (POSI) through the development of XR tool. The project is supported by the Norwegian Research Council and Norconsult.

The present study aims to satisfy the energy demands of a set of Norwegian residential structures with the least carbon dioxide and most renewable energy. Real-time data on building domestic hot water (DHW), heating, and electricity usage is used to plan and expand the renewable energy supply side. PVT panels provide DHW and electricity in the hybrid solar and biomass energy system. Heat is produced by the digester and heat pump. Also used is a twofold effect absorption refrigeration system for cooling. Rule-based regulation manages heat streams and redirects flows on the supply side. We provide the plant's size and execute the dynamic energy simulation. Electricity and biomass expenses determine building heating. The system is then tuned for operational conditions and compared to the design point. PVT may generate over 80% of annual DHW. Summertime radiation is more intense and can be turned into cooling energy, therefore 64.8% of cooling output comes from it. Digester/CC heats 66.55% of the structure, suggesting designers use biomass in winter due to increased energy costs. A parametric analysis shows that increasing PVT duration and tank size affects efficiency and emissions differently. Cost, efficiency, and emission index at TOPSIS are 9.73 $/hr, 36.8%, and 7.75 kg/MWh, according to optimization findings.

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This work investigates the potential of simplified control approaches to deploy the building energy flexibility (BEF), here for the shifting of the space-heating load in a real-life educational building. The educational building is a passive house school where internal gains play an important role in the room thermal dynamics. It is equipped with a waterborne heat distribution system connected to district heating. The building is located in Elverum, Norway, having a strong heating-dominated climate. Focusing on schedule-based control strategies for pre-heating the building in the mornings, the study demonstrates significant load shifting to off-peak hours. The energy use during typical peak hours (7a.m. to 9a.m.) is reduced by 50% while the daily energy use is not increased significantly, highlighting the effectiveness of this simple approach. Occupant acceptance surveys among the pupils reveal no significant differences in thermal comfort perception between the periods with business-as-usual and schedule-based controls. Practical challenges in integrating simplified controls are highlighted and underscore the importance of considering energy flexibility during the building tendering and design phase. Bridging the gap between theoretical research and real-life applications, this research contributes to the advancement of energy-flexible operation of real-life buildings.

Model predictive control (MPC) is a promising optimal control technique for activating building energy flexibility using its thermal mass. The performance of the MPC controller is directly related to the accuracy of the model prediction. Grey -box models, based on physical laws and calibrated on measurement data, are commonly used to represent the building thermal dynamics in MPC. Most research works use Linear Time -Invariant (LTI) grey -box models even though weather conditions vary significantly throughout the heating season. This is critical as inaccurate model prediction can lead to a lower performance of the MPC controller. This study introduces two adaptive MPC schemes to overcome this limitation of LTI models. The first one, called the Partially Adaptive MPC, only updates the effective window area of the prediction model. The second one, called the Fully Adaptive MPC, updates all the parameters of the grey -box model. The adaptive MPC performance is compared with MPC using LTI models in two different tests. The simulation -based results show that MPC based on LTI performs well if the control model is trained during a period with similar weather conditions as the period when the MPC will be applied. The Partially Adaptive MPC is unable to deliver satisfactory prediction performance due to the limited number of parameters that are updated. The Fully Adaptive MPC has the best performance compared to the other MPCs, especially as it avoids thermal comfort violations.

Efforts to enhance the energy efficiency of heating, ventilation, and air conditioning (HVAC) systems have been bolstered by technical advancements and stringent regulations. However, HVAC systems not only emit during operation due to energy consumption but also have significant embodied emissions, which recent studies show can exceed those of the operational phase. This study introduces an optimization framework aimed at minimizing lifetime emissions-both operational and embodied-for ventilation systems, an area previously underexplored. The optimization framework incorporates detailed calculations of pressure drop, fan power and newly developed life cycle ventilation inventory data with a life cycle assessment perspective. A case study of ventilation ductwork in a "BREEAM Excellent" certified energy-efficient building in Norway demonstrates the application of this optimization framework. Findings indicate that for this case, optimizing ductwork dimensions can reduce lifetime emissions of the ventilation system by 15 %, compared to the existing designs with an emission intensity of 0.3 kg CO2/kWh. Further, the study examines how the emission intensity of electricity generation and service lifetime influence total emissions, highlighting the growing importance of embodied emissions as electricity generation becomes cleaner. This underscores the necessity of considering both operational and embodied emissions in design decisions. This study presents an optimization tool for low- emissions ventilation design, capable of processing diverse layouts and aiding in decarbonizing ventilation systems towards achieving zero-emission buildings. Future integration with building information modeling (BIM) and artificial intelligence (AI) could further enhance autonomous low-carbon design and decision-making.