Building energy performance modeling is essential for energy planning, management, and efficiency. This paper presents a space heating model suitable for auto-generating baseline models of existing ...multifamily buildings. Required data and parameter input are kept within such a level of detail that baseline models can be auto-generated from, and calibrated by, publicly accessible data sources. The proposed modeling framework consists of a thermal network, a typical hydronic radiator heating system, a simulation procedure, and data handling procedures. The thermal network is a lumped and simplified version of the ISO 52016-1:2017 standard. The data handling consists of procedures to acquire and make use of satellite-based solar radiation data, meteorological reanalysis data (air temperature, ground temperature, wind, albedo, and thermal radiation), and pre-processing procedures of boundary conditions to account for impact from shading objects, window blinds, wind- and stack-driven air leakage, and variable exterior surface heat transfer coefficients. The proposed model was compared with simulations conducted with the detailed building energy simulation software IDA ICE. The results show that the proposed model is able to accurately reproduce hourly energy use for space heating, indoor temperature, and operative temperature patterns obtained from the IDA ICE simulations. Thus, the proposed model can be expected to be able to model space heating, provided by hydronic heating systems, of existing buildings to a similar degree of confidence as established simulation software. Compared to IDA ICE, the developed model required one-thousandth of computation time for a full-year simulation of building model consisting of a single thermal zone. The fast computation time enables the use of the developed model for computation time sensitive applications, such as Monte-Carlo-based calibration methods.
This paper focuses on multi-family buildings in a Swedish city district, erected between 1965 and 1973, which are now in need of renovation. For the two types of multi-family buildings in the ...district, tower buildings and low-rise buildings, dynamic energy use is predicted by using an energy signature method. The energy signature is then used to calculate the primary energy use number of the building stock, according to calculations methods dictated by Swedish building regulations. These regulations are also used to assess which multi-family buildings are in need of renovation, based on the buildings’ primary energy use. For buildings that need energy renovations, it is simulated so that the energy use of each multi-family building complies with these same building regulations. The proposed methodology for simulating energy renovation also determines new energy signature parameters, related to building heat loss coefficient, balance temperature and domestic hot water usage. The effects of simulated renovation are displayed in a duration diagram, revealing how a large-scale renovation affects the district’s heat load in different annual periods, which affects the local district heating system. Sensitivity analysis is also performed before and after simulated energy renovation.
Reliable energy models are needed to determine building energy performance. Relatively detailed energy models can be auto-generated based on 3D shape representations of existing buildings. However, ...parameters describing thermal performance of the building fabric, the technical systems, and occupant behavior are usually not readily available. Calibration with on-site measurements is needed to obtain reliable energy models that can offer insight into buildings’ actual energy performances. Here, we present an energy model that is suitable for district-heated multifamily buildings, based on a 14-node thermal network implementation of the ISO 52016-1:2017 standard. To better account for modeling approximations and noisy inputs, the model is converted to a stochastic state-space model and augmented with four additional disturbance state variables. Uncertainty models are developed for the inputs solar heat gains, internal heat gains, and domestic hot water use. An iterated extended Kalman filtering algorithm is employed to enable nonlinear state estimation. A Bayesian calibration procedure is employed to enable assessment of parameter uncertainty and incorporation of regulating prior knowledge. A case study is presented to evaluate the performance of the developed framework: parameter estimation with both dynamic Hamiltonian Monte Carlo sampling and penalized maximum likelihood estimation, the behavior of the filtering algorithm, the impact of different commonly occurring data sources for domestic hot water use, and the impact of indoor air temperature readings.
In this study, the performance of different cooling technologies from energy and economic perspectives were evaluated for six different prototype residential Nearly Zero Energy Buildings (NZEBs) ...within a planned future city district in central Sweden. This was carried out by assessing the primary energy number and life cycle cost analysis (LCCA) for each building model and cooling technology. Projected future climate file representing the 2050s (mid-term future) was employed. Three cooling technologies (district cooling, compression chillers coupled/uncoupled with photovoltaic (PV) systems, and absorption chillers) were evaluated. Based on the results obtained from primary energy number and LCCA, compression chillers with PV systems appeared to be favorable as this technology depicted the least value for primary energy use and LCCA. Compared to compression chillers alone, the primary energy number and the life cycle cost were reduced by 13%, on average. Moreover, the district cooling system was found to be an agreeable choice for buildings with large floor areas from an economic perspective. Apart from these, absorption chillers, utilizing environmentally sustainable district heating, displayed the highest primary energy use and life cycle cost which made them the least favorable choice. However, the reoccurring operational cost from the LCCA was about 60 and 50% of the total life cycle cost for district cooling and absorption chillers, respectively, while this value corresponds to 80% for the compression chillers, showing the high net present value for this technology but sensitive to future electricity prices.
12.9% of the energy use in the EU originates from the commercial and public sector. It has therefore become a priority to optimize energy efficiency in these buildings. The purpose of this study has ...been to explore how energy demand in a new office building is affected by different internal heat gains, location, orientation, and façade design, and also to see how different indicators can change perspective on energy efficiency. The study was performed with simulations in IDA-ICE with different façade design and changes in internal heat gains (IHG), orientation, and location. Energy demand was then compared to two different indicators. Using a façade designed to lower solar heat gains had little effect on energy demand in the north of Sweden, but slightly more effect further south. The amount of internal heat gains had significant effect on energy demand. Making deeper studies on design and internal heat gains should therefore be prioritized in the beginning of new building projects so the most energy-efficient design can be chosen. When the indicator kWh/m2 was used, the cases with low internal heat gains were perceived as the most energy efficient, while when kWh/(m2 × hpers) (hpers = hours of use) was used, the cases with high occupancy and low electricity use were considered to be the most energy efficient. Therefore, revising the standardized indicator is of great importance.
The effect of mechanical night ventilation on thermal comfort and electricity use for cooling of a typical historic office building in north-central Sweden was assessed. IDA-ICE simulation program ...was used to model the potential for improving thermal comfort and electricity savings by applying night ventilation cooling. Parametric study comprised different outdoor climates, flow rates, cooling machine’s coefficient of performance and ventilation units’ specific fan power values. Additionally, the effect of different door schemes (open or closed) on thermal comfort in offices was investigated. It was shown that night ventilation cannot meet the building’s total cooling demand and auxiliary active cooling is required, although the building is located in a cold climate. Night ventilation had the potential in decreasing the percentage of exceedance hours in offices by up to 33% and decreasing the total electricity use for cooling by up to 40%. More electricity is saved with higher night ventilation rates. There is, however, a maximum beneficial ventilation rate above which the increase in electricity use in fans outweighs the decrease in electricity use in cooling machine. It depends on thermal mass capacity of the building, cooling machine´s coefficient of performance, design ventilation rate, and available night ventilation cooling potential (ambient air temperature).
Low-emissivity (low-E) window films are designed to improve the thermal comfort and energy performance of buildings. These films can be applied to different glazing systems without having to change ...the whole window. This makes it possible to apply films to windows in old and historical buildings for which preservation regulations often require that windows should remain unchanged. This research aims to investigate the impacts of low-E window films on the energy performance and thermal comfort of a three-story historical stone building in the cold climate of Sweden using the simulation software “IDA ICE”. On-site measurements were taken to acquire thermal and optical properties of the windows. This research shows that the application of the low-emissivity window film on the outward-facing surface of the inner pane of the double-glazed windows helped to reduce heat loss through the windows in winter and unwanted heat gains in summer by almost 36% and 35%, respectively. This resulted in a 6% reduction in the building’s annual energy consumption for heating purposes and a reduction in the percentage of total occupant hours with thermal dissatisfaction from 14% (without the film) to 11% (with the film). However, the relatively high price of the films and low price of district heating results in a rather long payback period of around 30 years. Thus, the films seem scarcely attractive from a purely economic viewpoint, but may be warranted for energy/environmental and thermal comfort reasons.
The European Union (EU) has implemented several policies to enhance energy efficiency. Among these policies is the objective of achieving energy-efficient renovations in at least 3% of EU buildings ...annually. The primary aim of this study was to offer a precise environmental comparison among four similar district-heated multifamily buildings that have undergone identical energy efficiency measures. The key distinguishing factor among them lies in the HVAC systems installed. The chosen systems were as follows: (1) exhaust ventilation with air pressure control; (2) mechanical ventilation with heat recovery; (3) exhaust ventilation with an exhaust air heat pump; and (4) exhaust ventilation with an exhaust air heat pump with a Photovoltaic (PV) panel. This study involved a life cycle assessment that relied on actual material data from the housing company and energy consumption measurements. This study covered a period of 50 years for thorough analysis. A sensitivity analysis was also conducted to account for various future scenarios of energy production. The findings revealed that the building with an exhaust air heat pump exhibited the lowest greenhouse gas emissions and the shortest carbon payback period (GBPT), needing only around 7 years. In contrast, the building with exhaust ventilation without heat recovery showed the highest emissions and the longest carbon payback period (GBPT), requiring approximately 11 years. Notably, the results were significantly influenced by future scenarios of energy production, emphasizing the crucial role of emission factors in determining the environmental performance of distinct renovation scenarios.
In this case study, the energy performance of a secondary school building from the 1960s in Gävle, Sweden, was modelled in the building energy simulation (BES) tool IDA ICE version 4.8 prior to major ...renovation planning. The objectives of the study were to validate the BES model during both occupied and unoccupied periods, investigate how to model airing and varying occupancy behaviour, and finally investigate energy use to identify potential energy-efficiency measures. The BES model was validated by using field measurements and evidence-based input. Thermal bridges, infiltration, mechanical ventilation, domestic hot water circulation losses, and space heating power were calculated and measured. A backcasting method was developed to model heat losses due to airing, opening windows and doors, and other occupancy behaviour through regression analysis between daily heat power and outdoor temperature. Validation results show good agreement: 3.4% discrepancy between space heating measurements and simulations during an unoccupied week. Corresponding monthly discrepancy varied between 5.5% and 10.6% during three months with occupants. Annual simulation indicates that the best potential renovation measures are changing to efficient windows, improved envelope airtightness, new controls of the HVAC system, and increased external wall thermal insulation.
Historical buildings account for a significant portion of the energy use of today’s building stock, and there are usually limited energy saving measures that can be applied due to antiquarian and ...esthetic restrictions. The purpose of this case study is to evaluate the use of the building structure of a historical stone building as a heating battery, i.e., to periodically store thermal energy in the building’s structures without physically changing them. The stored heat is later utilized at times of, e.g., high heat demand, to reduce peaking as well as overall heat supply. With the help of Artificial Intelligence and Convolutional Neural Network Deep Learning Modelling, heat supply to the building is controlled by weather forecasting and a binary calendarization of occupancy for the optimization of energy use and power demand under sustained comfortable indoor temperatures. The study performed indicates substantial savings in total (by approximately 30%) and in peaking energy (by approximately 20% based on daily peak powers) in the studied building and suggests that the method can be applied to other, similar cases.
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