Uncertainty analysis of climate change potential assessments of five building energy renovation measures in Sweden

The aim of this study is to assess the impact of the uncertainties of life cycle inventory (LCI) data for energy use and materials in life cycle assessments of standard energy renovation measures carried out in multi-family buildings in Sweden. Five energy renovation measures were assessed with regard to their climate change potential. Modules A1–A3 and module B6 were included in the assessment and the functional unit, 1 m2 heated floor area of a renovated building fulfilling the Swedish building regulations and with a calculation period of 20 years, was used. The uncertainty of LCI data for materials and energy were assessed using the Ecoinvent data quality system. This study shows that with two different energy mixes, all renovation measures result in a decrease in the climate change potential. The five renovation measures used in the simulations, with and without consideration to uncertainties, show a lower climate change potential when carried out than when not carried out. It is also shown in this study that the inclusion of the uncertainties of the input data did not have any impact on the overall decisions to renovate or not to renovate. However, this should not be regarded as a general conclusion. If a renovation measure were to have a higher level of material use, or if the “Future energy mix” were to be improved, uncertainty considerations could become much more important from a climate change perspective. Article Highlights All assessed energy renovation measures show a decrease in their climate change potential when carried out. The energy renovation measures with the largest decreases of climate change potential are also the measures with largest energy saving potential. When uncertainties are considered, there are no overlaps in the results when carrying out or not carrying out a renovation measure.

Comparing the economics of electric and water underfloor heating

Introduction. Using underfloor heating to maintain warm temperature inside manned rooms is a widely spread international practice. Domestic design organizations also take advantage of this solution, as it makes a positive impact on the indoor microclimate and thermal comfort. Underfloor heating outperforms traditional heating systems in terms of particular operational characteristics. The application of underfloor heating is a relevant issue, addressed by numerous publications, however, researchers tend to focus on the heat emission capacity of floors that have different constructions. The goal of this research is to analyze the economics of electric and water underfloor heating systems. Materials and methods. The aggregate cost method is employed to perform the economic analysis of underfloor heating systems. The co-authors have calculated capital and operating expenses, broken down by the years. The co-authors compare electric and water underfloor heating systems installed in the rooms having the floor area of 5, 10, and 20 sq. meters. The rooms are located in Moscow. Indoor heat losses are considered to be linearly dependent on the heated floor area. Results. The co-authors have calculated capital and operating expenses incurred in the above rooms. They have also drawn an aggregate heating cost graph for three rooms having two types of heating systems installed. The costs are broken down by the years. Conclusions. Although the research findings describe individual cases, they can serve as the basis for a general conclusion that the payback period of an underfloor heating system depends on the heated floor area and that electric underfloor heating systems are better for small rooms. Further studies can focus on alternative pipeline design systems, different power consumption modes of the pump depending on the circuit length, and non-continuous heating systems.

Simulation of Natural Ventilation Inside Tunnel Greenhouse

A study of the variation of the temperature and the speed under an open greenhouse with and without plant was developed and the effect of the wind speed on the internal climate under the greenhouse was analyzed by the use of the software Fluent-CFD based on the finite volume method. The airflow through the crop was introduced by using the porous medium approach. Three dimensional simulations which described turbulent flows in steady state were carried out and the turbulence was modeled by using the standard k-ε model. The air temperature variation shows a gradient from the sidewalls towards the center of the greenhouse due to the movement of the hot air rising towards the roof and another vertical gradient due to the air circulation above the surface of the heated floor. At the openings, the maximum air velocity was reached and the lowest values are observed in the middle of the greenhouse, at the crop level and at the corners. The variation of the climatic parameters affects greatly the growth of the plant. The results of the simulation given as airflows and temperature patterns are satisfactory while comparing them to those of the literature. These results can help to know the distribution of the internal climate inside the greenhouse, so they facilitate the openings design.

Investigation and comparison on thermal comfort and energy consumption of four personalized seat heating systems based on heated floor panels

The climate of Yangtze River Basin in China is cold and humid in winter. Conventional air-conditioning systems may cause high energy consumption and uncomfortable microclimatic conditions especially for lower body of indoor occupants. This study investigated four personalized seat heating systems, in a typical office room in Shanghai during winter, based on heated floor panels including heated floor panels + ordinary chair (HF-OC), heated floor panels + insulated chair (HF-IC), heated floor panels +insulated chair and leg box (HF-IC-LB) and overall personalized heating (OPH). The surface temperature of walls and heated floor panels, and the indoor air temperature at different positions were recorded with thermocouples. The hourly energy consumptions of the proposed personalized seat heating systems were measured and compared with a conventional split type air conditioner. Questionnaires of thermal sensation and comfort were carried out among 10 university students. Compared with HF-OC, HF-IC could improve the thermal comfort to a certain extent, while HF-IC-LB provided the optimal thermal micro-environment for the lower body other than other body parts. The OPH systems were proven effective to provide satisfactory thermal environment for all body parts at lower indoor temperature (12–16°C) with much less energy consumption than room air conditioners.

Mapping of Domestic Hot Water Circulation Losses in Buildings – Preliminary Results from 134 Measurements

The hot water circulation system in a building is a system which helps prevent Legionella problems whilst ensuring that tenants have access to hot water quickly. Poorly designed or implemented systems not only increase the risk to people’s health and thermal comfort, but even result in an increase in the energy needed for this system to function properly. Results from previous studies showed that the total hot water circulation system loss can be as high as 25 kWh/m2 heated floor area per year. The purpose of this project is to measure the total energy use per year of the hot water circulation system in about 200 multifamily dwellings of different ages to verify that a system loss of 4 kWh/m2, year is a realistic assumption for both newer and older/retrofitted buildings. The preliminary results from the first 134 measurements showed that the assumption of 4 kWh/m2, year is rarely fulfilled. An average energy use of more than three times this is more common, even in newer buildings. Whilst some of the total energy lost is used to heat the buildings, it is not desirable because it is an uncontrolled energy flow.

Energy Renovation versus Demolition and Construction of a New Building—A Comparative Analysis of a Swedish Multi-Family Building

This study addresses the life cycle costs (LCC) of energy renovation, and the demolition and construction of a new building. A comparison is made between LCC optimal energy renovations of four different building types with thermal performance, representing Swedish constructions from the 1940s, 1950s, 1960s, and 1970s, as well as the demolition of the building and construction of a new building that complies with the Swedish building code. A Swedish multi-family building from the 1960s is used as a reference building. LCC optimal energy renovations are identified with energy saving targets ranging between 10% and 70%, in addition to the lowest possible life cycle cost. The analyses show that an ambitious energy renovation is not cost-optimal in any of the studied buildings, if achieving the lowest LCC is the objective function. The cost of the demolition and construction of a new building is higher compared to energy renovation to the same energy performance. The higher rent in new buildings does not compensate for the higher cost of new construction. A more ambitious renovation is required in buildings that have a shape factor with a high internal volume to heated floor area ratio.

Control strategy for battery-supported photovoltaic systems aimed at peak load reduction

The use of photovoltaic (PV) technologies is one of the key means for achieving the balance between operational power demand and generation in net Zero Energy Buildings (nZEBs). However, direct use of PV power on-site is limited due to wide variability and uncertainty of PV output, the temporal mismatch between PV generation and load and other factors. Consequently, in addition to low self-consumption rates, the problem of peak grid load and peak PV feed into the grid persists. Batteries that are coupled to PV units may partially offer the solution to these problems, if operated under an intelligent control strategy. In this paper we proposed a forecast-based control strategy for battery-to-grid interaction aimed at enhancing selfconsumption and at reducing peak load. Python programming environment was used for data processing and algorithm development. Exemplification was made based on the reported hourly energy demand in one office building of 3000 m2 heated floor area located in Trondheim, Norway. Forecasting of electricity load profiles was based on the seasonal autoregressive integral moving average (SARIMA) model. For PV power forecasting, the algorithm communicated with external service – Solcast API. The search method for optimal scheduling of operational time and the extent of charging/discharging was proposed. The results showed that as opposed to conventional battery use, this control strategy allowed to achieve significantly more consistent grid interaction. It offered highly accurate battery scheduling on a day-ahead basis while utilising minimum historical data and computational resources. The algorithm may be beneficial for end-users and grid operators, and thus, it has a high potential for future integration into building energy supply systems.