Building Information Modelling Energy Performance Assessment on Domestic Dwellings: A Comparative Study

Building Information Modelling (BIM) is growing in pace, not only in design and construction stages, but also in the analysis of facilities throughout their life cycle. With this continued growth and utilisation of BIM processes, comes the possibility to adopt such procedures, to accurately measure the energy efficiency of buildings, to accurately estimate their energy usage. To this end, the aim of this research is to investigate if the introduction of BIM Energy Performance Assessment in the form of software analysis, provides accurate results, when compared with actual energy consumption recorded. Through selective sampling, three domestic case studies are scrutinised, with baseline figures taken from existing energy providers, the results scrutinised and compared with calculations provided from two separate BIM energy analysis software packages. Of the numerous software packages available, criterion sampling is used to select two of the most prominent platforms available on the market today. The two packages selected for scrutiny are Integrated Environmental Solutions - Virtual Environment (IES-VE) and Green Building Studio (GBS). The results indicate that IES-VE estimated the energy use in region of ±8% in two out of three case studies while GBS estimated usage approximately ±5%. The findings indicate that the introduction of BIM energy performance assessment, using proprietary software analysis, is a viable alternative to manual calculations of building energy use, mainly due to the accuracy and speed of assessing, even the most complex models. Given the surge in accurate and detailed BIM models and the importance placed on the continued monitoring and control of buildings energy use within today’s environmentally conscious society, this provides an alternative means by which to accurately assess a buildings energy usage, in a quick and cost effective manner.

Building performance evaluation of domestic energy efficient retrofits in current and future climates

Approximately half of the houses in Northern Ireland were built before any form of minimum thermal specification or energy efficiency standard was enforced. Furthermore, 44% of households are categorised as being in fuel poverty; spending more than 10% of the household income to heat the house to bring it to an acceptable level of thermal comfort. To bring existing housing stock up to an acceptable standard, retrofitting for improving the energy efficiency is essential and it is also necessary to study the effectiveness of such improvements in future climate scenarios. This paper presents the results from a year-long performance monitoring of two houses that have undergone retrofits to improve energy efficiency. Using wireless sensor technology internal temperature, humidity, external weather, household gas and electricity usage were monitored for a year. Simulations using IES-VE dynamic building modelling software were calibrated using the monitoring data to ASHARE Guideline 14 standards. The energy performance and the internal environment of the houses were then assessed for current and future climate scenarios and the results show that there is a need for a holistic balanced strategy for retrofitting.

Demand-side characterisation of the smart city for energy modelling.

This paper presents a new methodology for characterising the energy performance of buildings suitable for city-scale, top-down energy modelling. Building properties that have the greatest impact on simulated energy performance were identified via a review of sensitivity analysis studies. The methodology greatly simplifies the description of a building to decrease labour and simulation processing overheads. The methodology will be used in the EU FP7 INDICATE project which aims to create a master-planning tool that uses dynamic simulation to facilitate the design of sustainable, energy efficient smart cities.

Energy Optimization of Memory Intensive Parallel Workloads

Energy consumption is an important concern in modern multicore processors. The energy consumed by a multicore processor during the execution of an application can be minimized by tuning the hardware state utilizing knobs such as frequency, voltage etc. The existing theoretical work on energy minimization using Global DVFS (Dynamic Voltage and Frequency Scaling), despite being thorough, ignores the time and the energy consumed by the CPU on memory accesses and the dynamic energy consumed by the idle cores. This article presents an analytical energy-performance model for parallel workloads that accounts for the time and the energy consumed by the CPU chip on memory accesses in addition to the time and energy consumed by the CPU on CPU instructions. In addition, the model we present also accounts for the dynamic energy consumed by the idle cores. The existing work on global DVFS for parallel workloads shows that using a single frequency for the entire duration of a parallel application is not energy optimal and that varying the frequency according to the changes in the parallelism of the workload can save energy. We present an analytical framework around our energy-performance model to predict the operating frequencies (that depend upon the amount of parallelism) for global DVFS that minimize the overall CPU energy consumption. We show how the optimal frequencies in our model differ from the optimal frequencies in a model that does not account for memory accesses. We further show how the memory intensity of an application affects the optimal frequencies.

Simulation of whole building coupled hygrothermal-airflow transfer in different climates

The coupled heat, air and moisture transfer between building envelopes and indoor air is complicated, and has a significant influence on the indoor environment and the energy performance of buildings. In the paper, a model for predicting coupled multi-zone hygrothermal-airflow transfer is presented. Both heat and moisture transfer in the building envelope and multi-zone indoor airflow are simultaneously considered; their interactions are modeled. The coupled system model is implemented into Matlab–Simulink, and is validated by using a series of testing tools and experiments. The new program is applied to investigate the moisture transfer effect on indoor air humidity and building energy consumption in different climates (hot-humid, temperate and hot-dry climates). The results show that not accounting for hygrothermal effects in modeling will result in overestimation of energy costs for hot and humid climate situations and possible over sizing of plant leading to inefficient operation.

RFID based Efficient Lighting Control

The Kyoto Protocol and the European Energy Performance of Buildings Directive put an onus on governments
and organisations to lower carbon footprint in order to contribute towards reducing global warming. A key
parameter to be considered in buildings towards energy and cost savings is its indoor lighting that has a major
impact on overall energy usage and Carbon Dioxide emissions. Lighting control in buildings using Passive
Infrared sensors is a reliable and well established approach; however, the use of only Passive Infrared does not
offer much savings towards reducing carbon, energy, and cost. Accurate occupancy monitoring information can
greatly affect a building’s lighting control strategy towards a greener usage. This paper presents an approach for
data fusion of Passive Infrared sensors and passive Radio Frequency Identification (RFID) based occupancy
monitoring. The idea is to have efficient, need-based, and reliable control of lighting towards a green indoor
environment, all while considering visual comfort of occupants. The proposed approach provides an estimated
13% electrical energy savings in one open-plan office of a University building in one working day. Practical
implementation of RFID gateways provide real-world occupancy profiling data to be fused with Passive
Infrared sensing towards analysis and improvement of building lighting usage and control.

Azepanium-based ionic liquids as green electrolytes for high voltage supercapacitors

This work provides a first-time-study of Azepanium-based ionic liquids (ILs) as electrolyte components for electrochemical double layer capacitors (EDLCs). Herein, two Azepanium-based ILs, namely N-methyl, N-butyl-azepanium bis(trifluoromethanesulfonyl)imide (Azp(14)TFSI) and N-methyl, N-hexyl-azepanium bis(trifluoromethanesulfonyl)imide (Azp(16)TFSI) were compared with the established IL N-butyl, N-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide (Pyr(14)TFSI) in terms of viscosity, conductivity, thermal stability and electrochemical behavior in EDLC systems. The ILs' operative potentials were found to be comparable, leading to operative voltages up to 3.5 V without significant electrolyte degradation. 

Experimental analysis of air flow profiles in a double skin facade in a maritime climate

Glazed Double Skin Facades (DSF) offer the potential to improve the performance of all-glass building skins, common to commercial office buildings in which full facade glazing has almost become the standard. Single skin glazing results in increased heating and cooling costs over opaque walls, due to lower thermal resistance of glass, and the increased impact of solar gain through it. However, the performance benefit of DSF technology continues to be questioned and its operation poorly understood, particularly the nature of airflow through the cavity. This paper deals specifically with the experimental analysis of the air flow characteristics in an automated double skin façade. The benefit of the DSF as a thermal buffer, and to limit overheating is evaluated through analysis of an extensive set of parameters including air and surface temperatures at each level in the DSF, airflow readings in the cavity and at the inlet and outlet, solar and wind data, and analytically derived pressure differentials. The temperature and air-flow are monitored in the cavity of a DSF using wireless sensors and hot wire anemometers respectively. Automated louvre operation and building set-points are monitored via the BMS. Thermal stratification and air flow variation during changing weather conditions are shown to effect the performance of the DSF considerably and hence the energy performance of the building. The relative pressure effects due to buoyancy and wind are analysed and quantified. This research aims to developed and validate models of DSFs in the maritime climate, using multi-season data from experimental monitoring. This extensive experimental study provides data for training and validation of models.

The effect of water depth on the performance of a small surging wave energy converter

The effect of water depth on the performance of a small surging wave energy converter (WEC) is investigated analytically, numerically and experimentally. It is shown that although the average annual incident wave power is significantly reduced by water depth, a large proportion of this reduction is due to the dissipation of highly energetic, but largely unexploitable seas. It is also shown that the power capture is related more closely to incident wave force than incident wave power. Experimental results demonstrate that both the surge wave force and power capture of a flap-type WEC increase in shallow water.