Estimating uncertainty when using transient data in steady-state calculations

When using measurement data for monitoring there is often a desire for steady-state analysis. On-line condition monitoring and fault detection systems are typical applications where the traditional way of treating transient data is to remove it using methods that require tuning using thresholds. This paper suggests an alternative approach where the uncertainty estimate in a particular variable is increased in response to the presence of transients and through propagation, varies the uncertainty in the result accordingly. The formulation of the approach is described and applied to two examples from building HVAC systems. The approach is demonstrated to be a pragmatic tool that can be used to increase the robustness of calculations from time series data

Uncertainty in whole house monitoring

Monitoring energy and temperatures in dwellings is becoming commonplace due to the reduction in sensing costs. Measurements can be used for informing the occupants on their energy as well as developing better inputs for building performance simulation and verifying analysis. In a home monitoring environment making sense of this data can be difficult as the number of measurements increases; one of the key challenges for the homeowner and for organisations that collect and analysis energy data is understanding what can and cannot be ‘seen’ in the data. In building simulation, there is a growing interest in applying uncertainty to generate robust model predictions, however there is also a need to understand the uncertainties in measurements used. What is often missed in these analysis is an evaluation of the uncertainties in the measurements in relation to the intended analysis. This paper presents a set of typical domestic energy monitoring measurements that have recently been collected as part of a 4 year research project in the UK. Levels of uncertainty are evaluated and the consequences for typical metrics used in energy and comfort analysis are discussed

Estimating the air change rates in dwellings using a heat balance approach

Infiltration and ventilation rates in domestic buildings vary with construction type, weather conditions and the operation of openings in the fabric. Generating good estimates of ventilation is important for modelling, simulation and performance assessment as it has a significant impact on energy consumption. Physical tests can be applied to estimate leakage, but this is cumbersome and impractical to apply in most cases. This paper applies a heat balance approach to energy monitoring data to estimate a parameter that describes the combined ventilation and infiltration rates in real family homes. These estimates are compared with published values and a model is presented that describes the air change rate as a function of user behaviour (control of openings) and varying wind speed. The paper demonstrates that it is possible to estimate plausible air change rates from such data

Uncertainty in model based condition monitoring

Model based techniques for automated condition monitoring of HVAC systems have been under development for some years. The generation of false alarms has been identified as a principal factor affecting the potential usefulness of condition monitoring in HVAC applications. Results from the application of these methods to systems installed in real buildings have highlighted the difficulty in selecting good alarm thresholds that balance robustness (lack of false alarms) and sensitivity (early detection). This paper demonstrates that this balance can be met in a transparent and analytical manner, through the application of uncertainty analysis. The paper discusses the sources of uncertainty associated with component models and system measurements. A Condition Monitoring scheme applied to a typical HVAC cooling coil subsystem installed in a real building is presented. Faults are artificially introduced into the system and are used in conjunction with fault-free operation to demonstrate the sensitivity and robustness of the scheme. The principle conclusions drawn by the paper consider the likely minimum magnitudes of faults that can be detected in typical HVAC systems, without false alarm generation. More broadly however, the paper demonstrates that the issue of uncertainty affects all aspects of system monitoring, modelling and control

The implications of heat electrification on national electrical supply-demand balance under published 2050 energy scenarios

Published UK 2050 energy scenarios specify a range of decarbonised supply side technologies combined with electrification of transportation and heating. These scenarios are designed to meet CO2 reduction targets whilst maintaining reliability of supply. Current models of the UK energy system either make significant assumptions about the role of demand side management or do not carry out the analysis at sufficient resolution and hence determining the impact of heat electrification on the reliability of supply of the scenarios is not possible. This paper presents a new model that estimates national supply and demand, hour-by-hour. Calculations are based on 11 years of weather data which allows a probabilistic assessment of deficit frequency throughout the day. It is found that achieving demand reduction targets are far more important than meeting electrification targets and that significant adoption of CHP is most likely to deliver a viable energy future for the UK

Uncertainty in the performance validation of HVAC Systems

A first principles based model approach to AHU cooling coil performance validation is presented. The model of correct operation is compared to that observed in the real system. In the scheme, uncertainty in the measurements and the models is evaluated to generate robust thresholds for decision making. The approach describes the design intent by estimating certain model parameters from design data and expert knowledge. The method systematically incorporates the uncertainty in these parameter estimates in the calculation of the system validation threshold. This yields a definite, transparent indication of system performance to a stated level of confidence. The approach is demonstrated on a cooling coil subsystem installed in an air-handling unit serving zones in a real building

Factors affecting ‘end-of-day’ window position in a non-air-conditioned office building

This paper presents a longitudinal study observing people's use of windows in mixed mode cellular offices, and sets out to identify factors other than air temperature, that have a significant influence on window operation. The work focuses on the final position of the window at the end of the working day. The results have been compared to other published work and the building is found to have similar characteristics when it and its occupants are treated as a whole. When sub-sets of the data are examined, the factors of season, floor level, gender, and personal preference emerge as having a statistically significant effect on the end-of-day window position in the building examined and these findings are properly discussed with relevant references

Estimating waste heat from domestic hot water systems in UK dwellings

Domestic Hot Water (DHW) production can account for a quarter of the energy consumed in UK dwellings and this proportion is likely to increase as the energy required for space heating reduces in order to achieve demand reduction targets. As the margins for improving the performance of heating system technologies diminish, the need for improving modelling accuracy and precision increases. Although studies have considered DHW use, there is a lack of reflection on the consumption and performance of systems in contemporary UK dwellings. This paper is based on two family homes and investigates heat losses from DHW networks using high resolution demand data combined with an analytical model. The model estimates are compared to widely used building performance models and it is found that the models may over estimate the heat losses by a significant amount and that short draw-offs are particularity influential in determining the amount of heat wasted

A critical software review - how is hot water modelled in current building simulation ?

In a changing climate and with ever increasing energy standards that lead to low and zero energy buildings, the provision of hot water in buildings will become more significant in relation to the overall energy consumption. Higher demand on the provision of hot water consumption has been documented and will occur around activities such as laundry, dishwashing, food preparation, bathing and cleaning activities. The accurate prediction and simulation of hot water in building design is therefore crucial and we need to rethink how we estimate the amount of hot water in our buildings. This paper will investigate how hot water demand and provision in homes is simulated via a number of different tools. The input and output differences with respect to hot water are compared to measured data of a building in the UK

Decarbonising domestic heating: what is the peak GB demand?

Around 80% of domestic heat demand in Great Britain (GB) is supplied by natural gas, but continuing to heat dwellings in this way is unlikely to be compatible with national emission reduction targets. Electrical heating using heat pumps is expected to play a significant role in future space heating and hot water provision. The assessment of future heating technologies requires knowledge of the current demand for heat at short time intervals in order to evaluate peak demands and possible storage requirements. Existing half-hourly national heat demand estimates are built on data from small samples of dwellings. This paper provides estimates of GB domestic heat demand under mild, normal and cold weather conditions based on data from over 6000 dwellings collected between May 2009 and July 2010 that participated in the GB smart meter trial. The calculated peak domestic heat demand of 170 GW is around 40% lower than previously calculated suggesting that the difficulties surrounding the electrification of heat are far less profound than previously assumed. These results can be used in the development of future energy pathways and scenarios