Abstract
The focused investigation of building design is necessary to understand and quantify the implication of different design parameters on their energy performance. The design of future buildings is a major challenge, as current designs may be inappropriate in a future with global warming due to climate change impacts. In addition this understanding is necessary to be able to predict timing and profile of future energy demand, which is crucial for the long-term planning of energy infrastructures – particularly electricity. In this paper, the Morris Elementary Effects method is used as a screening method, to identify the key parameters of the design and operation of office buildings that affect the estimation of space cooling peak load and annual energy demand. Internal heat gains, cooling set-point and ventilation rates are identified as the parameters with larger implications for both annual and peak space cooling demand. In future climate scenarios, the magnitude of change of annual space cooling demand is significantly (around five times) larger than the change in the peak demand. Asides from the potential increase of space cooling demand in future scenarios, the sensitivity of the space cooling demand relative to the change in design parameters is potentially much larger.
Highlights
Mitigation and adaptation to Climate Change (CC) impacts will be one of the most important challenges of the twenty-first century
The analysis presented here has tested the input variation with this range of parameters, the distribution of conditions used, and it does not intend to represent the statistical representation of the parameters in the current office building stock
Abela et al [6] concluded average peak cooling power in the UK is 50-75 W.m-2. This peak value is significant behind the rule of thumb for office building cooling plants given in CIBSE guide F [31], which may be extremely conservative in assumptions for operating conditions
Summary
Mitigation and adaptation to Climate Change (CC) impacts will be one of the most important challenges of the twenty-first century. The UK Climate Projections produced in 2009 (UKCP09) estimate that the increase in maximum summer temperatures in the UK may be between 2 and 10°C by the 2080s in comparison to the baseline period (1960-1990) [1]. The sensitivity of building energy model outputs can be explored by using automated parametric simulation which imposes variation on the domain of input parameters. This can enable the analysis of the robustness of the results generated from the execution of a Sensitivity Analysis (SA) [12]. Sensitivity indices of input parameters can be calculated based on the results generated by the simulation of models
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