A probabilistic energy model for non-domestic building sectors applied to analysis of school buildings in greater London

The diversity of non-domestic buildings at urban scale poses a number of difficulties to develop models for large scale analysis of the stock. This research proposes a probabilistic, engineering-based, bottom-up model to address these issues. In a recent study we classified London's non-domestic buildings based on the service they provide, such as offices, retail premise, and schools, and proposed the creation of one probabilistic representational model per building type. This paper investigates techniques for the development of such models. The representational model is a statistical surrogate of a dynamic energy simulation (ES) model. We first identify the main parameters affecting energy consumption in a particular building sector/type by using sampling-based global sensitivity analysis methods, and then generate statistical surrogate models of the dynamic ES model within the dominant model parameters. Given a sample of actual energy consumption for that sector, we use the surrogate model to infer the distribution of model parameters by inverse analysis. The inferred distributions of input parameters are able to quantify the relative benefits of alternative energy saving measures on an entire building sector with requisite quantification of uncertainties. Secondary school buildings are used for illustrating the application of this probabilistic method. © 2012 Elsevier B.V. All rights reserved.

Interactions between building integrated photovoltaics and microclimate in urban environments

BIPV (building integrated photovoltaics) has progressed in the past years and become an element to be considered in city planning. BIPV has significant influence on microclimate in urban environments and the performance of BIPV is also affected by urban climate. The thermal model and electrical performance model of ventilated BIPV are combined to predict PV temperature and PV power output in Tianjin, China. Then, by using dynamic building energy model, the building cooling load for installing BIPV is calculated. A multi-layer model AUSSSM of urban canopy layer is used to assess the effect of BIPV on the Urban Heat Island (UHI). The simulation results show that in comparison with the conventional roof, the total building cooling load with ventilation PV roof may be decreased by 10%. The UHI effect after using BIPV relies on the surface absorptivity of original building. In this case, the daily total PV electricity output in urban areas may be reduced by 13% compared with the suburban areas due to UHI and solar radiation attenuation because of urban air pollution. The calculation results reveal that it is necessary to pay attention to and further analyze interactions between BIPV and microdimate in urban environments to decrease urban pollution, improve BIPV performance and reduce cooling load. Copyright © 2006 by ASME.

Interactions between Building Integrated Photovoltaics and microclimate in urban environments

BIPV(Building Integrated Photovoltaics) has progressed in the past years and become an element to be considered in city planning. BIPV has influence on microclimate in urban environments and the performance of BIPV is also affected by urban climate. The effect of BIPV on urban microclimate can be summarized under the following four aspects. The change of absorptivity and emissivity from original building surface to PV will change urban radiation balance. After installation of PV, building cooling load will be reduced because of PV shading effect, so urban anthropogenic heat also decreases to some extent. Because PV can reduce carbon dioxide emissions which is one of the reasons for urban heat island, BIPV is useful to mitigate this phenomena. The anthropogenic heat will alter after using BIPV, because partial replacement of fossil fuel means to change sensible heat from fossil fuel to solar energy. Different urban microclimate may have various effects on BIPV performance that can be analyzed from two perspectives. Firstly, BIPV performance may decline with the increase of air temperature in densely built areas because many factors in urban areas cause higher temperature than that of the surrounding countryside. Secondly, the change of solar irradiance at the ground level under urban air pollution will lead to the variation of BIPV performance because total solar irradiance usually is reduced and each solar cell has a different spectral response characteristic. The thermal model and performance model of ventilated BIPV according to actual meteorologic data in Tianjin(China) are combined to predict PV temperature and power output in the city of Tianjin. Then, using dynamic building energy model, cooling load is calculated after BIPV installation. The calculation made based in Tianjin shows that it is necessary to pay attention to and further analyze interaction between them to decrease urban pollution, improve BIPV Performance and reduce colling load. Copyright © 2005 by ASME.

The ensemble statistics of the band-averaged energy of a random system

This paper is concerned with the response statistics of a dynamic system that has random properties. The frequency-band-averaged energy of the system is considered, and a closed form expression is derived for the relative variance of this quantity. The expression depends upon three parameters: the modal overlap factor m, a bandwidth parameter B, and a parameter α that defines the nature of the loading (for example single point forcing or rain-on-the-roof loading). The result is applicable to any single structural component or acoustic volume, and a comparison is made here with simulation results for a mass loaded plate. Good agreement is found between the simulations and the theory. © 2003 Published by Elsevier Ltd.

The ensemble statistics of the energy of a random system subjected to harmonic excitation

This paper is concerned with the ensemble statistics of the response to harmonic excitation of a single dynamic system such as a plate or an acoustic volume. Random point process theory is employed, and various statistical assumptions regarding the system natural frequencies are compared, namely: (i) Poisson natural frequency spacings, (ii) statistically independent Rayleigh natural frequency spacings, and (iii) natural frequency spacings conforming to the Gaussian orthogonal ensemble (GOE). The GOE is found to be the most realistic assumption, and simple formulae are derived for the variance of the energy of the system under either point loading or rain-on-the-roof excitation. The theoretical results are compared favourably with numerical simulations and experimental data for the case of a mass loaded plate. © 2003 Elsevier Ltd. All rights reserved.