Jérôme Henri Kämpf

A hybrid CMA-ES and HDE optimisation algorithm with application to solar energy potential

This paper describes the results of initial experiments to apply computational algorithms to explore a large parameter space containing many variables in the search for an optimal solution for the sustainable design of an urban development using a potentially complicated fitness function. This initial work concentrates on varying the placement of buildings to optimise solar irradiation availability. For this we propose a hybrid of the covariance matrix adaptation evolution strategy (CMA-ES) and hybrid differential evolution (HDE) algorithms coupled with an efficient backwards ray tracing technique. In this paper we concentrate on the formulation of the new hybrid algorithm and its testing using standard benchmarks as well as a solar optimisation problem. The new algorithm outperforms both the standalone CMA-ES and HDE algorithms in benchmark tests and an alternative multi-objective optimisation tool in the case of the solar optimisation problem.

A comparison of global optimization algorithms with standard benchmark functions and real-world applications using EnergyPlus

There is an increasing interest in the use of computer algorithms to identify combinations of parameters which optimise the energy performance of buildings. For such problems, the objective function can be multi-modal and needs to be approximated numerically using building energy simulation programs. As these programs contain iterative solution algorithms, they introduce discontinuities in the numerical approximation to the objective function. Metaheuristics often work well for such problems, but their convergence to a global optimum cannot be established formally. Moreover, different algorithms tend to be suited to particular classes of optimization problems. To shed light on this issue we compared the performance of two metaheuristics, the hybrid CMA-ES/HDE and the hybrid PSO/HJ, in minimizing standard benchmark functions and real-world building energy optimization problems of varying complexity. From this we find that the CMA-ES/HDE performs well on more complex objective functions, but that the PSO/HJ more consistently identifies the global minimum for simpler objective functions. Both identified similar values in the objective functions arising from energy simulations, but with different combinations of model parameters. This may suggest that the objective function is multi-modal. The algorithms also correctly identified some non-intuitive parameter combinations that were caused by a simplified control sequence of the building energy system that does not represent actual practice, further reinforcing their utility.There is an increasing interest in the use of computer algorithms to identify combinations of parameters that optimize the energy performance of buildings. For such problems, the objective function can be multi-modal and needs to be approximated numerically using building energy simulation programs. As these programs contain iterative solution algorithms, they introduce discontinuities in the numerical approximation to the objective function. Metaheuristics often work well for such problems, but their convergence to a global optimum cannot be established formally. Moreover, different algorithms tend to be suited to particular classes of optimization problems.  To shed light on this issue, we compared the performance of two metaheuristics, the hybrid CMA-ES/HDE and the hybrid PSO/HJ, in minimising standard benchmark functions and real-world building energy optimization problems of varying complexity. From this, we find that the CMA-ES/HDE performs well on more complex objective functions, but that the PSO/HJ more consistently identifies the global minimum for simpler objective functions. Both identified similar values in the objective functions arising from energy simulations, but with different combinations of model parameters. This may suggest that the objective function is multi-modal. The algorithms also correctly identified some non-intuitive parameter combinations that were caused by a simplified control sequence of the building energy system that does not represent actual practice, further reinforcing their utility.

A new device for dynamic luminance mapping and glare risk assessment in buildings

High dynamic range imaging has been shown to be a reliable tool to assess luminance maps and glare risk probability in buildings. However, there are some limitations of image capturing time, especially when dealing with highly dynamic and contrasted daylight situations. We used a newly developed prototype of a digital camera which contains a high dynamic range pixel array chip, with a logarithmic scale for encoding. This type of camera allows to effectively assessing luminance, contrast and contrast directions, by taking only a single image or by performing real time recordings. The device was equipped with a fisheye lens and V-lambda filters to adapt the camera’s spectral sensitivity to the human eye. After spectral as well as photometric calibration and vignetting correction, the device was tested to perform luminance mapping of real scenes. The results showed that luminance maps of a room can be efficiently assessed under dynamic daylight and mixed day- and electric lighting conditions in a very short time (i.e. 100 ms), when compared to classical HDR imaging techniques. This allows us to calculate glare indexes of a scene simultaneously. The camera opens a variety of new applications as a useful tool for architects, building designers and lighting experts. The device can be used to easily monitor daylight availability and glare indexes in existing buildings and further developments for advanced (day-) lighting control can be envisaged.

Ground temperature modelling: the case study of rue des maraîchers in Geneva

This paper presents a methodology to approximate the urban heat island effect by using a PostgreSQL database and CitySim software, a simulation tool to evaluate urban energy flows. A ground temperature model has been developed for shallow depths (until 4m), which reproduces the phenomena of heat transfer into the ground on an hourly basis. This model is further used to predict the outdoor ground surface temperature, which is an indicator of the urban heat island effect. A PostgreSQL database which contains information such as the building footprints, geographical location, address, construction date, energy system etc. of the buildings was modified to include data relative to this model. A case study has been performed in a small neighbourhood, Rue des Maraichers, in Geneva (Switzerland) in order to illustrate the usage of this tool to analyse the surface temperature of asphalted roads and green alleys. Finally, a methodology has been introduced to predict the urban heat island effect using this temperature.

Visualizing street orientation and solar radiation in relation to complex topography

Street networks can be visualized in various ways depending on the purpose. Here we introduce (in the present context) a new technique for visualizing the orientation of street networks in relation to complex topography. The technique is tested on the city of Sheffield, England, with a current population of about 555,500 (in 2010) and a total street number of 23,500. Using digital elevation maps and unique historical datasets, we show how the street network of Sheffield has expanded in a complex topographical environment for close to three centuries, that is, since 1736. The results demonstrate how the topography has affected the spatial orientation of the evolving network. We quantify the network geometry through entropy analysis; entropy is a measure of dispersion or spreading. The results show that the orientation entropy of the network has gradually increased with time. In 1736 the network was primarily composed of orthogonal streets, and had comparatively low entropy. As the network expanded the topographical constraints have contributed to the street orientation becoming more uniform on the rose, resulting in increasing entropy. The analysis also shows that the entropy of the central part of the present network is lower than that of the outer and younger parts. The potential solar radiation for Sheffield is also calculated, visualized, and compared with the topography model and the street network density. The results show that the network density (number of streets per unit area) correlates solar radiation; high-density parts of the network tend to coincide with high-intensity solar radiation.

Multi-criteria analysis for the integrated performance assessment of complex fenestration systems

ABSTRACT Complex fenestration systems (CFS) designed to collect and redirect daylight from the sky-vault are generally placed on the upper part of a window in order to improve the distribution of indoor daylight. Due to their additional function as solar protection, their use might contribute to the mitigation of the unfavourable effects that the admission of daylight signifies, especially in buildings located in prevailing sunny climates (risk of glare and overheating). An appropriate selection of the CFS that better contributes to improve the interior daylight environment would imply an integrated performance assessment taking into account relevant aspects such as indoor daylight distribution and the visual and thermal comfort of occupants. However, such an assessment implies the use of performance criteria with different targets; therefore, in order to evaluate their overall performance, a multi-criteria analysis is applied in this study. The method presented here describes a comprehensive evaluation to determine those CFS that better contribute to an improved indoor daylighting environment in a building located in a prevailing sunny climate. The CFS performance assessment was undertaken with computer simulations using their bi-directional transmission distribution function (BTDF).

Integration of outdoor human comfort in a building energy simulation database using CityGML Energy Ade

Handling data needed by Building Energy Simulation (BES) tools can be a tedious task, especially at the urban scale. Besides BES, users often have different needs (building energy use, human comfort, integration of renewables, urban planning…) in mind when using simulation tools, but often have access to the same dataset. To simplify and harmonize the process of obtaining a homogeneous dataset, we make use of a PostgreSQL database in the CityGML file format using the Energy Application Domain Extension (ADE), which can be accessed remotely to retrieve data. CityGML with Energy ADE is an open data model with the objective of having a common platform to store and exchange 3D information and energy data between municipalities, professionals and researchers. The structure of the CityGML covers the following modules: geometry, construction, occupancy and energy systems. However, in the CityGML structure an important parameter to describe the city livability is missing: the outdoor human comfort. Considering this, we propose to further develop the database, by adding outdoor human comfort parameters and results. A case study of the Ecole Polytechnique Federale de Lausanne (EPFL) campus will be set-up, stored in the database and simulated with the software CitySim. The resulting human comfort indices will further be sent back to the improved database for an offline analysis with GIS tools. With this new development, the CityGML with Energy ADE can benefit from information on the urban microclimate and its impact on people activities and wellbeing.

Overheating reduction of a cold formed steel-framed building using a hybrid evolutionary algorithm to optimize different PCM solutions

Cold formed steel-framed constructions have been strongly disseminated with particular emphasis on the residential sector due to their fast execution, quality control and final cost. However, this construction typology presents a weakness associated with a low thermal inertia and a consequential risk of overheating. The present research addresses the overheating rate reduction of a cold formed steelframed building located in the coastal region of mainland Portugal, a particular environment considering the combination of the high outdoor temperature amplitude and the lack of thermal inertia of such building typology. To overcome this weakness, different phase change materials solutions (PCMs) were incorporated into the partition walls and ceilings of south oriented compartments. Thus, thermal energy storage provided by the PCMs solutions play a crucial role in the indoor thermal regulation of the building by minimizing indoor temperature peaks and amplitude improving indoor thermal comfort with lower energy demand. To optimize the PCM solution in order to reduce the rate of overheating, a hybrid evolutionary algorithm was used in conjunction to the EnergyPlus® simulation engine, adapting a list of parameters. This study was extended to identify the best PCM solution to minimize, in some cases prevent, the overheating risk for different climate applications in Portugal mainland. The results attained reveal the possibility to reduce the overheating risk by up to 89% in highly glazed south faced compartments and 23% in north orientated compartments. In terms of heating energy demand, a reduction of 17% was also attained, triggered by the PCM storage effect.

Multi-scale modelling to assess human comfort in urban canyons

As the impact of climate change progresses, heat waves are expected to increase significantly in the future. Coupled with the urban heat island effect, this will tend to have a major impact on the comfort of the inhabitants in urban areas. It is thus crucial to adopt the necessary sustainable measures and development scenarios to improve city liveability and human health. The main physical parameters that affect the outdoor human comfort are the air temperature, the relative humidity and the wind speed. Various tools, such as CFD or LES models, have been used in the past to evaluate these variables for the calculation of human comfort indices. These tools however are computationally too expensive and require extensive resources and data. Moreover, in our previous studies on the outdoor human comfort realized with the CitySim software, the meteorological variables were not linked to the urban form, geometry and roughness. To overcome these barriers, the CIM (Canopy Interface Model) was developed to calculate high-resolution vertical profiles of meteorological variables. The CitySim software to perform energy and temperature simulations then used these outputs. In this study, virtual pedestrians were located in two different areas of the EPFL campus, in Lausanne (Switzerland): a natural environment - characterized by clay soil and cherry trees - and an artificial environment, the new asphalt square near the SwissTech Convention Centre. The analysis carried out with the CitySim software compares the outdoor human comfort of pedestrian with the wind data from the traditional Meteonorm dataset, and the new CIM wind simulations. A sensitivity analysis of the results shows the difference between both simulations, quantifying the impact of the new wind model in the calculation of the indices.