Multi-criterion optimization of building envelope in the function of indoor illumination quality towards overall energy performance improvement
Graphical abstract
Introduction
According to the International Energy Agency (IEA), buildings exceed 40% of world energy demand and emit close to 1/3 of CO2 worldwide [1]. The need to optimize building energy performance was elaborated in numerous researches using various analysis methods, energy simulations and techniques in order to design sustainable, energy efficient and cost-effective buildings [2], [3], [4], [5], [6], [7]. Authors Eui-Jong et al. developed a simplified model of building envelope design using physically simplified city simulation tools [8]. Rahman elaborated the energy and environmental life cycle assessment of office building envelopes [9]. Authors Attia et al. have summarized potential challenges and opportunities for integrating simulation-based building performance optimization tools in net zero energy buildings design [10].
Illumination performance analysis has been a widespread topic investigated in numerous papers via simplified models, daylight coefficient concept, daylighting schemes, window properties, building design and climate conditions [11], [12], [13], [14], [15]. Building simulation for energy strategy formulation in façade retrofitting different climatic conditions of EU was investigated by authors Capeulo and Ochoa [16]. A detailed multi-level optimization principle was demonstrated by Evins in a process on a straight-forward test case, applied to a case study simplified office building [17].
Thermal and lighting simulations applying energy modeling, glazing's transmittance dependence and envelope thickness and economic aspects were investigated in previous researches [18], [19], [20], [21].
A recently published investigation from authors Ma et al. [22] investigated window to wall ratio as a function of two parameters; U-value and ambient temperature amplitude. Authors stated that factors which are heat gain related such as solar heat gain coefficient (SHGC), shading, sky cloudiness and building orientation do have a great impact on window to wall ratio (WWR) determination; however it was impossible to consider. Thus the authors propose the assumption of these factors. However, the multi-criterion optimization methodology applied in our research elaborates building envelope, window to wall ratio and window geometry selection further, by implementing various factors in the optimization process which influence indoor illumination quality, electricity reduction for lighting and exterior glazing properties in the aim of overall energy performance improvement of existing or newly designed office buildings.
This paper elaborates the formulation and application of an integral methodology for overall energy performance improvement of office buildings and demonstrates its application on an existing reference building. The idea is to formulate a general/integral methodology which could be applied widely in energy performance refurbishment of existing buildings and help architects and engineers in the early-design stages of new projects.
The developed coupled-integral methodology links together both building envelope construction optimization and user comfort. It is flexible and adaptable for application in various climatic conditions and for different building energy efficiency directives and regulations. The development process of the multi-objective methodology consisted of four major phases, which can be seen in the flowchart, Fig. 1. The first three phases refer to data analysis and construction of the reference building's computational model. In the first phase technical data, construction and building material data, HVAC data, and monthly energy expenses where gathered. Building's district heating energy utilization was monitored respectively. The second phase referred to the detailed processing, analysis and evaluation of the gathered data packages. Building performance was evaluated and critical building operation errors were determined. Finally in the third phase a computational CAD model was created using Building Information Modeling (BIM) technology where building geometry, function, construction and material data were integrated. Following the computational model's construction the multi-criterion optimization in the fourth phase referred to the determination of adequate window to wall ratio (WWR) and window geometry (WG) in the function of visual comfort and predefined parameters. Afterwards the optimized Best Case Energy Performance Scenario was determined according to glazing parameters and climate data using dynamic energy performance simulation.
The integral methodology will be demonstrated on a reference office building model located in a temperate climate zone with high annual temperature variations.
In order to formulate an efficient solution for building envelope improvement according to the European Standards, EN 15251 [23], the building was investigated as a dynamic multi-zone thermal system using multi-criterion research methodology. Building envelope performance is investigated both from glazing performance and thermal performance (heating and cooling demand) aspects by using multi-criterion optimization. Efficient WWR and WG was determined in the function of three criteria:
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Advanced spatial daylight dispersion analysis,
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Average daylight factor determination,
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Electric lighting reduction using automatic sensor system.
Authors Gvozdenac et al. elaborated the energy policy situation in Serbia and in the European Union [24], [25], [26], where authors determined that Serbia lags behind in the process of improving energy efficiency due to inadequate and slow institutional organization and application of state instruments in order to implement strategies.
The research was conducted on a typical not refurbished existing reference multi-level office building (total area 3430 m2) located in the district of the University of Novi Sad in Serbia. The aim was to determine the heating and cooling energy demand in the function of building envelope properties (WWR, WG, glazing properties and exterior wall thermal properties) in order to offer effective methods for energy performance improvement.
The workflow consisted of the following three phases:
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Phase I; Multi-criterion optimization of building envelope.
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Phase II; Multi-zone thermal model construction and simulation data implementation.
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Phase III; Dynamic simulation of various scenarios in the function of glazing parameters.
Section snippets
Location and climate data
In phase 1, Location and climate data were imported from the global climatological database Meteonorm 7 [27]. The climate data package was converted into EnergyPlus Weather file (EPW) format in hourly intervals. Monthly average climate data from Meteonorm 7 database are shown in Table 1. Average monthly radiation energy and temperature oscillations are shown in Fig. 2.
In Table 2, the location and building situation are merged with an image of the reference office building. Annual sun path
WWR, WG and window properties
Daylight intensity was measured in hourly intervals during the winter and summer period with KIMO luxmeter instrument. The monitoring was conducted on the 9th floor's west oriented office, with 50% glazing area. As shown in Fig. 8 the monitored indoor daylight intensities majority during July and August was above visual comfort requirement for office environment.
Indoor illumination dispersion was simulated and analyzed for three WG's shown in Table 4 below. The WG's were selected according to
Construction, occupancy and operation schedules
The building envelope applied in the simulation was selected according to the thermal insulation requirements of the Serbian Directive - Official Gazette RS no. 61/2011 and EU Standard [25], [26], [29]. The building envelope construction was improved in order to reduce the heat transfer coefficient. The U-value of the existing office building's exterior walls is 2.32 W/(m2K) since the walls are constructed from 25 cm fired clay brick, without insulation layer. The modified exterior wall
Energy performance results and evaluation
Electric lighting and equipment electricity demand per square meter of floor area required 44 kW h/m2/a annually. Monthly electricity demands are shown in Fig. 13. These internal loads were adopted as constant loads in all scenarios with the internal energy gains produced by their operation. EnergyPlus simulations in cover the following:
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Determination of heating and cooling energy demands in the case of 10 Scenarios and
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Evaluation of glazing influence on the annual energy performance (heating and
Comparison of energy performance simulation results with annual expenses
Comparison of annual energy demands between reference office tower building and the Best Case Scenario are presented in Fig. 17, Fig. 18 and Table 8 as numerical values. Fig. 17 presents the comparison of monthly heating expenses and heating demands from the simulated Best Case Scenario. The findings presented that if the U-value of exterior walls is reduced to 0.7 W/m2K and for exterior glazing stands below 1.0 W/m2K with SHCG value below 0.3, than the annual heating energy demand for the
Conclusion
The investigation presented the applicability of the formulated integral methodology which could be both flexible and adaptable for application in various climatic conditions and for different building energy efficiency directives and regulations. The developed multi-objective methodology consisting of four major phases was demonstrated on a reference office building. The integral methodology is formulated to be general, adaptable and applicable which could be widely applied in energy
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2022, Building and EnvironmentCitation Excerpt :Over the past decade, optimization tools have shown strong design potential and have been successfully integrated into recognized energy building simulation software packages such as Open Studio and Design-Builder, TRNSYS, and others [44]. In particular, the optimization method has been widely used in the optimization design of building skin [45–50]. Although the numerical optimization method is widely used in the optimization research of building skin, there are few studies on the optimization design of building skin that integrate both the maintenance and production functions.