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Tools forEnergy Evaluation and Planning:
EXPERIENCES AND PROPOSAL
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Floriberta BinartiDresden, 10th ‐14th June 2013
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1. AC planning of a library building
2. Energy performance evaluation of campus buildings
3. Energy performance map of fenestration design in urban context based on sky view factor
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energy performance evaluationof campus buildings (2008)
AC planning of a Library Building (2009)
Climate profiles:Warm temperature, small diurnal and annual ranges of temperature, high humidity
Climate profiles:High solar radiation, high
sky luminance, fairly cloudy, painful sky glare
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ECOTECT for - energy performance evaluation- calculation of room cooling load
easily modeling complex buildings and their
surroundings
Designer friendly program and provides some facilities in a single package
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Survey for input data
- Room type/occupant activity- Occupant number- Equipment- Clothing- Wind sensitivity- Air tightness
Standard for library building(UNESCO & National Library Bldg)
- Relative Humidity- Air Speed- Illuminance Level- Temperature (thermostat range)
- Air Change Rate
ROOM COOLING LOAD SIMULATIONSto calculate the AC capacity
AIRFLOW SIMULATIONSto define proper AC position
AC SYSTEM PLANNING:
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Zone management -
automatically created from
3D model
Set up the general properties of each
zone
Estimated equipment efficiencyThermal load applies standard HVAC system for a single COP factor
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Standard for thermal comfort
Standard for visual comfort
Activity
Standard for thermal comfort
Air tightness of the construction
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8COOLING LOAD
Monthly cooling load
Hourly cooling load
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COOLING LOADPSE‐UAJY
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COOLING LOAD
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COOLING LOADPSE‐UAJY
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COOLING LOAD
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AIR FLOW DISTRIBUTION
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CFD‐ACE+algorithm:steady state, turbulence model: standard k‐з
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AIR FLOW DISTRIBUTION
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AIR FLOW DISTRIBUTION
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AIR FLOW DISTRIBUTION
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AIR FLOW DISTRIBUTION
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ENERGY PERFORMANCE EVALUATION:
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2 weeks SURVEY
BUILDINGMODEL
Physical Measurement
Building Documents
Observation
Interview & Questionnaire
ANALYSIS
Field Measurement
Walk through survey
Validation
THERMAL &
LIGHTING SIMULATIONS
Standards
real energy consumption
Equipment-building condition &
maintenance, occupant behavior
RECOMMENDATIONS
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ENERGY PERFORMANCE EVALUATION:
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Relative high internal heat gain
Campus building 1
Relative high conductive heat gain
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GAINS BREAKDOWN
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GAINS BREAKDOWN ‐ All Visible Thermal Zones
FROM: 1st January to 31st December
CATEGORY LOSSES GAINS
FABRIC 0.0% 30.8%
SOL‐AIR 0.0% 9.6%
SOLAR 0.0% 8.6%
VENTILATION 0.0% 6.6%
INTERNAL 0.0% 35.6%
INTER‐ZONAL 100.0% 8.8%
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Relative high internal heat gain
Campus building 3
Relative high conductive heat gain
Relative high internal heat gainRelative high direct
solar heat gain
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GAINS BREAKDOWN
Campus building 2
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Daylight Factor: clipped with the minimum value of 2% and the maximum value of 5 %
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DAYLIGHTING
Lower than standard
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daylight level: clipped with the minimum value of 200 lux and the maximum value of 500 lux
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DAYLIGHTING
Insufficient daylight level
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Illuminance level of the lamp lights: clipped with the minimum value of 200 lux and the maximum value of 400 lux
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LIGHTING
Sufficient lighting level only below the lamps
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Illuminance level of daylight combined with the lamp lights: clipped with the minimum value of 200 lux and the maximum value of 500 lux
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DAYLIGHTING & LIGHTING
Lighting level helps increasing daylight level, but still creates uneven distribution
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FINDINGS:
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BEHAVIOR:
- keep the AC on- set up the thermostat at
very low temperature- let the door of air
conditioned room open
EQUIPMENTS:
- use CRT monitor more than LCD or LED
- choose improper capacity of the AC
- using fluorescent lamps without energy saving
ballastFURNISHING (LAYOUT):
- room layout/cupboard blocks the air flow
- high ceiling- dark color of furniture
- low maintenance of wall and ceiling surfaces and
lamps
SIMULATIONS:
‐ the highest percentage is conductive heat gains (50.4%), internal heat gain (17.0%),
interzonal heat gain (10.8%), then solar air heat gains (10.5%),
ventilation (8.2%), and solar heat gain (3.0%).
SURVEY:
‐ total cooling load: 96.5 W/m2.h ‐ the highest month: May and
coolest month: February
‐ uneven distribution of daylight level due to large classrooms
‐ illumination level is not sufficient for study because the artificial lightings were installed on high
ceiling
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- Combine AC with fan- Add shading devices on some facades/orientations- Increase internal surface reflectance by repainting or light color
painting- Reduce the height of lamps- Permanent Substitute Artificial Lighting for Interior (PSALI) with
automatic sensor- Routine maintenance- Re-layout rooms (furniture and partitions)- Energy saving lamps replacement (electronic ballast fluorescent
lamps or LED)- Energy saving monitor replacement (LCD or LED monitor)- Regrouping of lamp buttons- Repaint lamp reflectors with white color
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RECOMMENDATIONS:
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- Replacement of conventional ballasts with electronic ballasts in 5 campus buildings can save IDR 8.306.933,- per month.
- Replacement of 50% of existing AC with energy saving AC can save IDR 24.980.805,- per month.
- Replacement of CRT monitors with LCD monitors can save IDR 10.038.200,-
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References:Pusat Studi Energi – Universitas Atma Jaya Yogyakarta. (2008) Evaluasi Sistem Energi dan Rekomendasi Perbaikan Bangunan Kampus Universitas Atma Jaya Yogyakarta. Unpublished report. UAJY, Yogyakarta.Pusat Studi Energi – Universitas Atma Jaya Yogyakarta (2009) Perencanaan Pengkondisian UdaraBuatan pada Gedung Perpustakaan Universitas Atma Jaya Yogyakarta. Unpublished report. UAJY, Yogyakarta.
IMPLEMENTATION SCENARIO
PROPOSAL
Energy Performance Map of Fenestration Design in Urban Context Based on Sky View Factor
Backgrounds:Fenestration has an important role in creating thermally and visually comfortable indoor space, which affect the occupant performance, productivity and health. In many cases major heat loss or heat gains is through fenestration.Urban environment affects the fenestration performance by modifying the daylight and the solar radiation availability in buildings.Geometry of urban structure is usually represented by Sky View Factor (SVF).
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Theoritical review:Fenestration affects the energy use in a building through four basic mechanisms, i.e. thermal heat transfer, solar heat gain, air leakage and daylighting. Energy flows through fenestration via conductive and convective heat transfer caused by temperature difference between outdoor and indoor air, net long-wave radiative exchange between the fenestration and its surroundings, and between the glazing layers, and short-wave solar radiation incident on the fenestration products (ASHRAE, 2009).Shading devices modify window’s SHGC.Fenestration as daylight admission can reduce substantial energy use by displacement of the need for electric lighting during daytime. The energy use for supplementary lighting depends on the glazing visible transmittance (Tv) and the window glazing area. U, SHGC, air leakage and Tv are the instantaneous energy performance indices typically used to compare fenestration systems under fixed conditions (ASHRAE, 2009). Advanced technology in glazing creates new products with low SHGC or/and Uvalue, and high VLT.
Tinianov, 2010 Binarti, 2005 Binarti et al., 2012
Literature review:Rules of fenestration design to achieve indoor comfort has been widely discussed and applied during several decades. Rule of thumb has been recognized in daylighting and thermal design as practical guidance for fenestration design, hence for the energy design of the fenestration. Window-head-height to room depth ratio was introduced as DRT since the Green Vitruvius era. Later several building guidelines, codes and standards prescribe different versions with recommended ratios ranged from 1.5 to 2. Reinhart reviewed that its validity was based on Radiance simulations of rectangular sidelit spaces with standard interior surface reflectances for a variety of climates, facade orientations, façade geometries, and usage patterns. (Reinhart, 2004) Daylight factor (DF) has been widely used as prime daylighting rule of thumb (DRT) to describe the ratio of indoor illuminance level to the external illuminance level. Ibrahim (2009) proposed equations of Daylight Factor which can be applied under certain conditions. He did not address the issue of direct sunlight and heat gain.
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Theoritical review:Daylight and thermal performance of fenestration design depend so much on the external conditions, i.e. daylight and solar radiation availability. Sky View Angle (Lawrence Berkeley National Laboratory, 1997) or Sky Solid Angle (Capeluto, 2003) or Vertical Daylight Factor (Li, D. et al, 2008) has been used as a criterion to justify the daylight penetration in buildings. Sabry et al. (2010) found, there is a significant difference in daylighting performance when the distance of external obstruction increases and the external reflectance changes, although the sky view angle remains constant.Pereira et al. (2007) proposed Preferential Sky Window as a parameter of urban daylight availability.
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Pereira et al., 2007
Leder et al., 2006
Leder et al., 2006
Theoritical review:Kesten et al. (2012) presented a method to quantify the energy performance in urban quarter in Stuttgart. The results showed that the neighbor’s height to width ratio, spacing distance and frontal depth to length ratio can modify the building energy demand.Sky View Factor (SVF) is an important parameter of radiation geometry in built up areas (Chen et al., 2010). It describes radiation received/emitted by a planar surface at a site compared with that received/emitted on a surface without obstruction of the horizon.Compagnon (2004) described SVF as the ratio of the illuminance (Ei) and a uniform sky model of arbitrary luminance (L) : Ei/πL . SVF distribution is used as an indication of outdoor daylight factor distribution.
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Compagnon , 2004
Objectives:1. To classify urban area based on Sky View Factor (SVF) as a measure of solar
irradiation and daylight availability in urban area.2. To provide information about energy performance of fenestration designs in
urban context which is classified by the SVF.3. To investigate correlation between SVF (and other factors of urban
environment) and the energy performance of fenestration design.
4. To develop a proposed urban morphology and texture which can improve the energy performance of fenestration design.
5. To investigate most suitable fenestration design for specific urban texture and building type
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PROPOSAL
Energy Performance Map of Fenestration Design in Urban Context
Based on Sky View Factor
Methods:
1. Generate fenestration designs:
Observation on some building types to generate variations in Window to Wall Area Ratio (WWR), Window to Floor Area Ratio (WFR), Window Height to Floor Width Ratio (HWR).
Variations in window glazing which are generated from available glazing specs.
Variations in shading devices.
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m.energitoday.com
commons.wikimedia.org
uajy.ac.id
Methods:
2. Classify the existing urban area base on the SVF:
Visual observation on the urban morphology/texture (: H/W ratio, density-openness, direct and diffuse irradiation, illuminance level, surface albedo).
Some methods to obtain the SVF:
Fish-eye lens photograph with BMSky-view. BMSky-view is a software application with graphical interface to compute the SVF value directly from fish-eye lens digital camera (Rzepa et al., 2009).
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Methods:
2. Classify the existing urban area base on the SVF:
RayMan is developed to calculate short wave and long wave radiation fluxes, even mean radiant temperature. It is possible to implement fish-eye photographs for calculation of SVF. Meteorological data can be input manually or by using pre-existing files. RayMan is user friendly environment and rappid running time. (Matzarakis, 2012).
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Methods:
2. Classify the existing urban area base on the SVF:
SkyHelios is helpful to estimate radiation fluxes and mean radiant temperature in urban and complex situation accurately. Input data base can be from digital elevation models (DEM), data concerning urban obstacles (OBS) or other digital files. Data produced from SkyHelios can be imported directly in RayMan to run calculation of the thermal indices and estimate the SVF (Matzarakis, 2012).
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Methods:
3. Indoor thermal and daylight simulation of fenestration designs:
Some energy modeling softwares are:
Ecotect is an environmental analysis software, which consists of facilities to compute lighting simulation, thermal performance, acoustic simulation, solar exposure, shading design, etc. in single package. One model can be used for several kinds of simulation. Calculation of room thermal load has considered thermal load from lighting. The energy used to achieve visual comfort must be simulated separately.
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Methods:
3. Indoor thermal and daylight simulation of fenestration designs:
DesignBuilder – E+:- calculate heating & cooling loads using ‘heat balance’ method.
- calculate heat transmission through the building fabric using real hourly weather data.
- simulate daylighting of a building with external/internal shading and various glazing systems.
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4. Validation:Compare the field measurements (using luxmeter and piranometer) with the simulation results.
5. Energy Performance Mapping:The map of the energy performances of fenestration designs as the total of heat gains from the envelope (fabric gains) plus energy that needs for supplemental lighting of each urban area with its own SVF are presented using ArchGIS.
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References:E. Mediastika & F. Binarti (2003) Vegetative Shading to Control Solar Heat Gain and Glare. Proceedings of 4th International Seminar on Sustainable Environment Architecture, Dept. of Architecture - TrisaktiUniversity, Jakarta, October 15-16, 2003.B. Tinianov (2010) Advanced Glazing and Window Technology. BETEC Symposium, Dec. 10, Washington.C.F. Reinhart (2005) A simulation-based review of the ubiquitous window-head height to daylit zone depth rule of thumb. 9th International IBPSA Conference Montreal, Canada; August 15-18, 2005. N.L.N. Ibrahim (2009) Daylighting rule of thumb and typology. Faculty of Architecture, Design & Planning, University of Sydney, New South Wales, Australia, PHD Thesis. F. Binarti (2005) Lightshelf for Improving Indoor Horizontal Illuminance Distribution. Journal of Teknik Vol. XII/1 April 2005.Lawrence Berkeley National Laboratory (1997) Tips for daylighting with windows. [Berkeley, Calif.]: The Program.F. Binarti, A.D. Istiadji, P. Satwiko & P.T. Iswanto (2012) Raising high energy performance glass block from waste glasses with cavity and interlayer. Int. Conf. on Sustainability in Energy and Buildings, September 3-5, Stockholm.I. Capeluto (2003) The influence of the urban environment on the availability of daylighting in office buildings in Israel, Building and Environment. 38, 745 – 752. S.M. Leder, F.O.R. Pereira, A. Claro, M.G. Ramos (2006) Impact of Urban Design on Daylight Availability. PLEA2006 - The 23rd Conference on Passive and Low Energy Architecture, Geneva, Switzerland, 6-8 September 2006.Li, D. et al, 2008 Simple method for determining daylight illuminance in a heavily obstructed environment, Building and Environment. 44, 1074 – 1080.H. Sabry, A. Syarif, S. Shawky, T. Rakha (2010) Assessing the Effect of External Obstruction Parameters on Indoor Daylighting Performance in Desert Clear Sky Conditions. International Sustainable Development Research Conference , 30 May – 1 June 2010, Hong Kong
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References:F.O.R. Pereira, S.M. Leder & A. Claro (2007) Preferential Sky Window: A new parameter to correlate sky obstruction and indoor daylighting performance. PLEA2007 - The 24th Conference on Passive and Low Energy Architecture. 22 – 24 November 2007, Singapore.D. Kesten, A. Kereci, A. Strzalka, U. Eicker (2012) A Method to Quantify the Energy Performance in Urban Quarters. Journal on Indoor air quality, ventilation Vol. 18:1-2, p100-111.R. Compagnon (2004) Solar and daylight availability in the urban fabric. Energy and Buildings 36 (2004) 321-328. V. Cheng, K. Steemers, M. Montavon, R. Compagnon (2006) Urban Form, Density and Solar Potential. PLEA2006 - The 23rd Conference on Passive and Low Energy Architecture, Geneva, Switzerland, 6-8 September 2006.B. Deroisy & A. Deneyer (2013) Daylight and Solar Access at Urban Scale: a Methodology and its Application to a High Density Development in Brussels. CIE Centenary Conference 12th -19th April 2013, Paris.M. Rzepa (2009) The Map of Sky View Factor in the Center of Lodz. The seventh International Conference on Urban Climate, 29 June - 3 July 2009, Yokohama, Japan.M. Hammerle, T. Gal, J. Unger and A. Matzarakis (2011) Comparisons of Models Calculating the Sky View Factor Used for Urban Climate Investigations. Theor Appl Climatol DOI 10.1007/s00704-011-0402-3. Springer-Verlag.A. Matzarakis (2012) RayMan and SkyHelios Model – Two Tools for Urban Climatology. Fachtagung des Ausschusses Umweltmeteorologie der Deutschen Meteorologischen Gesellschaft. 20.3 bis 22.3.2012, Leipzig. 5_V_5, 1-6.A. Matzarakis and O. Matuschek (2011) Sky view factor as a parameter in applied climatology – rapid estimation by the SkyHelios model. Meteorologische Zeitschrift, Vol. 20, No. 1, 039-045 (February 2011). Gebruder Borntraeger 2011.
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References:F. Binarti & A.D. Istiadji (2009) Studi Komparasi Program Simulasi Sebagai Piranti Redesain PencahayaanGereja. Unpublished Research Report. UAJY, Yogyakarta.
http://www.designbuilder.co.uk/content/view/114/commons.wikimedia.orgm.energitoday.comuajy.ac.id
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