Case Study: CBT Architects - Building Performance Modeling

FITCHBURG STATELiam O’Sullivan UNIVERSITYChad Reilly Building PerformanceAlfred Wojciechowski ModelingPresenters Energy Reduction Strategies October 27, 2011

agenda part 1: cbt – tools + process a. software b. products part 2: fitchburg state science project a. overview of the building design b. the players in building performance part 3: collaboration – team + process a. mep engineer b. commissioning agent c. energy modeling consultant part 4: cbt – ies + process total cost savings / lessons learned

fsu project overview • 105,425 total square feet – 55,625 addition – 49,800 renovation • LEED silver targeted (state mandated) • new wing: biology (8 labs), chemistry (3 labs), student lounges • existing wing: physics (3 labs), geology (2 labs), classrooms, faculty offices • on main campus road and terminus of main quad

fsu site location

fsu site context biology labs + support shared sciences physics labs + classrooms

fsu elevations

cbt process evidence based design + building information modeling (bim) 3D visualization – design communication coordination • sketchup, photoshop, revit, navisworks, physical models data rich – capture and retrieve information • revit simulations – building components and elements • ecotect, ies

3D visualization sketchup + photoshop

data rich revit – schematic design building area + program analysis

3D visualization sketchup + cad + photoshop

3D visualization revit – bim model • structure • floor slab • plumbing • fire protection • hvac • electrical • walls + ceiling • furniture + cabinetry

3D visualization revit – bim model • completed building • combined revit model

3D visualization revit – bim model

simulations ecotect

simulations ies (integrated environmental solutions)

collaborationteam + process

energy reduction collaboration core design team members cbt – architect • overall coordination • building performance modeling mechanical, electrical + plumbing engineer • develop systems • maintain code compliance energy modeling consultant • traditional energy modeling • identify energy reduction opportunities commissioning agent • advise end user on operations • identify energy reduction opportunities

mep design systems development (sd phase)

commissioning energy + water savings strategies report (dd phase) key components • building description + proposed mep systems • proposed energy + water savings strategies • labs21 benchmarking analysis • ashrae integrating energy strategies in accademic lab facilities • case studies • bridgewater state college • umass amherst new science building • yale university new engineering building • national renewable energy lab

commissioning comparative analysis (dd phase)

energy modeling analysis + recommendations (dd phase)

collaboration outstanding issues matrix (dd phase)

building performance modeling integrated, evidence based design 9000 8000 7000 6000 5000 Load (Btu/h) 4000 3000 2000 1000 0 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 01 Date: Mon 01/Dec to Wed 31/Dec Heating plant sensible load: 301 Lab Organic (all_fins_dec.aps) Heating plant sensible load: 314 Nursing / Indust (all_fins_dec.aps)

energy modeling verification report

cbties + process

specifics of building performance modeling revit generated model ies generated model main topics: • site conditions • building envelope • building facade • daylight harvesting • artificial lighting • natural ventilation

site solar shading analysis of adjacent hill23 M ay 18: 00 23 May – 6:00 PM zone of influence

building envelope insulation – wall • wall insulation (base case) • wall insulation (20% above code) • 2 ½ʺrigid insulation • 4ʺrigid insulation • U-value = 0.062 BTU/hr∙ft²∙ºF • U-value = 0.043 BTU/hr∙ft²∙ºF • additional $0.85/sf over 14,920 sf • hypothesis • more insulation will result in lower energy use and operating costs

building envelope insulation – wall MARGINALLY REDUCED HEATING LOAD NEGLIGIBLY IMPROVED COOLING LOAD 450000 350000 2 ½ʺ 400000 300000 insulation 350000 4ʺ insulation 250000 300000 200000 Load (Btu/h)Load (Btu/h) 250000 150000 200000 100000 150000 50000 100000 0 Sun Mon Tue Wed Thu Fri Sat Sun Sun Mon Tue Wed Thu Fri Sat Sun Date: Sun 21/Dec to Sat 27/Dec Date: Sun 20/Jul to Sat 26/Jul Heating plant sensible load: 96 rooms (increase wall to 4 inch insulation.aps) Heating plant sensible load: 96 rooms (base_case.aps) Cooling plant sensible load: 96 rooms (increase wall to 4 inch insulation.aps) Cooling plant sensible load: 96 rooms (base_case.aps) heating plant sensible loads during winter solstice cooling plant sensible loads during summer solstice $290/ yr. • results • increasing insulation beyond 2 ½ʺresulted in very minimal savings and made no difference in envelope performance • net first cost savings to NOT use 4ʺthick insulation: $12,500

building envelope insulation – roof • roof insulation (base case) • roof insulation (20% above code) • 5ʺminimum rigid insulation • 6ʺminimum rigid insulation • U-value = 0.048 BTU/hr∙ft²∙ºF • U-value = 0.040 BTU/hr∙ft²∙ºF • additional $1.50/sf over 31,750 sf • hypothesis • more insulation will result in lower energy use and operating costs MARGINALLY REDUCED HEATING LOAD NEGLIGIBLY IMPROVED COOLING LOAD 420000 350000 400000 300000 380000 360000 250000 340000 320000 200000 Load (Btu/h) Load (Btu/h) 300000 5ʺ insulation 280000 150000 6ʺ insulation 260000 100000 240000 220000 50000 200000 180000 0 00:00 06:00 12:00 18:00 00:00 00:00 06:00 12:00 18:00 00:00 Date: Wed 24/Dec Date: Sun 20/Jul Heating plant sensible load: 96 rooms (increase roof insulation.aps) Heating plant sensible load: 96 rooms (base_case.aps) Cooling plant sensible load: 96 rooms (increase roof insulation.aps) Cooling plant sensible load: 96 rooms (base_case.aps) heating plant sensible loads (dec. 24th) cooling plant sensible loads (july 20th)

building envelope insulation – roof $4,260/ yr. 5ʺ insulation +$186/ yr. 6" insulation modeling results of upgrading roof insulation to code (5ʺminimum thickness) and to 20% above code (6ʺminimum thickness) – condike roof $205/ yr. 6" insulation modeling results of upgrading roof insulation to 20% above code (6ʺminimum thickness) – new addition roof • results • increasing insulation to code (5ʺ minimum thickness resulted in savings of ) $4,260 annually • increasing insulation to 6ʺresulted in very minimal savings and made no difference in envelope performance • minor heating savings achieved during the winter are offset during remaining seasons when it is beneficial to have less insulation trapping heat within the building • net first cost savings to NOT use insulation thicker than 5ʺ: $47,500

building envelope heating + cooling loads 400000 HEATING LOAD DOMINANCE 350000 300000 250000 Load (Btu/h) 200000 150000 100000 50000 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Date: Wed 01/Jan to Wed 31/Dec Cooling plant sensible load: 96 rooms (increase wall to 4 inch insulation.aps) Heating plant sensible load: 96 rooms (increase wall to 4 inch insulation.aps) annual heating and cooling plant sensible loads

building envelope glass • high perfomance glass • super high perfomance glass • ¼ʺviracon glazing • ¼ʺsolarban glazing • ½ʺ air space cavity • ½ʺ airspace cavity • ¼ʺclear float glazing • ¼ʺ clearfloat glazing • U-value = 0.28 BTU/hr∙ft²∙ºF • U-value = 0.28 BTU/hr∙ft²∙ºF • solar heat gain coefficient = 0.35 • solar heat gain coefficient = 0.27 • additional $25/sf over 8,008 sf • hypothesis • super high performance glass will lower operating costs and be worth the initial cost increase

building envelope glass high performance glass Delta = 4,000 MBTU / year (0.59% of max) super high performance glass • cooling loads: reduced by 45% • heating loads: increased by 3.9% • heating loads are much greater than cooling loads, so the modest increase in heating loads more than cancels the energy savings from cooling ies virtual environment model and components

building envelope glass 450000 400000 350000 300000 Load (Btu/h) 250000 200000 super high performance glass 150000 INCREASE IN HEATING LOAD high performance glass 100000 Sun Mon Tue Wed Thu Fri Sat Sun Date: Sun 21/Dec to Sat 27/Dec Heating plant sensible load: 96 rooms (upgrade to solarban.aps) Heating plant sensible load: 96 rooms (base_case.aps) heating plant sensible loads during winter solstice - $2,457/ yr. modeling results of super high performance glass • results • decrease in solar heat gain coefficient results in requirement for additional reheat energy that more than offsets the electrical savings • in a new england climate, with minimal summer course offerings, super high performance glass resulted in equal or poorer performance in overall energy use • net first cost savings to NOT use super high performance glass: $200,000

building facade overhangs at glass entry pavilion 1 foot overhangs 7 foot overhangs • hypothesis • increasing the depth of the overhangs will reduce cooling loads

building facade overhangs at glass entry pavilion 110000 100000 90000 SIGNIFICANT COOLING LOAD REDUCTION 80000 Load (Btu/h) 70000 60000 1 foot overhangs 50000 40000 7 foot overhangs 30000 20000 10000 0 00:00 06:00 12:00 18:00 00:00 Date: Mon 21/Jul Cooling plant sensible load: lobby level 2 & 310A Atrium / Lounge (base_case_all_shades.aps) Cooling plant sensible load: lobby level 2 & 310A Atrium / Lounge (base_case_no_shades.aps) cooling plant sensible loads during single day peak time (july 21st) 21% reduction in cooling load 7029 BTU/hr. 7 foot overhangs 8918 BTU/hr. 1 foot overhangs cooling plant sensible loads during summer cycle • results • 9,804,000 BTU of cooling saved annually • significant annual cooling cost savings to use 7 foot overhangs

facade and roof plant loads during peak heating periods greenhouse – no shades Cooling load Heating load greenhouse glass entry pavilion entry lobby – horizontal shades Heating load

building facade exterior shading – solar simulation model west facing lab 301 east facing lab 314 sun path diagram – building orientation horizontal shade vertical shade “frame” climate data – sun movement ies software – model

building facade exterior shading – horizontal fins 12" deep horizontal fins 36" deep horizontal fins • hypothesis • increasing the depth of the horizontal fins will reduce cooling loads

building facade exterior shading – horizontal fins opportunity for savings WEST FACING LAB EAST FACING LAB annual cooling plant sensible loads (ies software generated graph) • results • increasing horizontal fins beyond 12ʺ resulted in very minimal electrical energy savings due to reductions in cooling • decreasing the amount of solar gain within the building resulted in an increase in reheat energy, which more than offsets the electrical savings • net first cost savings to NOT use 36ʺ deep horizontal fins: $65,000

building facade exterior shading – vertical fins 8" deep vertical fins 36" deep vertical fins • hypothesis • increasing the depth of the vertical fins will reduce cooling loads

building facade exterior shading – vertical fins 13000 12000 11000 10000 9000 8000 Load (Btu/h) 7000 INCREASE IN HEATING LOAD 6000 5000 4000 36ʺ vertical fins 3000 2000 8ʺ vertical fins 1000 0 00:00 06:00 12:00 18:00 00:00 Date: Tue 23/Dec Heating plant sensible load: 301 Lab Organic (dec_vert_fins.aps) Heating plant sensible load: 314 Nursing / Indust (dec_vert_fins.aps) Heating plant sensible load: 301 Lab Organic (dec_vert_fins_36.aps) Heating plant sensible load: 314 Nursing / Indust (dec_vert_fins_36.aps) heating plant sensible loads (dec. 23rd) • results • increasing vertical fins beyond 8ʺresulted in very minimal electrical energy savings due to reductions in cooling • decreasing the amount of solar gain within the building resulted in an increase in reheat energy, which more than offsets the electrical savings • net first cost savings to NOT use 36ʺ deep vertical fins:$68,000

building facade exterior shading – summary data MAY COOLING DEC HEATING no shades no shades no shades no shades 1.899 1.669 2.272 1.357 horizontal shades horizontal shades horizontal shades horizontal shades 1.694 vertical shades vertical shades vertical shades vertical shades horiz. and vert. shades horiz. and vert. shades horiz. and vert. shades horiz. and vert. shades 1.251 2.342 1.491 heating and cooling plant sensible loads comparing shade layouts

daylight harvesting ies software – radiance analysis daylight levels (fc) 53.669 increased percentage area 44.7 increased above threshold (fc)

daylight harvesting internal light shelves no light shelves light shelves effective natural light penetration into space decrease in natural light penetration into space • results • net first cost savings to NOT use light shelves: $687,000

daylight harvesting windows and depth OFF ON ON effective natural light penetration into space • analysis • how deep does effective natural light penetrate into the classrooms and labs?

daylight harvesting windows and depth 28% of daytime lighting needs in the lab can be met with no light shelves • results • net savings: in 1/3 of the space, artificial lighting can be turned off through the use of sensors to maximize natural daylight harvesting • significantly lower operational costs

artificial lighting light layouts and lamping – base design (linear) 1.4 Watts/Square Foot allowable 31 fc (low) 171 fc (high) 102 fc (avg) typical classroom at condike base design: 3.71 W/SF (2.31 W/SF over) • hypothesis • through foot candle targets modeling, first cost and energy costs can be reduced

artificial lighting light layouts and lamping – revised design (gridded) • comparison • design development layout based on electrical engineer, manufacturing data, and architectural decisions versus prioritizing energy reduction, architectural layouts, and "effective and even lighting" levels 8 fc (low) 54 fc (high) 27 fc (avg) • results revised design: .94 W/SF (0.46 W/SF under) • effective and even lighting levels achieved with a 30% watts per square foot lighting power density reduction • net savings: • first cost: $100,500 • operating costs: $10,500/year • potential utility company incentives: $16,000/year

natural ventilation glass enclosed stairways dynamic modeling of envelope, air movement, and shading • hypothesis • natural ventilation can provide comfort and reduce operating costs versus a mechanical cooling system

natural ventilation glass enclosed stairways – improving temperatures naturally ventilated unventilated stair temp stair temp improvementby improvement by unventilated natural ventilation natural ventilation stair temp exterior temp naturally ventilated unventilated naturally ventilated stair temp stair temp stair temp exterior temp exterior temp temperature changes in stairways throughout the school year (ies software generated graphs)

natural ventilation glass enclosed stairways – increasing thermal comfort Natural ventilation reduces the occurrence of temperatures above 72ºF during operating hours from more than 20% of the time to less than 10% of the time in the south stair. stair temperatures by hour without natural ventilation stair temperatures by hour with natural ventilation • results • elimination of 4 tons of cooling by NOT using air conditioning units • first cost savings to naturally ventilate stairways: $34,500

project savings site conditions neighborhood hillside. . . . . . . . . . . . . . . . n/a building envelope glass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . $200,000 insulation – wall . . . . . . . . . . . . . . . . . . . . $12,500 insulation – roof . . . . . . . . . . . . . . . . . . . . $47,500 building facade exterior shading – vertical fins . . . . . . . . $68,000 exterior shading – horizontal fins . . . . . . $65,000 overhang at glass entry pavilion . . . . . . . n/a daylight harvesting windows and depth . . . . . . . . . . . . . . . . . . n/a internal light shelves . . . . . . . . . . . . . . . . $687,000 artificial lighting light layouts and lamping . . . . . . . . . . . . . $100,500 natural ventilation glass enclosed stairways . . . . . . . . . . . . . $34,500 total first cost savings . . . . . . . . . . . . . . . . . $1,500,000 total operating cost savings . . . . . . . . . . . . $34,300 per year

lessons learned 1. multi disciplines should participate together to inform low operating goals first costs 2. ʺrulesof thumbʺ and manufacturer„s data are too general ; simulation results should be specific to your project in your location 3. do continuous experimentation through the design phases to maximize effective decision making www.cbtarchitects.com

Case Study: CBT Architects - Building Performance Modeling

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Case Study: CBT Architects - Building Performance Modeling Presentation Transcript