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Saved by Brian Matthews
on November 7, 2008 at 6:49:24 am
 

Energy Modeling of Buildings

 

Description:

     Energy modeling of buildings is a practice of predicting the energy costs of a building.             

 

Purpose:

     The goal of energy modeling is to accuratly predict the energy use of a particular building to either test the energy performance of the building with regards to established codes and standards, or to compair and contrast two buildings in order to find the resulting savings from the application of prospective energy efficient measures.   It would be most desirable to have two  identical buildings, one energy efficient, the other not, and compair their utility bills to find differences.   It is seldom that such a situation exists so energy modeling is used to simulate and estimate a building's energy use.   

 

Industries served:

     All buildings that have significant utility or energy use would benefit from energy modeling due to its ability to predict the useful savings that result from the installation of mechanical equipment with greaterenergy efficiency, or the implimentation of new practices that reduce peak or yearly energy use.   Not all energy efficient equipment or practices fit all situations.   Analysis is necessary to find the most worthwhile savings created in exchange for the typically higher up-front cost and effort.   At the end of the day what must be known is, "Will this energy efficient activity save money in the long run?"   Often the ballances is tipped or encouraged by federal, state, or other governing body providing incentives. 

 

Methods:

     Classification of the different methods are diverse in their practice but generally subscribe to the goal of predicting energy use.   The choice between the different methods is primarily based on level of accuracy desired and what methods, codes, or standards a governing body requires the modeler to adhere to.   

 

  • Computational Fluid Dynamic (CFD) simulations
  • Hourly/Sub-Hourly simulations (Equest)  -A detailed summary of each hour of the year and the hour-by-hour energy operation of the building.
  • Compariative Summary Tools -Use a database to rate the building's energy efficiency in regard to other buildings.
  • Custom Measure tools.  -Non-Interactive method of looking at one measure at a time.

 

Existing Guides

  • Equest Workbook
  • MPP Guidebook

 

Modeling Resources:

  • Units, Conversions, and Definitions comon to Energy Modeling:
    • Cooling (ton, vs. hp, Btu, vs. mBtu, vs. mmbtu, vs. kw)
    • Heating (cf gas vs. therm, vs. Heating Factor)
    • Gas (cf vs btu)
    • Electricity (Var vs. kWh, vs. 3phase current vs. 2 phase current, vs 490volt ac vs. 280 volt ac vs. 110 volt ac vs. kW vs btu)
  • Typical Energy Use of Buildings
    • Typical heating Factors for buildings
    • Typical Cooling Facotrs for buildings
    • Speciality Buildings (DATA CENTERS, REFRIGERATED WAREHOUSES)
  • Energy database 
    • Lighting energy use
    • Kitchen Appliances energy use
    • Laundry (residential and commercial) energy use
    • Computer and office workstation energy use
    • Commercial Kitchen (restaurant) energy use
    • Swimming Pool Energy use
    • Spa and luxury equipment energy use
    • Recharging large Electric vehicle energy use (Fork Lifts, Golf carts, electric cars, etc.)
    • Manufacturing workstation energy use. 

Fundamental building characteristics

  • Outside Air
    • Air Changes Per Hour
    • HVAC exhaust-supply offsets
    • Wind 
    • Cracks in building envelopes
    • Stack effect through all Elevator,mechanical shafts, and stairwells.
    • Air buoyancy effect through all elevator, mechanical shafts, and stairwells.
  • Exhaust
    • Affect exhaust fans have on building infiltraition
    • Typical rooms under exhaust
    • Specialty Exhaust rooms
      • Parking Garages
      • Bathrooms
      • Chemical work stations and Laboratories
      • Repair Garages
      •  
  • HVAC
    • CVCT systems
    • VAV systems
    • PTAC systems
    • Typical residential systems (urban)
    • Typical industrial systems
    • ASHRAE SYSTEM TYPES VS EQUEST PROGRAM INPUTS
    •  
  • ENVELOPE
    • Thermal bridging
    • Exposed floor slab, balconies
    • Roof dynamics
    • Cavity wall physics
    • Moisture barrier
    • Wall construction type dependencies on local climate.
    •  
  • Occupancy
    • Occupancy Schedules:
      • Residential
      • Health Care facilities
      • Commercial
      • Office
      •  
    • Thermostat Schedules
      • Residential
      • Health Care facilities
      • Commercial
      • Office
      •  
    • Lighting Schedules
      • Residential
      • Health Care facilities
      • Commercial
      • Residentail
      •  

 

Baseline Building Information

  • Modeling Code defined Baselines 
    • ASHRAE 90.1 2004 APPENDIX G
    • MPP
    • LEED analysis methodology (per Credit)

 

Improved Building Information and Energy Conservation Measure Modeling Approaches

  • SOLAR PV
  • CONDENSING BOILERS
  • ENVELOPE IMPROVEMENTS
  • REFRIGERATED STORAGE FACILITY
  • ENVELOPE
  • LIGHTING
  • PROCESS IMPROVEMENT
  • BUILDING MANAGEMENT SYSTEMS
  • ENERGY & HEAT RECOVERY
  • COMBINED HEAT AND POWER (CHP)
  • NATURAL GAS RECIPROCATING ENGINE GENERATOR, CHILLER
  • BIODIESEL RECIPROCATING ENGINE GENERATOR/ CHILLER
  • ABSORPTION CHILLER
  • HVAC IMPROVEMENT
  • ELEVATOR AND PEOPLE MOVING APPARATUS
  • COMPUTERS, OFFICE EQUIPMENT
  • DAY LIGHTING
  • WIND
  • GROUND-SOURCE GEOTHERMAL
  • RADIANT FLOOR
  • OCCUPANCY SENSING LIGHTING, HVAC
  • EXHAUST AIR DAMPERS
  • EXHAUST CONTROLS

 

 

Software:

 

 

Data Classification:

 

     First, a few words on numbers, and the different types of numbers used in energy modeling:

    

  1. SES "Scalar Evenly Scheduled" -  A number that is applied to a building parameter independent of schedules because in the calculation used to attain this number there had been predetermined hours per day of use assumed.  An example of this would be a an amount of water outdoor plants need per year at a particular building.   For simplicity, it is easier to assume a 5,000 gallons per year and thereby 50,000/ 365 days =137 gallons per average day, than to calculate seasonal rainfall, hourly evaporation etc.   SES numbers are highly volatile and subject to error if not used properly.  "SES" numbers do have a certain advantage in certain situations so long as their interaction and affect on accuracy of the model are accounted for.  
  2. SDS "Scalar Definitively Scheduled" -A number that is only valid when used in conjunction with a schedule where every hour of every day has a value ranging from 1-100% (or fraction from 0.01 to 1.0).    An example of this is a 60 watt light bulb used 2.4 hours a day.   The load will never be 60 watts 24/7.  
  3. ISV  "Isolated Static Values"   These are numbers that never change regardless of schedule, part load ratios, or other variable reactionary events.  The gallons per minute of a shower head is an example.  
  4. IDV  "Interactive Dependent Values"  
    • On a building input, these type of numbers must be accompanied by appropriate pairs or in groups in order to run a working simulation.    If, for example, only 4 out of 5 numbers are correct for an HVAC system, but one number is either not known or incorrect, the simulation results may be volatile in accuracy.  Often, when a modeler overrides features of a program intended to be user-friendly (and thereby rigid and inadaptable) a volatility in the results may occur because the automatic features of the program were unintentionally prevented to run their course.    Sometimes you must either know 5-6 critical numbers or be willing to accept the resulting limitations of only being able to input 1-2 numbers (and thereby rely on the rigid automatic features of the software) This situation can be referred to as "Trash in Trash out". 
    • On a building's Output side of things,  there are a limited quantity of energy values yielding whether a building is of high or low energy performance.    Each one of the energy values are either directly affected by one energy measure or joint affected by many energy measures stacked on each other.   Errors can occur, but not be seen, if one measure's over estimation of energy savings is masked by another energy measures under estimation of energy savings.   All energy modeling requires a fine combing of the data to check that all is in order.        
  5. CKV "Critical Key Values"  Just as there are potentially many dozens of inputs that go to make up a model, there is an accompanying importance some numbers over others.   From most numbers an error range of 4-8% may be acceptable, but if key values have such a loose tolerances then this may lead to 10 or more percent difference on the result.   Some numbers magnify their loose tolerances while other numbers have a reduced impact on the overall result accuracy.    Doing approximations of certain numbers should be done with proper care as their impact on the model's results may not be apparent in first runs of a building model.     

 

 

 

 

 

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