Building Simulation - Penn Engineeringcis800/lectures/simulation_gao.pdf · The foundation for building simulation as a distinct class of software applications came with the advent

Building SimulationXuefeng Gao (Frank)

Monday, April 4, 2011

Terminology


Building Simulation?


energy and mass flow?

structural durability?

aging?

egress?

construction site simulation?


our focus is on energy performance modeling, explained by “physical transport processes”


this area has its origin in early studies of energy and mass flow processes in the built environment


groundwork was done in 1960s and 1970s

energy performance

lighting

HVAC

air flow

He notes, “Unlike conventional geometric primitives such as sphere, which has its own autonomous organization, a metal-ball is defined in relation to other objects. Its center, surface, area, mass, and organization are determined by the other fields of influence.” Those “fields of influence” can be used to simulate anything from the motion of the sun to the movement of people to changing brand identities, anything whose influence can be assigned a value.10


“The earliest attempts to adapt computer programs to building performance simulation (or “calculation” as an early term) date from late 1960s.” -- Godfried Augenbroe


later on ...

combined moisture and heat transfer

acoustics

control systems

urban and micro climate


later on ...


acoustics

control systems

urban and micro climate Swiss Re Building, London – Foster and Partners


later on ...


acoustics

control systems

urban and micro climate Foster and Partners


Until the mid-1990s

major software vendors began to show interest in the building simulation area

DOE-2, ESP-r, TRNSYS


Since late 1990s

domains other than energy are increasingly covered by specialized tools

the launch of EnergyPlus (the merger of BLAST and DOE-2) made it quickly became the most popular whole building energy simulation program among researchers.


EnergyPlus

models heating, cooling, lighting, ventilation,other energy flows, and water use.

time-steps less than an hour, moduar systems and plant integrated with heat balance-based zone simulation, multizone air flow, thermal comfort, water use, natural ventilation, and photovoltaic systems.


Trends in building simulation 9

a matter that needs more study. It can be argued that such seamless transition can ingeneral not be automated as every translation between design and analysis requiresintervention of human judgment and expert modeling skills, strongly influenced bydesign context and analysis purpose.

In an attempt to put the observations of this section in a broad historic perspective,Figure 1.3 identifies building simulation trends between 1970 and 2010.

The foundation for building simulation as a distinct class of software applicationscame with the advent of first-principles-based formulation of transport phenomenain buildings, leading to DAE formulations that were amenable to standard computa-tional methods. The next step was towards broader coverage of other aspects of tech-nical building behavior. This movement towards function complete tools led to largesoftware applications that are being used today by a growing user base, albeit thatthis user base is still composed of a relatively small expert guild. The next two majormovements started in parallel in the 1990s and had similar goals in mind on differ-ent levels of granularity. Interoperability targets data sharing among (legacy) appli-cations whereas code sharing targets reuse and inter-application exchange of programmodules. Whereas the first tries to remove inefficiencies in data exchange, the latteris aiming for functionally transparent kits of parts to support the rapid building (orrather configuration) of simulation models and their rapid deployment.

Design integration adds an additional set of process coordination issues to its pred-ecessor movements. Ongoing trials in this category approach different slices of a verycomplex picture. It is as yet unclear what approach may eventually gain acceptanceas the best framework for integration.

The two most recent trends in Figure 1.3 have in common that they are Internetdriven. The Web enables a new breed of simulation services that is offered at an

R&D applied DAE

Interoperable

Code shared

Design integrated

Web-enabled

Pervasive/invisible “Invisible”

Function complete Energy, light, acoustics, CFDEnergyPlus, ESP, …

STEP, COMBINE, IAI, ...

OOP, EKS, SPARK, IDA, NMF, ...

ESP+, BLIS, DAI,SEMPER

e-Simulation, controls, remote, DAI+

1970 1980 1990 2000 2010

Figure 1.3 Trends in technical building performance simulation tools.Godfried Augenbroe, 2002. Trends in building simulation.


Drury B.Crawley (DOE) et al contrasted the capabilities of building energy performance simulation programs

BLAST, BSim, DeST, DOE-2.1E, ECOTECT, Ener-Win, Energy Express, Energy-10, EnergyPlus, eQUEST, ESP-r, IDA ICE, IES, HAP, HEED, PowerDomus, SUNREL, Tas, TRACE and TRYSYS.


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Table 1 General Modeling Features

BLA

ST

BSi

m

DeS

T

DO

E-2.

1E

ECO

TEC

T

Ener

-Win

Ener

gy

Expr

ess

Ener

gy-1

0

Ener

gyPl

us

eQU

EST

ESP-

r

HA

P

HEE

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IES

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omus

SUN

REL

Tas

TRA

CE

TRN

SYS

Simulation solution! Sequential loads, system, plant calculation

without feedback X X X

Simultaneous loads, system and plant solution X2 X X 3 X X X4 X X5 X X6 X X X X X7 X X Iterative non-linear systems solution X 3 X X X X X X X X X X X Coupled loads, systems, plant calculations X X X4 X X X X X X X X X Space temperature based on loads-systems

feedback X X X X8 X X X X X X X X X X X X X X

Floating room temperatures9 X X X X X X X X X X X X X X X X X X X X Time step approach X User-selected for zone/environment interaction X2 X10 R X11 X12 X13 X X X14 X X15 Variable time intervals for zone air/HVAC

system interaction X2 X10 X X X16 X R

User-selected for both building and systems X X X X X17 Dynamically varying based on solution transients X X X18

Full Geometric Description ! Walls, roofs, floors X X X X X X X X X X X X X X X X X X19 Windows, skylights, doors, and external shading X X X X X P X X X X X X20 X X X X X X

2 Only in IBLAST, an unreleased, integrated simulation version of BLAST. BLAST simultaneously calculates all zones in the “building” heat balance. 3 ECOTECT exports its models to the native file formats of EnergyPlus, ESP-r, HTB-2, and Radiance, invoking calculations and then importing results for display and analysis. 4 CNE simulation engine used by Energy-10 uses iterative convergence to achieve energy balance (thermal network coupled with building systems) at each time step. 5 HVAC air-side and water-side combined calculation 6 Loads and HVAC airside systems integrated with feedback. Plant is sequential with system/loads. 7 Idealized HVAC equipment only in release version. Research version with more realistic HVAC models. 8 Based on CIBSE Admittance Method for early design decision-making and analysis 9 No environmental controls 10 Up to 256 timesteps per hour 11 For Energy-10 the CNE engine runs in 15-minute time steps with results reported on an hourly basis. 12 15-minute default, 10 minute to 1 hour time steps. Use can modify so that 1 minute time steps can be done but not recommended due to stability issues. 13 1 minute to 1 hour time steps for zones and flow networks and a multiple of that for detailed systems. 14 1-hour default, 1-second to 24-hour time steps. 1-minute time interval schedules. 15 Building and system use the same time step. 1-hour default, user can select down to 0.1 second 16 5 minute time step for electric heat/cool/fan equipment for demand vs. energy cost calculation 17 Type 56 (building) uses an internal time step for airflow and envelope coupling. Other components (e.g. storage tanks) have internal time steps 18 User-specified tolerance controls time step and integration order 19 Taking into account geometry for view factors, detailed shading, direct radiation distribution requires additional input data. 20 Skylights with multiple beam reflections

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Table 2 Zone Loads

BLA

ST

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Heat balance calculation38! X X X X39 3 X X X39 X X X X X X X X X Building material moisture adsorption/desorption40! X41 X 3 X X O X X42 X P X43 Element conduction solution method Frequency domain (admittance method) X X X X Time response factor (transfer functions) X X X 3 X X X X X X X Finite difference / volume method X X X X44 X X

Interior surface convection Dependent on temperature X X 3 P X X45 X X X X X X X Dependent on air flow X X P X X X X E Dependent on CFD-based surface heat coefficient E E X User-defined coefficients46 X X X47 X X E48 X R X X X X X

Internal thermal mass X X X X X X X X X X X X X X X X X X X Human thermal comfort49! Fanger X X X X X X X X X X Kansas State University X X X Pierce two-node X X MRT (Mean Radiant Temperature) X X X X X50 X X X X X Radiant discomfort51 X X X P X Simultaneous CFD solution E E52 PAQ (Perceived Air Quality)53 X P

38 Simultaneous calculation of radiation and convection processes each time step 39 Only for calculation of custom weighting factors that are then used in the hourly calculation 40 Combined building envelope heat and mass transfer 41 Only in IBLAST, an unreleased, integrated simulation version of BLAST. 42 Takes into account combined vapor diffusion and capillary migration using variable transport coefficients 43 Simple or 2-node models. 44 As option for loads calculations. 45 A range of convection regimes can be specified. Heat transfer at each outside and inside face is re-evaluated at each timestep (unless specifically disabled). 46 Constants, equations or correlations 47 Constant coefficients only 48 Includes correlations from Khalifa and Marshall (1990), Awbi and Hatton (1999), Fisher (1995), Fisher and Pedersen (1997), Alamdari and Hamilton (1983), Beausoleil-Morrison (2000). 49 Based on occupant activity, inside temperature, humidity and radiation 50 Either as average MRT in zone or at an internal body using explicit radiation view factors to other zone surfaces 51 Explicit radiation view factors 52 Occupants and small power devices can be treated as blockages and heat/humidity/CO2 sources within the CFD domain. 53 Simsonson, Solonvaara and Ojanen (2001)

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Table 7 HVAC Systems

BLA

ST

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Discrete HVAC components135 X P X X X X R R X X Idealized HVAC systems X X X X X X136 X X X X137 User-configurable HVAC systems X X P X X X138 X139 X X X X R X X X Air loops140 X P X P X X X X X R X X X Fluid loops141 X P X X X X X X P R X X X Run-around, primary and secondary fluid loops with independent pumps and controls X P X X X X P X X X142

Fluid loop pumping power143 X X144 X X X Pipe flow-pressure networks145 X X

Air distribution system146 X P X X X147 X X X X R X

Multiple supply air plenums P X P X147 X X

Simplified demand-controlled ventilation! Ventilation rate per occupant and floor area X X X X X X148 X X X P X Ventilation air flow schedule X X X X X X X149 X X X X X X X User-defined ventilation control strategy150 X151 X X X X X X

CO2 modeling CO2 zone concentrations, mechanical and natural X X X X O111

135 Including part-load performance 136 ESP-r users tend to use ideal zone controls to represent environmental controls as loops of sensors and actuators with a range of controls laws. These can be combined with flow networks to represent air distribution systems if increased resolution is needed. For projects where detailed component performance is required a network of detailed systems components can be defined. 137 The multizone building model (Type 56) can optionally calculate the load from the temperature and humidity setpoints. A maximum power can be set and if that maximum is reached the model calculates the actual zone temperature 138 See Table 14 for a general discussion of how ESP-r approaches detailed system components and for a list of component types. 139 User selects a basic airside or waterside system type and then configures components permitted for that type of air loop or water loop. 140 Connect fans, coils, mixing boxes, zones 141 Hot water, chilled water and condenser loops connect equipment 142 By combining available components 143 Based on flow and pressure with 2/3-way valves with static head 144 Static head not supported. 145 Arbitrary structure with valves, pumps and controls 146 Including conduction losses and air leakage 147 Via plant components and/or flow network 148 Via CO2 based control 149 Intelligent controller manages night flushing and daytime economizer for passive cooling 150 Any combination of feed-forward/feedback controllers 151 CO2 controlled ventilation rates

Energy-10: early design stage, roughly defined, less accuracy

EnergyPlus: detailed, powerful engine, no interface

eQUEST: detailed, simple interface, widely used in industry as in US

......


What the simulation brought about in design?


“Architectural form used to appear as the ultimate result of a process of research.” -- Antoine Picon


“Silent, invisible electronic world” of virtual design must ultimately end in “physical reality” -- Norman Foster


“At the heart of the matter is the question: where do the aesthetic eye and an algorithm converge? How will a computer

know when to stop and how does that related to what we like?” -- Cecil Balmond


TimeProject Start Project End

Design



Design

Analysis



Design

Tools

Analysis



Design

Tools

Analysis


Design

Tools

Analysis


Tool late or not efficient


speeding up the design process

increasing efficiency

enabling the comparison of a broader range of design variants

better understanding of the consequences of design decisions


It is an instrument, which is exceptionally suitable to answer “what-

if”-type questions.-- Sten de Wit


“What would happen if we would like to make this design alteration?”


“What would be the effect of this type of retrofit?”


“What would be the building respond to these extreme conditions?”


Are the answers accurate?


Commonly the answers to these questions can only be estimated with some degree of uncertainty

lack of knowledge about the properties of the building or building component

Simplified simulation model given consideration of the complexity of the building


Help!What to do with this call for “help!”?


In practical commissioning


Base Model

Information from Energy Audit

What-if Scenario Analysis

Yearly Metered Data

Calibrated Model I

Chilled Water Steam Electricity!

Calibrated Model II

Monthly Metered Data

Adjust uncertain variables

Configure settings to mimic actual system performance

Level I Calibrate by Outcome Ideal (design) vs. Actual

!

Level II Calibrate by Behavior What-if based on current actual Performance

!

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Slide made by Bin Yan


Simulation Aided Design -- a proposal


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ANDRE, P., GEORGES, B., LEBRUN, J., LEMORT, V. & TEODORESE, I. V. 2008. From model validation to production of reference simulations: how to increase reliability and applicability of building and HVAC simulation models. Building Services Engineering Research & Technology, 29, 61-72.

AUGENBROE, G., 2002. Trends in building simulation. Building and Environment, 37(8– 9):891–902.

CRAWLEY, D. B., HAND, J. W., KURNMERT, M. & GRIFFITH, B. T. 2008. Contrasting the capabilities of building energy performance simulation programs. Building and Environment, 43, 661-673.

CRAWLEY, D.B., LAWRIE, L.K., PEDERSEN, C.O., WINKELMANN, F.C., WITTE, M.J., STRAND, R.K., LIESEN, R.J., BUHL, W.F., HUANG, Y.J., HENNINGER, R.H., GLAZER, J., FISHER, D.E. SHIREY, D., 2004. EnergyPlus: new, capable and linked. Journal of Architectural and Plan- ning Research (In Press, winter issue).

ENERGYPLUS DOCUMENTATION, 2010. Engineering Reference: the Reference to EnergyPlus Calculations. University of Illinois and the Ernest Orlando Lawrence Berkeley National Laboratory.

HABERL, J. & BOU-SAADA, T. 1998. Procedures for Calibrating Hourly Simulation Models to Measured Building Energy and Environmental Data. ASME Journal of Solar Energy Engineering, Vol. 120, pp. 193-204.

LIU, M. & CLARIDGE, D. E. 1998. Use of calibrated HVAC system models to optimize system operation. Journal of Solar Energy Engineering-Transactions of the Asme, 120, 131-138.

OLOFSSON, T., SJÖGREN, J. U. & ANDERSSON, S., 2005. Energy performance of building evaluated with multivariate analysis. Ninth International IBPSA Conference.


Documents

Building Simulation - Penn Engineeringcis800/lectures/simulation_gao.pdf · The foundation for building simulation as a distinct class of software applications came with the advent