Energy simulation tools for buildings
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Energy Simulation Tools for Buildings. Philip Haves Lawrence Berkeley National Laboratory [email protected] Presentation Outline. Applications and motivations History High level architecture Physical phenomena Levels of modeling detail and approximations

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Energy simulation tools for buildings

Energy Simulation Tools for Buildings

Philip Haves

Lawrence Berkeley National Laboratory

[email protected]


Presentation outline

Presentation Outline

  • Applications and motivations

  • History

  • High level architecture

  • Physical phenomena

  • Levels of modeling detail and approximations

  • Numerical methods and computational challenges

  • Users and user interfaces

  • Validation

  • Example applications:

    • San Francisco Federal Building – airflow network modeling, CFD

    • Naval Station Great Lakes – real-time simulation


Applications and motivations

Applications and Motivations

  • Building Design

    • Comparison of design alternatives

    • Code compliance

    • Prediction of actual energy consumption

  • Building Operations

    • Performance monitoring and fault detection

  • Product Development

    • Identify price/performance targets

  • Policy Development

    • Scenario analysis


History

History

1970

1980

1990

2000

Whole Building

Systems

TRNSYS

HVACSIM+

SPARK

IDA

Modelica

Post Office, NBSLD

Cal-ERDA

Cal-Pas

DOE-2

BLAST

ESP

Suncode

Trane Trace

TAS

EnergyPlus

eQuest

IES-VE


Architecture

Architecture

Weather

Reports

Envelope

Simulate

(time-

stepping)

Pre-process

Systems

Time Series

Schedules


Data model

Data Model

Project

Material Assemblies

Design Alternative 1

Other Systems

2

3

Building

Geometry

HVAC

Building Elements

Zones

Geometry

Usage

Location

Simulation

Report

Water Systems

Air Systems


Output

Output


Phenomena i

Phenomena - I

Time-scales: decades, year, day, minutes, ~instantaneous

Occupied Spaces

  • Heat and mass transfer – radiation, convection, conduction, absorption → heating, cooling and (de)humidification loads

  • Air flow – mechanical and natural ventilation

  • Pollutant transport and fate – gas, particles

  • Optical behavior of glazing systems and enclosures

  • Occupant comfort – thermal stress, draft risk, adaptive behavior

  • Indoor environmental quality – air pollution, odor, health, glare, noise

  • Occupant behavior – thermostats, windows, blinds


Phenomena ii

Phenomena - II

Solar Radiation

  • Solar position, shading, atmospheric turbidity

  • Sky radiation: sky dome, reflections from ground and other buildings

    Systems

  • Heat and mass transfer – heating and cooling systems:

    • refrigeration cycles – vapor compression, absorption

    • heat exchangers – sensible heat transfer, condensation, evaporation

  • Fluid flow networks – turbulent and transitional flow

    • duct and piping systems

    • natural ventilation and infiltration

  • Control systems

    • SISO cascaded control - local loop, supervisory

    • optimization-based control – model predictive control


Levels of modeling detail

Levels of Modeling Detail

  • Stock modeling – representative buildings

  • Whole building - dynamic HVAC loads, quasi-static systems

    • simple zoning, generic systems

    • room-level zoning, specific equipment

  • Room airflow:

    • interzonal networks – each zone homogeneous

    • CFD: velocity, temperature, contaminant fields – single or connected spaces

  • HVAC

    • annual simulation: predefined flow rates, quasi steady state, manufacturers’ data

    • control system design, e.g. demand response: dynamic component models, explicit modeling of local loops


Numerical methods i

Numerical Methods - I

  • Wall conduction:

    • transfer functions – fast but no non-linearities

    • finite difference – explicit or implicit

    • typically 1-D ― 2-D or 3-D for window frames, foundations, ground

  • Long wave radiation

    • (Ti4 - Tj4) ≈ 4Tave (Ti - Tj)

    • View factors or area-weighted mean radiant temperature

  • Surface convection

    • qi = hc(Θ, v, L, T) (Ti - Tair)

  • Heat balance method – each room: 6(+) surfaces + room air → 7(+) simultaneous (linearized?) equations per room – solve for:

    • temperatures (floating/unconditioned)

    • surface temperatures and heating and cooling loads


Numerical methods ii

Numerical Methods - II

  • Air flow

    • interzonal networks - two port non-linear elements connected at nodes that implicitly enforce mass balances

    • CFD: Navier Stokes equations + turbulence models:

      • large eddy models for airflow around buildings

      • simpler turbulence models for simple flows in interior spaces

  • Daylight distribution

    • daylight factors (interior/exterior illuminance) precalculated for simple geometries

    • ray tracing – forwards or backwards

  • HVAC system simulation

    • component models: non-linear differential and algebraic equations

    • solver matches inputs and outputs → well posed problem

    • problem reduction methods → small set of iteration variables


Computational challenges

Computational Challenges

  • Execution speed:

    • CFD

    • ray tracing

    • parametric studies

    • optimization

  • Speed and robustness

    • system simulation: large sets of DAE’s

  • Parallel computing: multi-core processors, GPU’s, supercomputers

    • ‘embarrassingly parallel’: parametrics, some optimization methods

    • multi-threading: ray tracing, CFD, radiant exchange … (hand crafting)

  • Visualization of building performance


Users and interfaces

Users and Interfaces

Users

Interoperability/interfaces

Building Information Models – object-oriented 3-D CAD

Cost estimating tools

Building control system

  • Building design engineers:

  • Architects

  • Building operators

  • Policy makers

  • Researchers

  • Educators


Cross validation

Cross-Validation


Measured design ratios relative to design eui

Measured/Design Ratios Relative to Design EUI

Source: Frankel and Turner, NBI


Predicting actual energy performance

Predicting Actual Energy Performance

  • Design simulations don’t model real conditions (building codes!)

    • occupancy schedules

    • plug loads

    • weather

  • Real buildings often don’t perform as expected by their designers:

    • faulty construction

    • malfunctioning equipment

    • incorrectly configured control systems

    • inappropriate operating procedures


Energy simulation tools for buildings

Design and Controls Pre-commissioning of a Naturally Ventilated Office Tower in San Francisco using a Coupled Thermal and Airflow Simulation Program

Philip Haves and Dimitri Curtil, Lawrence Berkeley National Laboratory

Paul Linden and Guilherme Carrilho da Gracia, Natural Works

Erin McConahey, Arup

Tim Christ, Morphosis

Work supported by the General Services Administration and the Federal Energy Management Program


Natural ventilation design issues

Natural Ventilation Design Issues

  • Is buoyancy needed to supplement wind?

  • If so, are external chimneys needed to supplement internal buoyancy?

    Use coupled thermal and airflow simulation (EnergyPlus) to predict performance of different design options:

  • wind-driven cross-flow ventilation

  • wind + internal stack

  • wind + internal + external stack

    Role of simulation:

  • give designers and client confidence that natural ventilation will work

  • select system


San francisco climate

San Francisco Climate

  • Prevailing wind from WNW

  • Occasional short hot periods

  • Daytime summertime temperatures 4-6oF lower than at airport, night-time temperatures ~equal


Energyplus

EnergyPlus

Thermal:

  • multi-zone whole building simulation

  • HVAC, lighting and (day)lighting

  • thermal storage, 15 minute time-step

  • heat balances on each surface and room air

  • Airflow:

  • air-flow between spaces connected by cracks and large openings

  • wind pressure  pressure coefficients, velocity profile

  • buoyancy  space temperatures at previous time-step


Testing the configurations predicted degree hours above base temperature

Base

temperature (oF)

Wind only

Internal stack

Int & ext stack

Int stack + wind

Int & ext stack + wind

72

288

507

432

279

285

75

80

118

103

76

76

78

13

25

19

11

12

Testing the configurations: Predicted degree-hours above base temperature


Energy simulation tools for buildings

The airflow pattern - pollutant/heat removal ability

short circuit & accumulation of pollutants

S

E

S

E

D

E

T

A

I

L


Energy simulation tools for buildings

Design of the flow deflector on the bottom of the lower window - second iteration.


Whole building performance monitoring and fault detection

Whole Building Performance Monitoring and Fault Detection

  • A collaboration between LBNL and United Technologies Research Center

  • Proof-of-concept at Naval Station Great Lakes

  • Real-time EnergyPlus connected to building control system

  • Solarimeter and sub-metering installed

  • Compare simulation and measurements:

    • Whole building electric and gas

    • Lighting

    • Plugs

    • Major HVAC:

      • Chillers

      • Large fans

  • Significant differences:

    • Calibrate the model?

    • Fix the building?

28


Future work

Future Work

  • Usability

    • better user interfaces to support design workflow

    • interoperability

  • Computational efficiency

  • Software architecture – separation of models, numerics and interfaces

  • Stochastic modeling – occupant behavior, weather …

  • Model validation

    • empirical validation – laboratory and real buildings

    • inter-model comparisons

    • characterization of modeling uncertainties

  • Process validation – standard practices, QA

    • protocols for different simulation goals

    • input data uncertainties, model uncertainties → output uncertainties

  • Education and training

    • generic principles of simulation

    • use of specific tools

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