Building Performance Simulation: Importance, Software And Uses

Introduction

Building Performance Simulation (BPS) is a powerful tool that utilizes computer-based mathematical models, grounded in fundamental physical principles and engineering practices, to replicate and analyze various aspects of a building’s performance.

The primary goal of BPS is to quantify critical aspects of building performance relevant to design, construction, operation, and control. It encompasses several sub-domains, including thermal simulation, lighting simulation, acoustical simulation, and air flow simulation, each addressing specific facets of a building’s behavior. BPS plays a vital role in scientific computing and the design of energy-efficient buildings.

Importance Of Building Performance Simulation

Buildings are intricate systems influenced by a multitude of parameters. BPS simplifies this complexity by creating abstract models that allow for detailed analysis and the evaluation of key performance indicators without the need for expensive physical measurements. BPS offers an efficient and cost-effective way to assess various aspects, including energy demand, indoor environmental quality (thermal and visual comfort, indoor air quality, and moisture control), HVAC and renewable system performance, urban-level modeling, building automation, and operational optimization.

Evolution Of Building Performance Simulation

Over the past six decades, numerous BPS software programs have been developed to cater to different aspects of building performance. These tools range from climate analysis and thermal comfort assessment to energy calculations and daylight simulations. The core of BPS revolves around multi-domain, dynamic, whole-building simulation tools that provide critical indicators like heating and cooling loads, energy demands, temperature trends, humidity levels, comfort metrics, air quality, ecological impact, and costs.

Key Input Data For BPS

A typical BPS model requires various input data, including:

1. Climate: Ambient temperature, relative humidity, solar radiation, wind speed, and direction.
2. Site: Building location, orientation, shading from nearby structures, and ground properties.
3. Geometry: Building shape and zone configurations.
4. Envelope: Material properties, construction details, windows, thermal bridges, and openings.
5. Internal Gains: Heat generated by lighting, equipment, and occupants, including operation schedules.
6. Ventilation System: Air transport and conditioning (heating, cooling, humidification).
7. Room Units: Local heating, cooling, and ventilation units.
8. Plant: Centralized units for energy transformation, storage, and delivery.
9. Controls: Strategies for window operation, shading, ventilation, room units, and plant components.

Key Performance Indicators

BPS provides a wealth of key performance indicators, including:

1. Temperature Trends: Analysis of temperature variations in zones, on surfaces, and within construction layers.
2. Comfort Indicators: Evaluation of comfort parameters like PMV (Predicted Mean Vote) and PPD (Predicted Percentage of Dissatisfied), radiant temperature asymmetry, CO2 concentration, and relative humidity.
3. Heat Balances: Calculation of heat balances for zones, entire buildings, or individual plant components.
4. Load Profiles: Profiles of heating and cooling demands, as well as electricity consumption for equipment and lighting.
5. Energy Demand: Assessment of energy consumption for heating, cooling, ventilation, lighting, equipment, and auxiliary systems (e.g., pumps, fans, elevators).
6. Daylight Availability: Analysis of natural light availability in specific zones at different times and under varying external conditions.

Additional Uses Of BPS Software

Apart from performance evaluation, BPS software finds applications in:

1. System Sizing: Determining the appropriate sizes of HVAC components, heat exchangers, boilers, chillers, heat pumps, and renewable energy systems.
2. Control Strategy Optimization: Configuring controllers for shading, window operation, heating, cooling, and ventilation to improve operational efficiency.

Historical Perspective

The history of BPS is intertwined with the development of computers. In the late 1950s and early 1960s, the United States and Sweden initiated early developments in building simulation. Initially, models focused on analyzing individual system components using steady-state calculations, such as gas boilers. The first reported building simulation tool, BRIS, emerged in 1963. The 1970s marked significant advancements with the release of powerful simulation engines like BLAST, DOE-2, ESP-r, HVACSIM+, and TRNSYS, driven by the energy crisis in the United States.

BPS grew through collaborative efforts involving academia, government institutions, industry, and professional organizations. It matured into a discipline offering unique expertise, methods, and tools for evaluating building performance. This evolution led to increased discussion about improving the flexibility of simulation tools in the 1980s, with the development of equation-based simulation environments like ENET and Modelica.

Challenges And Future Directions

Building Performance Simulation continues to face challenges related to problem representation, performance assessment, operational application, and user education. Key tasks for the BPS community include:

1. Promoting Better Concepts.
2. Standardizing Input Data and Model Libraries.
3. Establishing Standard Performance Assessment Procedures.
4. Integrating BPS More Effectively into Practice.
5. Providing Operational Support and Fault Diagnosis.
6. Offering Education, Training, and User Accreditation.

Ensuring Accuracy In BPS

Accuracy in building simulation models is crucial. It refers to the alignment between simulation results and actual building performance measurements. Sources of uncertainty in BPS stem from approximations in model inputs, occupant behavior, and other factors. Calibration, the process of adjusting model inputs to match real-world data, is essential. Factors affecting reliability in BPS include data quality, simulation engineer competence, and the methods employed in the simulation engine.

Standardization And Validation

ASHRAE Standard 140-2017 outlines a method to validate the technical capability and applicability range of BPS software. ASHRAE Guideline 4-2014 provides performance indices criteria for model calibration. These indices include Normalized Mean Bias Error (NMBE), Coefficient of Variation (CV) of the Root Mean Square Error (RMSE), and R2 (coefficient of determination), with recommendations for acceptable values.

Technological Aspects

Given the complexity of building energy and mass flows, BPS relies on numerical methods like response function methods or finite differences/finite volume approximations, as analytical solutions are often impractical. Many BPS programs use imperative programming languages, limiting model flexibility and extensibility. Some modern engines utilize symbolic Differential Algebraic Equations (DAEs) with general-purpose solvers, enhancing model reuse, transparency, and accuracy.

Applications Of Building Performance Simulation

Building simulation models find application in various contexts, including:

1. Architectural Design: Comparing design options to inform energy-efficient building design.
2. HVAC Design: Calculating thermal loads for equipment sizing and system control strategy design.
3. Building Performance Rating: Demonstrating compliance with energy codes, green certifications, and financial incentives.
4. Building Stock Analysis: Supporting the development of energy codes, standards, and large-scale energy efficiency programs.
5. CFD in Buildings: Simulating boundary conditions for Computational Fluid Dynamics (CFD) studies.

Software Tools For BPS

Numerous BPS software tools are available, categorized into three main types:

1. Applications with Integrated Simulation Engine (e.g., EnergyPlus, ESP-r, TAS, IES-VE, IDA ICE).
2. Software that Docks to a Certain Engine (e.g., Designbuilder, eQuest, RIUSKA, Sefaira).
3. Plugins Enabling Performance Analysis (e.g., DIVA for Rhino, Honeybee, Autodesk Green Building Studio).

These tools provide a range of capabilities, from whole-building simulations to model input calibration and building auditing. They consist of both simulation engines, responsible for solving thermodynamic and building science equations, and modeler applications that provide user-friendly interfaces for data input and result visualization.

Notably, some software packages offer both the calculation engine and interface within a single product. Here is an overview of commonly used simulation engines and modeler applications in the field of BPS:

1. ApacheSim: Developed by Integrated Environmental Solutions Ltd. (UK), ApacheSim is a commercial tool known for its integrated simulation engine. It offers advanced features for building performance analysis.
2. Carrier HAP: Created by United Technologies (US), Carrier HAP is a commercial tool primarily used for HVAC design, with a focus on thermal load calculations.
3. COMFIE: Developed initially by Mines ParisTech and later by IZUBA énergies (France), COMFIE is a commercial software specializing in building performance analysis and simulation.
4. DOE-2: James J. Hirsch & Associates (US) developed DOE-2, a freeware simulation engine with a long history of applications. It serves as the core for several modeler applications, including eQuest, RIUSKA, EnergyPro, and GBS.
5. EnergyPlus: Developed by Lawrence Berkeley National Laboratory (US), EnergyPlus is a widely used freeware simulation engine known for its versatility. It integrates with modeler applications such as DesignBuilder, OpenStudio, cove.tool, and many others.
6. ESP-r: Created by the University of Strathclyde (UK), ESP-r is a freeware simulation engine with a focus on energy performance analysis. It also functions as a standalone modeler application.
7. IDA: Developed by EQUA Simulation AB (Sweden), IDA is a commercial simulation engine using Differential Algebraic Equations (DAEs) and Modelica. It is paired with the IDA ICE modeler.
8. SPARK: Lawrence Berkeley National Laboratory (US) offers SPARK as a freeware simulation engine that utilizes DAEs. VisualSPARK serves as the graphical interface for model creation.
9. TAS: Environmental Design Solutions Limited (UK) developed TAS as a commercial simulation engine with a 3D modeling interface called TAS 3D Modeler.
10. TRNSYS: Created by the University of Wisconsin-Madison (US), TRNSYS is a commercial simulation engine known for its versatility and applications in Simulation Studio and TRNBuild modeler applications.

BPS In Practice And Global Adoption

Since the 1990s, BPS has transitioned from being primarily a research tool to becoming an essential design tool for industrial projects. However, its adoption varies widely between countries. Building certification programs like LEED (USA), BREEAM (UK), and DGNB (Germany) have played a pivotal role in expanding the application of BPS. National building standards, such as ASHRAE 90.1 (USA), BBR (Sweden), SIA (Switzerland), and NCM (UK), have further encouraged industrial adoption.

Performance-Based Compliance

In a performance-based compliance approach, building codes and standards rely on predicted energy use from BPS, rather than rigid, prescriptive requirements. This approach offers greater design flexibility, provided that overall building performance meets specified criteria. Certifying agencies define model inputs, software specifications, and performance requirements to ensure compliance.

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Conclusion

Building Performance Simulation is a vital tool for optimizing building design, operation, and energy efficiency. It simplifies the complex interactions within buildings, providing valuable insights to architects, engineers, and policymakers. As BPS continues to evolve, addressing challenges related to accuracy, standardization, and practical application will be crucial. This versatile technology has the potential to play a significant role in creating sustainable and energy-efficient buildings worldwide.