What you will learn
- What building performance simulation covers, from energy to daylight
- How models are built from design geometry and systems data
- What option comparison and sensitivity analysis require
- How results are reported for design decisions and compliance
- How to phase a tool from one analysis type to a full suite
What a building performance simulation tool is
A performance simulation tool predicts how a building behaves before it is built. Given geometry, materials, glazing, systems, climate data, and occupancy patterns, it models energy consumption, daylight levels, and thermal comfort, hour by hour through a year. Design teams use it to compare options — glazing ratios, shading, insulation, system choices — and to support compliance submissions with modelled evidence.
Option comparison is the use that matters. A single simulation result is hard to judge; a set of options modelled consistently, with the differences and their causes visible, lets the team choose with evidence. The tool should therefore make consistent, comparable runs easy, not just single runs possible.
Core features
Comparable option runs with transparent assumptions define the product.
- Model import from design geometry and systems data
- Energy modelling with hourly simulation through a year
- Daylight analysis with spatial and temporal metrics
- Thermal comfort modelling by space and season
- Option comparison with consistent assumptions and difference views
- Reporting for design decisions, clients, and compliance submissions
How it is built
Start with one analysis type and option comparison, then add analyses.
- Model: geometry, materials, systems, and climate data import
- Energy: hourly simulation and results for one building type
- Options: comparison workflows with consistent assumptions
- More analyses: daylight, thermal comfort, and sensitivity
- Reporting: design reports, client summaries, and compliance packs
Technology choices
Simulation engines should come from established, validated sources, with the tool built around them for modelling, comparison, and reporting. Reimplementing physics engines invites errors in results that inform real design and compliance decisions.
Assumptions must be explicit and versioned. Climate files, occupancy patterns, and system efficiencies shape results, and a report should state them so results can be reproduced and challenged.
Challenges to plan for
Model quality limits results. Geometry errors, missing thermal bridges, and wrong system data produce precise-looking nonsense, so the tool should validate models and flag gaps before simulation, not just report results.
Compliance reporting needs care. Compliance submissions require specific methods and formats, and the tool should support those explicitly rather than asking teams to reformat design results.
Who it is for, and its limits
Performance simulation fits architecture firms, engineering consultancies, and sustainability teams designing low-energy buildings. It fits projects where performance targets and compliance require modelled evidence.
Simulation does not guarantee performance. Results depend on model quality and assumptions, and operational performance also depends on construction quality and occupant behaviour; reports should state those limits.
What a first release looks like
A first release should model energy for one building type with option comparison and assumption reporting. Daylight and thermal comfort analyses come later, once option comparisons have informed real design decisions, including a case where the preferred option changed because the comparison showed its true cost. Assumption transparency must be proven: every report states its climate file, occupancy patterns, and system efficiencies, so results can be reproduced and challenged.
Consider a design team comparing glazing ratios for an office floor. The tool runs consistent simulations for three options, showing energy use, peak loads, and the assumptions behind each run. The middle option wins on balance, and the team records the comparison with its assumptions in the design report. Later, when the client questions the choice, the team reruns the comparison from the recorded assumptions and reproduces the result. If assumptions are buried or missing, the comparison is an opinion with charts attached.
A mistake worth avoiding
The mistake worth avoiding is presenting simulation results without their assumptions. An energy figure without its climate file, occupancy pattern, system efficiencies, and model quality notes cannot be reproduced, challenged, or compared — yet it will be quoted in design meetings and compliance discussions as if it were a measurement. The discipline is assumption-attached reporting: every result published with the assumptions that produced it, versioned alongside the model, so a later team can rerun the comparison and get the same answer. Simulation without stated assumptions is not evidence; it is a number with a chart.
Frequently asked questions
What does energy modelling predict?
Hourly energy consumption through a year, given geometry, materials, systems, climate, and occupancy, so design options can be compared.
Why compare options consistently?
Because a single result is hard to judge. Consistent assumptions across options make differences meaningful and attributable to design choices.
How is daylight assessed?
Through spatial and temporal metrics showing daylight levels across spaces and seasons, not just a single average.
Can results support compliance?
Yes, where the tool supports the required methods and formats, with assumptions stated in the compliance pack.
How much does it cost to build?
Cost depends on analysis types, model import depth, and reporting requirements. One analysis type for one building type is far smaller than a full simulation suite, so confirm with a scoped quote.