January 27th 2025

Case Study: Leveraging IESVE's Parametric Simulation for Optimised Building Performance

Case Study: Leveraging IESVE's Parametric Simulation for Optimised Building Performance

An EU project has demonstrated the power of IESVE’s Parametric Simulation feature for efficient analysis and optimisation of building design choices to reduce energy consumption, emissions, and operating costs. 

LEGOFIT, a Horizon Europe funded project, aims to design, implement and validate an advanced and dynamic integrative approach to reach Energy Positive Homes (EPH). Using smart and innovative solutions, with a high scalability and replicability for building construction and renovation, the project aims to develop a holistic design platform that encompasses not only passive and active technologies, but also their integration, for the smartest exchange of information and interoperability of systems, based on Building Information Modelling (BIM).

This case study focuses on one of the project’s new-build demonstration sites in Luxembourg, where one of 24 single-family homes was chosen for detailed analysis to gather insights on optimal HVAC settings and construction configurations through parametric simulations. Experts from IES collaborated with researchers from the Luxembourg Institute of Science and Technology (LIST) for the baseline energy modelling and information gathering for this pilot site.

The team then used IESVE’s Parametric Simulation feature, which enables users to evaluate multiple design configurations to determine their contribution to the building’s overall energy performance. This made it the ideal tool to support LEGOFIT's objective of making buildings adaptable, energy-efficient, and capable of sustaining a positive energy balance over their lifetime.

Houses at the Luxembourg demo site are equipped with PV panels, salt-water battery storage, heat pumps, and greywater recovery systems, creating an energy-efficient and sustainable environment. In a development such as this, testing a range of building parameters and HVAC configurations was valuable for identifying optimal settings for energy-positive performance, providing insights to guide design improvements across the broader initiative. 

The Challenge

The primary objective was to assess and compare multiple design parameters to identify the most energy-efficient solution for the building under various conditions. Given the range of options and combinations to test, running a traditional trial-by-trial simulation would have been highly time-consuming.

The Solution: Parametric Simulation in IESVE

IESVE's Parametric Simulation feature was the ideal solution for this project, allowing the consultants to model various design configurations. The tool enables users to set multiple parameters simultaneously, run thousands of design permutations, and analyse outputs efficiently. Key parameters tested included:

  • Setpoints: heating and cooling setpoints with an increment of 1°C 
  • Building Envelope: External wall, windows and roof U-values, external windows g-value 
  • Seasonal Efficiencies: SCoP (Seasonal Coefficient of Performance) and SSEER (Seasonal Energy Efficiency Ratio) of the heating and cooling systems 

The team addressed the key design questions, such as the impact of envelope improvements on energy savings, or the impact of heating and cooling efficiencies and the setpoint on the overall energy consumption. Figures 1 and 2 below show the different parameters considered for permutations in the parametric tool. 


Figure 1: Parameters tested in IESVE - setpoints and seasonal efficiencies

Figure 2: Parameters tested in IESVE - building envelope

However, the parametric feature can also take into account other parameters with the objective to find the best orientation for daylight utilisation, and the influence of renewable energy options on emissions, or to optimise HVAC system loads/sizing , shading, orientation, renewables, internal gains, infiltration rates, etc.,  producing an abundance of data for further analysis.

Execution and Performance

The parametric simulation setup enabled testing of around 20,000 permutations over a span of approximately 20 hours for this model in Luxembourg, leveraging the multi-core processing capability of a standard laptop. The streamlined automation reduced manual setup time significantly, with actions such as loads sizing, thermal performance assessment, and result generation executed in a sequential, automated workflow. The time needed to run these simulations varied depending on the machine’s processing power and available cores. 

This high-speed, high-volume testing provides a uniquely efficient pathway to optimise building parameters, rapidly producing valuable data for energy-positive performance while significantly reducing manual setup and processing time.

Data Analysis and Insights

To interpret the results of this extensive simulation effort, tools such as Parallel Coordinates were used (Figure 3). These visualisations provided an intuitive way to explore the influence of each parameter on energy performance and to compare potential scenarios (Figure 4). Furthermore, all results could be exported to CSV files for further machine learning applications, allowing for continued model training and data refinement.


Figure 3: Parallel Coordinates chart of all parametric simulation results

As an example, the team aimed to reduce the carbon emissions, maintain a high heating SCOP, and average external window g-value, and a preferred cooling setpoint, which narrowed down the number of options to 13 possible combinations for the building. 


Figure 4: Filtered results for specific criteria of parameters

A further specification can narrow this to a singular combination of parameters for design: 


Figure 5: Just one permutation example

Conclusion

This project has demonstrated an innovative approach to designing Energy Positive Homes, using advanced parametric simulations in IESVE to optimise energy efficiency across multiple building setups. The software's ability to efficiently run thousands of permutations to identify, test and refine high-performance designs and system settings in detail has been central to supporting LEGOFIT's goal of scalable, adaptable building solutions. 

“This case study has been a powerful demonstration of the value of IESVE’s parametric simulation feature when it comes to assessing different configurations to optimise building energy efficiency. I would like to thank all of the LEGOFIT project partners for their collaboration on this project and in particular my colleague, Daniele Patti, lead energy modeller in this task, who was instrumental in delivering the analysis and drafting of this case study.”Amisha Panchal, Project Manager, IES

For more information on parametric simulation in IESVE, you can check out the resources on our Parametric Simulation page.