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Ren4EEnIEQ - Comprehensive BIM add-on tool for the improvement of energy efficiency and indoor environment quality in renovation of buildings

COMPETE

Title: Ren4EEnIEQ - Comprehensive BIM add-on tool for the improvement of energy efficiency and indoor environment quality in renovation of buildings

Coordinators at INESCC: Álvaro Gomes

Co-Coordinator:

Project Team:

Date of approval: 08-04-2016

Dates start/end: 01-07-2016 / 30-06-2019

Total Eligible Cost: 71 456.00€

EU Financial Support: 60 737.60€

National Financial Support: 10 718.40€

Project Code: POCI-01-0145-FEDER-016760

Region of intervention:

Beneficiaries: Universidade de Aveiro, INESC Coimbra - Instituto de Engenharia de Sistemas e Computadores de Coimbra, Associação para o Desenvolvimento da Aerodinamica Industrial

Copromotor:

Site: https://ren4eenieq.wordpress.com/

Synopsis

The efficient use of energy in the built environment is a very important issue for a more sustainable future. The building stock accounts for 31% of the global energy consumption, with space heating and cooling representing one-third (up to 60% in cold climates). Building renovations can play an important role in the reduction of the end-user energy consumption. For this reason, a great interest has been put in adequate building analysis and in the development of building retrofit tools.

There are several computer-based optimization tools for building renovation/retrofit. However, these tools aim to determine the best combination of a few Constructive System (CS) and Energy System (ES - lighting, hot water, renewable energy, and HVAC) decision variables, but omit the actual architectural draft in the decision-making process. Therefore, such tools have limited impact in real case scenarios, when deep building renovation may result in profound adaptations to accommodate new occupational functions, and limited impact since only a partial optimization is carried out.

This research aims to develop a comprehensive tool for deep building renovation, which comprises the building survey, design generation, building geometry optimization, and ES and CS optimization in single BIM add-on tool. A user interactive multi-optimization procedure will be developed to assist the architect in searching for the best building renovation solution that minimizes energy consumption (EC) and maximizes the indoor environmental quality (IEQ) in a cost-effective manner. The resulting tool will be tested in architectural design practice scenarios to determine its strengths and weaknesses. The results will be written in a tool guidebook and disseminated in a technical seminar on building retrofit/renovation.

This innovative and unique approach has never been developed in the building renovation/retrofit research field. The research approach aims to create a tool to assist the building practitioner in finding the best design strategy according to competing objectives. Three core algorithms will be developed, which are based in previous works of the research team. The first algorithm is capable of generating alternative floor plan designs according to the same preferences and requirements of the user. It is a hybrid evolutionary strategy approached enhanced with a local search technique. This algorithm combines several requirements that were otherwise spread in different space planning approaches. It has been tested in several multi-level complex design programs with promising results. The second algorithm explores the thermal performance improvement potential of the generate floor plans, by changing sequentially several geometry variables, such as the building orientation, the openings position and size, the design of the shading mechanisms, the interior wall position, etc. The third algorithm to be developed aims to find the best renovation strategy considering CS and ES in a cost-effective manner. The developed algorithms, however, need to be further developed to fully tackle deep building renovations.

Additionally, two other algorithms will be developed to widen and improve the tool usage efficiency. The first algorithm is a trained Artificial Neural Network (ANN) for building performance assessment. It will be used during optimization processes of the core algorithms, as alternative to the dynamic simulation, which requires long computational runtimes. The dynamic simulation will be used in the tool for detailed performance reports and online training of the ANN. The aim of the second algorithm is to facilitate the building survey process. A 3D point cloud algorithm with a logarithmic proportional objective function will be used to capture and automatically generate the existing building geometry.

These five algorithms will be implemented in a BIM add-on user graphical interface, thus integrating this approach in the architectural workflow. As the usability and accessibility of the tool is an important issue for the aiming practitioners, ergonomic tests for human-interface interactions will be carried out. This information will be feedback to the tool developers. Finally, the tool will be tested in real case scenarios of different levels of building renovation.

The team is composed of several experts with different scientific background in buildings, such as architectural generative design, building retrofit, building energy efficiency, applied optimization, building survey, and ergonomics in human-interface interactions. Also, the team has the contribution of three renown international consultants, which cover specific objectives of the research project, such as the implementation of the tool in the fields of building performance simulation, BIM operability, and IFC standards.