Decision support to enable energy efficient building design for optimised retrofit and maintenance

Optimising energy consumption of new buildings (through design) and reducing energy consumption of existing buildings (using optimised retrofitting or maintenance) are important to achieving the global targets of energy saving and cutting CO2 emissions of buildings. Many decision support tools have been developed for architects and building designers to choose the best building design options with retrofit and maintenance in mind. However, there is a lack of understanding of the required data structures and databases that would support design and enable Facility Management (FM) in making best decisions during retrofit and maintenance for improved energy efficiency (EE). To address these limitations a decision support tool based on Multiple Criteria Decision Making (MCDM) for architects, energy designers and for FM is being developed within an ongoing EU research project “Design4Energy”, to enable design for EE maintenance and retrofit and support the FM in the operation stage. In this paper three aspects are presented: (1) analysis of existing decision support tools; (2) detailing the database requirements in terms of information technology (IT), components and systems, materials and the stakeholders on the basis of a literature search and a survey conducted with of stakeholders from the building sector; (3) a first prototype of a decision support tool for maintenance and retrofit being developed

Functional requirements and system architecture for decision support of energy efficient building design in retrofit and maintenance stage

This paper describes development of a methodology to support better retrofit and maintenance with optimised energy consumption using evolving technologies in material, components and systems both at building and neighbourhood levels. It is based on a retrofit and maintenance scenario focused on specification of the functional requirements, databases requirement and system architecture for the construction and operation of the decision support tool. Decision support (DS) tools have already been developed for architects and building designers to choose best building design options with retrofit and maintenance in mind. However, there is a lack of understanding of the required data structures, databases, definition of the functional requirements and the variety of the possible system architectures for this application. The proposed DS tool will support Facility Management (FM) to design their option on Building Information Model (BIM) file by making best retrofit and maintenance decisions for improved energy efficiency (EE) without needing full knowledge of the latest technologies in any required subject and without being expert in building energy performance analysis and simulation. A detailed retrofit and maintenance scenario and its corresponding process map are developed and explained in details. Database requirements are extracted and discussed, leading to specification of the necessary structure and content with a level of details. The functional requirements for retrofit and maintenance design scenario are discussed and an exhaustive list is generated. The decision support tool was structured using four building blocks: (i) energy performance and simulation block; (ii) retrofit and maintenance options generator; (iii) optimisation block and; (iv) a decision making block based on Multiple Criteria Decision Making (MCDM) method

Collaborative environment for energy-efficient buildings at an early design stage

This paper provides an approach for creating a collaborative environment for energy efficient buildings highlighting the issues required to be addressed at an early design phase. The paper will discuss a design scenario for a new built and suggest system architecture for implementing such scenario through the use of advanced simulation tools and modelling techniques to improve current practice in an early design phase. The suggested system architecture will allow multi-disciplinary teams to collectively and individually explore various energy solutions in a 3D interactive workspace to achieve optimum energy efficiency at building level. © 2015 Taylor & Francis Group