The paper describes a novel approach involving interoperability, data modelling technology, and application of the building information model (BIM) focused on sustainable architecture. They share relationships and multiple experiences that have existed for years but have never have been proven. This interoperability of building performance simulation maps building information and parametric models with energy simulation models, establishing a seamless link between Computer Aided Design (CAD) and energy performance simulation software. During the last four decades, building designers have utilized information and communication technologies to create environmental representations to communicate spatial concepts or designs and to enhance spaces. Most architectural firms still rely on hand labor, drafted drawings, construction documents, specifications, schedules and work plans in traditional means. 3D modelling has been used primarily as a rendering tool, not as the actual representation of the project. With this innovative digitally exchange technology, architects and building designers can visually analyze dynamic building energy performance in response to changes of climate and building parameters. This software interoperability provides full data exchange bidirectional capabilities, which significantly reduces time and effort in energy simulation and data regeneration. Data mapping and exchange are key requirements for building more powerful energy simulations. An effective data model is the bidirectional nucleus of a well-designed relational database, critical in making good choices in selecting design parameters and in gaining and expanding a comprehensive understanding of existing data flows throughout the simulation process, making data systems for simulation more powerful, which has never been done before. Despite the variety of energy simulation applications in the lifecycle of building design and construction projects, there is a need for a system of data integration to allow seamless sharing and bidirectional reuse of data.