This paper presents work undertaken as part of the European H2020 project OptEEmAL (Optimized Energy Efficient Design Platform for Refurbishment at District Level), toward development of a decision-support platform for building and district refurbishment interventions. We describe a methodology for generation and evaluation of refurbishment scenarios for building and districts with particular emphasis on "active" energy conservation measures (i.e., installation or replacement of heating, ventilation, air conditioning (HVAC) systems) and related controls. The impact of HVAC and controls on energy and economic key performance indicators are usually neglected or very simplified in existing energy simulation tools. We apply a model-based approach to evaluate key-performance indicators related to energy consumption and energy costs in buildings and districts, such that possible refurbishment alternatives can be easily evaluated, thereby showing how a smart decision support tool will allow stakeholders to compare multiple alternatives quickly. By considering relevant case studies at building and district level, including refurbishment of heating and cooling plants, we highlight, in a simulation-based study, how the deployment of efficiency-based controls enable significant energy savings thanks to the exploitation of the model-based approach. This way, additional motivations for energy savings and ultimately for new investments in energy-related technologies are provided.
The realization of smart and energetically efficient buildings is contingent upon the successful implementation of two tasks that occur on distinct phases component. An illustrative application of the proposed methodology in an office building is provided. MOTIVATIONEffective utilization of energy in buildings is receiving significant attention. This interest is justified on the observation that buildings account for a significant portion of end-energy use: in Europe 40% of the total energy consumed is used for the operation of buildings (Perez-Lombard et al., 2008) with a significant part of that energy used for conditioning occupied spaces. Energy retrofits, properly selected and executed, can yield appreciable reduction in energy demands. But the value of effective energy utilization during the building operational phase is undisputed both in terms of achieving good occupant comfort and in reducing energy consumption.In domestic environments the extensive research on intelligent temperature regulation and the proliferation of smart thermostats and home automation solutions are partly a response to that need. In the nondomestic building sector Building Energy Management Systems (BEMS) are used to ensure proper operation of systems and components in an energyefficient manner. Typical BEMS installations comprise a communication and data management layer enabling communication and data transfer between interacting field devices (sensors, actuators, field controllers); C 2015 Computer-Aided Civil and Infrastructure Engineering.
Energy retrofitting is paramount to reduce the use of energy in existing buildings, with benefits to the environment and people's economy. The increasing use of novel technologies and innovative methodologies, such as Terrestrial Laser Scanning (TLS) and Building Information Modelling (BIM), is contributing to optimise retrofit processes. In the context of energy efficiency retrofitting, complex semantic 3D BIM models are required that include specific information, such as second level space boundaries (2LSBs), material energy performance properties, and information of the Heating Ventilation and Air Conditioning (HVAC) system and their layout. All this information is necessary for energy analysis of the existing building and planning of effective retrofitting strategies. In this paper, we present an integrated (semi-)automated Scan-to-BIM approach to produce BIM models from point clouds and photographs of buildings by means of computer-vision and artificial intelligence techniques, as well as a Graphical User Interface (GUI) that enables the user to complete the models with information that cannot be retrieved by means of visual features. Information about the materials and their performance properties as well as the specification of the HVAC component is obtained from a database that integrates information from BAUBOOK, OKOBAUDAT and ASHRAE. The Scan-to-BIM tool introduced in this paper is evaluated with data from an inhabited two-storey building, delivering promising results in energy simulations.
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