Assessing gaps and needs for integrating building performance optimization tools in net zero energy buildings design

Abstract

This paper summarizes a study undertaken to reveal potential challenges and opportunities for integrating optimisation tools in Net Zero Energy Buildings (NZEB) Design. The paper reviews current trends in simulationbased Building Performance Optimisation (BPO) and outlines major criteria for optimisation tools selection and evaluation. This is based on analyzing user's needs for tools capabilities and requirement specifications. The review is carried out by means of a literature review of 165 publications and interviews with 28 optimisation experts. The findings are based on an inter-group comparison between experts. The aim is to assess the gaps and needs for integrating BPO tools in NZEB Design. The findings indicate existing limitations including model uncertainty, computation time, difficulty of use and steep learning curve. Some future directions anticipated or needed for improvement of current tools are presented.

Analysis of Photovoltaic Applications in Zero Energy Building Cases of IEA SHC/EBC Task 40/Annex 52

“…Studies on various energy calculation methods and load matching for NZEB definition were also performed [11][12][13]. Optimization tools and methods for NZEB design were comprehensively reviewed [14][15][16][17]. Meanwhile, based on conventional international standards and design model cases, the influences of NZEB passive elements and occupant behavior patterns on energy consumption and generation were analyzed [18][19][20].…”

Identification of cost-optimal and NZEB refurbishment levels for representative climates and building typologies across Europe

“…Further review studies on these subjects more specifically focusing on NZEB developments are presented by Attia et al (2013) and Lu et al (2015). Several examples of application of this method also with the aim of determine the optimum in terms of energy performances and costs (life cycle or initial costs) are presented in numerous studies (Diakaki et al 2008;Brown et al 2010;Morrissey and Horne 2011;Asadi et al 2012;Fesanghary et al 2012;Kumbaroğlu and Madlener 2012;Rysanek and Choudhary 2013;Penna et al 2015).…”

Framework for assessing the performance potential of seasonally adaptable facades using multi-objective optimization

“…The coupling of BPS tools with evolutionary optimization algorithms has proven to be a valuable approach for efficient and effective exploration of the option space in building envelope design [43][44][45][46][47][48]. Particularly in supporting high-performance building design, the application of multi-objective optimization (MOO) algorithms is useful [49][50][51], as it allows for visualization of trade-offs between two or more conflicting design objectives [52,53].…”