Building Information Modelling (BIM) is increasingly deployed as part of the processes in Architecture, Engineering and Construction (AEC) industry projects. While the benefits of BIM have been extensively proclaimed, explicit justification in terms of direct cost savings for BIM implementation on real-life projects, particularly for clash detection BIM workstream, are not well documented. This paper proposes and demonstrates a methodology to prove how BIM-based clash detection leads to cost savings. A schema is developed based on literature review and industrial expertise to quantify cost savings achieved by the utilisation of BIM-based clash detection and resolution. This paper provides validation of the proposed schema on a major infrastructure project. The developed schema includes the categorisation of identified clashes based on stakeholder involvement and required actions. The validation used the estimated cost of clashes were those not resolved before site operations took place. This schema simplifies both the categorisation and cost estimation of clashes in design. Estimated savings yielded 20% of contract value using the schema, for the multi-million-dollar project case study, thus extending evidence of BIM savings and benefits. The schema improves the existing process and valorises clash detection, thus allowing stakeholders to conduct a cost-benefit analysis. In addition, the categorisation methodology allows prioritising on the most costly clashes, and draw lessons learnt for further projects. This schema opens the path towards a systematic methodology to appraise the benefits of different BIM uses or processes.

Given the global energy and environmental situation, the European Union has been issuing directives with increasingly demanding requirements in term of the energy efficiency in buildings. The international competition of sustainable houses, Solar Decathlon Europe (SDE), is aligned with these European objectives. SDE houses are low energy solar buildings that must reach the near to zero energy houses’ goal. In the 2012 edition, in order to emphasize its significance, the Energy Efficiency Contest was added. SDE houses’ interior comfort, functioning and energy performance is monitored. The monitoring data can give an idea about the efficiency of the houses. However, a jury comprised by international experts is responsible for carrying out the houses energy efficiency evaluation. Passive strategies and houses services are analyzed. Additionally, the jury's assessment has been compared with the behavior of the houses during the monitoring period. Comparative studies make emphasis on the energy aspects, houses functioning and their interior comfort. Conclusions include thoughts related with the evaluation process, the results of the comparative studies and suggestions for the next competitions

Demand response (DR) involves economic incentives aimed at balancing energy demand during critical demand periods. In doing so DR offers the potential to assist with grid balancing, integrate renewable energy generation and improve energy network security. Buildings account for roughly 40% of global energy consumption. Therefore, the potential for DR using building stock offers a largely untapped resource. Heating, ventilation and air conditioning (HVAC) systems provide one of the largest possible sources for DR in buildings. However, coordinating the real-time aggregated response of multiple HVAC units across large numbers of buildings and stakeholders poses a challenging problem. Leveraging upon the concepts of Industry 4.0, this paper presents a large-scale decentralized discrete optimization framework to address this problem. Specifically, the paper first focuses upon the real-time dispatch problem for individual HVAC units in the presence of a tertiary DR program. The dispatch problem is formulated as a non-linear constrained predictive control problem, and an efficient dynamic programming (DP) algorithm with fixed memory and computation time overheads is developed for its efficient solution in real-time on individual HVAC units. Subsequently, in order to coordinate dispatch among multiple HVAC units in parallel by a DR aggregator, a flexible and efficient allocation/reallocation DP algorithm is developed to extract the cost-optimal solution and generate dispatch instructions for individual units. Accurate baselining at individual unit and aggregated levels for post-settlement is considered as an integrated component of the presented algorithms. A number of calibrated simulation studies and practical experimental tests are described to verify and illustrate the performance of the proposed schemes. The results illustrate that the distributed optimization algorithm enables a scalable, flexible solution helping to deliver the provision of aggregated tertiary DR for HVAC systems for both aggregators and individual customers. The paper concludes with a discussion of future work.