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Energy consumption in buildings is a key factor when accomplishing national and global CO 2 emission goals. The economic savings per building are limited and are difficult to argue. However, the efforts can be aggregated on district or city level: the approach described in this paper is a large scale co-simulation environment that helps to leverage efficiency by providing quantitative information about the efficiency impact on large scale, while minimizing the efforts in modeling single buildings. It addresses the challenge of modeling thermal behavior of a large neighborhood of buildings in order to calculate energy demands, regarding weather conditions, shading and room temperature settings with a time resolution below one hour. A proof of concept applies the method to a demonstration site of residential buildings and shows the heating demand and CO 2 footprint of the neighborhood. [ABSTRACT FROM AUTHOR]

The recast version of the Energy Performance of Buildings Directive (2010/31/EU) proposes a comparative methodology aimed at defining the energy performance of buildings “with a view to achieving cost-optimal levels”. Really, how can the cost-optimal technologies be detected? Moreover, how can the most proper packages of energy efficiency measures be chosen in order to obtain the cost-optimality? This paper would provide answers to these questions, by proposing a new methodology for the evaluation of the cost-optimality, by means of the multi-objective optimization of energy performance of buildings and indoor thermal comfort. The optimization procedure is developed by means of the coupling between MatLab and EnergyPlus, by implementing a genetic algorithm, and it allows the evaluation of profitable and feasible packages of energy efficiency measures applied to buildings. Then, following the adoption of these packages, the global cost over the lifecycle of the building is calculated, in order to identify the cost-optimal solution. After the presentation of the methodology, the developed method is proposed for the optimization of the energy retrofit of an existing building. Furthermore, the method can be applied also for new architectures, by considering reference buildings. [ABSTRACT FROM AUTHOR]