Multi-objectives optimization of Energy Efficiency Measures in existing buildings

• Energy refurbishments of existing buildings through Energy Efficiency Measures on envelope and HVAC system.
• Use of Genetic Algorithm and dynamic simulation to investigate the retrofit best opportunities.
• Optimization of different objectives: Energy savings, Costs and Indoor thermal comfort.
• Relationship between initial characteristics of the buildings and the configuration of optimal solutions.

The enhancement of the energy performance of the existing buildings stock is nowadays a priority. To promote buildings energy renovation, the European Committee (2010) [1] asks Member States to define retrofit strategies finding cost-effective solutions. This so-called cost-optimal approach, described by the Commission Delegated Regulation EU (European Commission, 2012) [2], pursues a balance of energy and economic targets, but currently neglects some important aspects, such as indoor thermal comfort. This research investigates the relationship between the initial characteristics of residential buildings and the definition of optimal retrofit solutions in terms of either maximum economic performance, or energy consumption minimization towards nZEBs behaviour for the lowest achievable thermal discomfort. A multi-objective optimization has been carried out using a genetic algorithm (NSGA-II) coupled with a dynamic simulation tool. The results demonstrate that (i) with conventional Energy Efficiency Measures, it is possible to approach the zero energy target maintaining the economical convenience but worsening the indoor thermal comfort and that (ii) there is the necessity to introduce incentives to foster solutions not economically profitable, but more efficient in terms of energy savings and indoor thermal comfort.

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