The poor condition of Italian schools has a chance for renovation thanks to climate policies aimed at limiting building consumption. Hence, defining effective retrofit strategies becomes vital, not only in the current but also in future climate scenarios. The aim of this work is to evaluate and optimize retrofit strategies for a school located in the Mediterranean area, considering both current and future weather scenarios, in terms of retrofit effectiveness and costs implications. Starting from the values set for the reference building proposed by the Italian law, a set of retrofit strategies was identified, considering envelope and systems alternatives. Then, a life cycle cost analysis has been performed for each possible alternative strategy to identify the optimal set of interventions. To this end, a single-objective optimization has been performed by coupling Energy Plus and Python, with the aim of minimizing the global investment cost, considering a time frame of 30 years. To simulate the climatic conditions variation, 11 years were simulated using an epw file representative of current climate (TMY) and the remaining 19 using an epw representative of future climate (2050), created using the morphing method based on the latest SSP5-8.5 scenario.

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School Energy Retrofit in a Changing Climate: Optimization of Retrofit Strategies and Cost Implications

  • Ludovica Maria Campagna,
  • Francesco Carlucci,
  • Francesco Fiorito

摘要

The poor condition of Italian schools has a chance for renovation thanks to climate policies aimed at limiting building consumption. Hence, defining effective retrofit strategies becomes vital, not only in the current but also in future climate scenarios. The aim of this work is to evaluate and optimize retrofit strategies for a school located in the Mediterranean area, considering both current and future weather scenarios, in terms of retrofit effectiveness and costs implications. Starting from the values set for the reference building proposed by the Italian law, a set of retrofit strategies was identified, considering envelope and systems alternatives. Then, a life cycle cost analysis has been performed for each possible alternative strategy to identify the optimal set of interventions. To this end, a single-objective optimization has been performed by coupling Energy Plus and Python, with the aim of minimizing the global investment cost, considering a time frame of 30 years. To simulate the climatic conditions variation, 11 years were simulated using an epw file representative of current climate (TMY) and the remaining 19 using an epw representative of future climate (2050), created using the morphing method based on the latest SSP5-8.5 scenario.