Abstract

In the last three decades, deep energy retrofit measures have been the standard option to improve the existing Danish building stock performance, with conventional techniques including envelope constructions insulation, windows change and lights replacement. While such techniques have demonstrated large technical and economic benefits, they may not be the optimal solution for every building retrofit case. With the advancement in the field of smart buildings and building automation systems, new energy performance improvement measures have emerged aiming to enhance the building intelligence quotient. In this paper, a technical evaluation and assessment of the trade-off between implementing deep energy retrofit techniques and improving building intelligence measures is provided. The assessment is driven by energy simulations of a detailed dynamic energy performance model developed in EnergyPlus. A 2500 m2 university building in Denmark is considered as a case study, where a holistic energy model was developed and calibrated using actual data. Different performance improvement measures are implemented and assessed. Standard deep energy retrofit measures are considered, where the building intelligence improvement measures are in compliance with the European Standard EN 15232 recommendations. The overall assessment and evaluation results will serve as recommendations aiding the decision to retrofit the building and improve the performance.

Highlights

  • When it comes to the building sector, Denmark is not an exception as the building block contributes to a substantial 40% of the overall energy consumption share with an equivalent contribution in terms of greenhouse gas emissions [1]

  • A 2500 m2 university building is considered as a case study in this work to evaluate and assess the trade-off between deep energy retrofit and improving building intelligence

  • Based on the results reported, it is clear that there is a large variation in the impact of each improvement measure on both the heating and electricity profile of the MMMI building

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Summary

Introduction

When it comes to the building sector, Denmark is not an exception as the building block contributes to a substantial 40% of the overall energy consumption share with an equivalent contribution in terms of greenhouse gas emissions [1]. There is an absence of a systematic methodology aiding the building’s retrofit decision-making In this context, the Danish government has realized the potential of improving the overall energy performance of exiting buildings and has launched recently a comprehensive strategy: “Strategy for the energy renovation of the existing building stock” [5]. Implementing the proposed retrofit package resulted in reducing the primary energy use of the school from 200 to 75 kWh/m2 considering both heating and electricity Another recent investigation by Jradi et al [9] proposed a systematic approach for building energy retrofitting using dynamic energy performance models. This is accompanied by saving 5.1 tons on the annual CO2 emissions along with a 4 years payback period

Deep Energy Retrofit vs Improving Building Intelligence
Case Study Building
Building Energy Modelling and Simulation
Energy Retrofit Measures
Results and Discussion
Conclusion
Energy Policy Toolkit on Energy Efficiency in New
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