Issue |
E3S Web Conf.
Volume 238, 2021
100RES 2020 – Applied Energy Symposium (ICAE), 100% RENEWABLE: Strategies, Technologies and Challenges for a Fossil Free Future
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Article Number | 06001 | |
Number of page(s) | 7 | |
Section | Renewable Energies in Buildings | |
DOI | https://doi.org/10.1051/e3sconf/202123806001 | |
Published online | 16 February 2021 |
Optimal investment in the energy system of Zero Emission Neighborhoods considering the refurbishment of the building stock
NTNU, Department for Electric Power Engineering, 7491 Trondheim, Norway
* Corresponding author: dimitri.q.a.pinel@ntnu.no
To increase the impact that Zero Emission Neighbourhoods (ZEN) can have in the effort to decrease CO2 emissions, the refurbishment of the existing building stock is a parameter that should be considered. The existing literature contains work on optimization models for the energy system of neighbourhoods taking into account emissions but fails to account for the refurbishment of buildings. This paper addresses this option and presents an optimization model for designing a cost-optimal energy system of a ZEN in the context of existing buildings. The model is presented and used in a case study in Norway and compared to a case with linearized binaries. A sensitivity analysis is performed on the cost of refurbishment. With the original refurbishment cost assumptions, it is not chosen by the optimization, contrary to the hydronic. The system relies mainly on PV, solar thermal collectors (ST), a biogas engine, a battery and heat pumps (HP) and heat storage. From 50% of the original refurbishment cost, it is chosen, and the system does not have a biogas engine and a heating grid anymore, but a much bigger battery and more heating technologies inside the buildings. With linearized binaries, the investments are similar to the case with 50% refurbishment cost, but the value of the linearized binaries cannot be used to indicate the share of building to refurbish.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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