Can photovoltaic systems' energy harvesting potential inform building design and retrofit decisions?

Ardeshir Mahdavi, Dawid Wolosiuk, Christiane Berger

Research output: Contribution to journalConference articlepeer-review

Abstract

Simulation methods can support both building design and building-integrated photovoltaic (PV) systems configuration. Related processes in this area typically start with a given building design, which is then considered in view of a fitting PV system configuration (i.e., type, size, orientation, local storage and/or grid export options). Simulation methods can specifically help with matching the temporal profiles of available solar energy and buildings' energy demand, which is especially relevant if a high level of energy self-sufficiency is targeted. However, the computational procedures in this area are rather one-way: Whereas relevant aspects of building designs (e.g., geometry and demand profile) inform the PV systems design, information on electricity generation potential via PV does not usually find its way back to building design decision making (e.g., building shape and orientation, transparent area fraction of the envelope, thermal mass). In this paper, we explore the potential of a bi-directional information flow between building design/retrofit decisions and PV system options. To this end, we illustrate how building design variables (e.g., orientation, glazing fraction) can be fine-tuned based on available PV system installation options. Thus, the proposed approach facilitates the exploration of the implications of PV-based energy generation options for building design decisions.

Original languageEnglish
Pages (from-to)1336-1342
Number of pages7
JournalBuilding Simulation Conference Proceedings
Volume18
DOIs
Publication statusPublished - 2023
Event18th IBPSA Conference on Building Simulation: BS 2023 - Shanghai, China
Duration: 4 Sept 20236 Sept 2023
https://bs2023.org/

ASJC Scopus subject areas

  • Building and Construction
  • Architecture
  • Modelling and Simulation
  • Computer Science Applications

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