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 (ie, 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 (eg, 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 (eg, 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 (eg, 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 language | English |
|---|---|
| Title of host publication | Proceedings of the 18th IBPSA International Conference and Exhibition Building Simulation (BS 2023) |
| Publication status | Published - 2023 |
| Event | 18th IBPSA Conference on Building Simulation: BS 2023 - Shanghai, China Duration: 4 Sept 2023 → 6 Sept 2023 https://bs2023.org/ |
Conference
| Conference | 18th IBPSA Conference on Building Simulation |
|---|---|
| Country/Territory | China |
| City | Shanghai |
| Period | 4/09/23 → 6/09/23 |
| Internet address |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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