The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/17129420

Ekici, Berk; Turkcan, Okan F.S.F.; Turrin, Michela; Sariyildiz, I. Sevil; Tasgetiren, Mehmet Fatih (2021): Multi-zone simulation results of Europoint complex for self-sufficiency in energy consumption and food production in Rotterdam. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/17129420.v1

Dataset

• Engineering Design
• Design Practice and Management
• Building
• Other Built Environment and Design
• Architecture

Artificial Intelligence (AI), BIPV, Building Performance Simulation (BPS), Building-integrated photovoltaics;, Computational Optimisation, energy consumption, machine Learning Predictions, Self-sufficiency, Vertical Farming

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CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Berk Ekici , Okan F.S.F. Turkcan , Michela Turrin , I. Sevil Sariyildiz , Mehmet Fatih Tasgetiren

The research focuses on optimising different zones of the Europoint complex in Rotterdam to achieve self-sufficiency in energy consumption and food production. For this reason, three buildings of the complex are parametrised in Grasshopper 3d Algorithmic Modelling Environment. The parametric models include various design variables related to the number of farming floors, shape, and the properties of the façade design with shading devices. Residential parts of the towers are divided into 3 subdivisions (building zones) to identify the best parameter sets for various floor levels considering the density of the surrounding. In each building zone, 1 floor level is considered to conduct the simulation results that corresponds to data collection from 9 different floor levels of the Europoint complex. Latin Hypercube Sampling method is used with Honeybee and Ladybug plug-ins developed for environmental analysis in Grasshopper during the sampling process. The collected data presents the results for residential energy consumption including heating, lighting, and equipment loads, energy generation of the towers, and daylight factor for each orientation in each zone. Detailed explanations of the design parameters, performance aspects, and glazing types are given in below. The published data can be used for sensitivity analysis, surrogate modelling, and statistical analysis for energy and daylight related works on Europoint complex in Rotterdam.

• 2021-12-14 first online, published, posted

4TU.ResearchData

pdf, csv

TU Delft, Faculty of Architecture and the Built Environment, Chair of Design Informatics
TU Delft, Faculty of Architecture and the Built Environment, Department of Architecture
Auburn University, Department of Industrial and Systems Engineering