Resources
Title:
SPAGHETTI: A Synthetic Data Generator for post-Covid Electric Vehicle Usage
Author:
Anaïs-Marie Celestine Berkes, EEG Group, PhD student and Gates Scholar in the Department of Computer Science and Technology at the University of Cambridge.
Description:
SPAGHETTI (Synthetic Patterns & Activity Generator for Home-Energy & Tomorrow’s Transportation Investigation) is a tool that can be used for the synthetic generation of realistic EV drive cycles. It takes as input EV user commuting and non-commuting patterns, allowing for personalised modeling of EV usage. It is based on a thorough literature survey on post-Covid work-from-home (WFH) patterns and can also be used to model the EV usage patterns of the three most common types of post-Covid workers. SPAGHETTI can be used by the scientific community to conduct further research on the large-scale adoption of EVs and their integration into domestic microgrids.
Please click on the link for more details.
Title:
Heatalyzer: A Tool for Evaluating Indoor Comfort in Buildings during Extreme Heat Events
Author:
Livia Capol, Master’s student in Computer Science at ETH Zurich and Visiting Student at the Department of Computer Science and Technology at the University of Cambridge
Description:
The increase in heatwaves due to climate change poses significant challenges to both indoor thermal comfort and occupant well-being. Unfortunately, existing work does not quantify the impact of extreme heat events as a function of building type, occupant age, and heatwave intensity and duration. We therefore present Heatalyzer, a novel Building Energy Modeling (BEM) tool to analyze indoor thermal comfort, liveability, and survivability for a range of buildings under both past and future weather scenarios. It lets users compare these outcomes across building types and weather scenarios, integrates algorithms for creating extreme weather data, and has a user-friendly interface. Additionally, it outputs several commonly used thermal comfort metrics, which are crucial for evaluating indoor conditions during heatwaves. These functionalities enable a wide audience, including building managers and policymakers, to assess the impact of extreme heat events on building occupants.
Please click on the link for more details.
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