This GitHub repository is the main point of access for students and lecturers of the ZZSC9020 capstone course.
In this repository, you will find the data to start developing your project. Also, we will use the repository to share code, documentation, data, models and other resources between the group members and course lecturers.
Complete the information below regarding your group.
- Chadi Abi Fadel (z5442788) - Software Development
- Joshua Evans (z5409600) - Report Writer / communication specialist
- Bernard Lo (z3464235) - Data Analyst
- Andrew Ryan (z2251397) - Project Manager
How does the integration of renewable energy features affect electricity demand forecasting accuracy. Specifically does including the features, 'solar generation capacity' (domestic and residential), and 'solar radiation' improve the forecasting accuracy of electricity demand compared with just using temperature alone. In effect, we will attempt to conduct the below hypothesis test for a number of different modelling approaches.
- Null Hypothesis: Temperature data alone is sufficient to reliably forecast electricity demand
- Alternative Hypothesis: Including the additional features of 'solar generation capacity' and/or 'solar radiation' improves the estimate of electricity demand
The repository has the following folder structure:
- agendas: agendas for each weekly meeting with lecturers (left 24h before the next meeting)
- checklists: teamwork checklist or a link to an account in a project task management tool
- data: datasets for analysis
- gantt_chart: Gantt chart or a link to an account in a project task management tool
- minutes: minutes for each meeting (left not more than 24h after the corresponding meeting)
- report: RMarkdown or Jupyter notebook report in progress
- src: source code