Liam Pereira's dissertation dataset contains synthetic photovoltaic and load data for one year at hourly frequency. The photovoltaic dataset includes irradiance, solar positional angles, and cloud cover, while the load dataset includes baseline averages and stochastic noise. A separate search space dataset explores combinations of PV and battery sizes with fitness evaluations.
Use Cases
- Simulating Energy Management System (EMS) behavior based on synthetic hourly load averages and stochastic noise.
- Optimizing photovoltaic and battery size combinations based on the fitness values in the explored search space.
- Analyzing solar energy potential based on synthetic irradiance, solar declination, altitude, and azimuth angle data.
- Modeling load profiles shaped by seasonal factors and temperature, as described in the dissertation.
Strengths
- Contains one year of hourly data for both photovoltaic and load simulations.
- Photovoltaic dataset includes multiple solar positional angles (declination, altitude, azimuth) and cloud cover percentages.
- Load dataset incorporates stochastic noise simulation and seasonal/temperature shaping factors.
- Optimization search space explicitly includes PV size, battery size, and fitness value columns.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Data is synthetic, generated for a specific dissertation, and may not reflect real-world conditions.
Provenance
- Source
- Liam Pereira via figshare
- Collection Method
- Synthetic generation and simulation for a dissertation.
- Time Range
- One year of hourly data.
- Freshness
- Last updated 2026-05-25 12:58:39; freshness should be verified.