The Power Forecasting Group (PFG) serves forecasts for 3.1 GW of renewable power generation in the Southwest United States, including 45 utility-scale photovoltaic (PV) systems. The PFG partners with regional utilities including TEP, APS, and SRP to provide power forecasts for the Western Energy Imbalance Market.
Patrick Bunn leads the PFG, and Leland Boeman is part of the team. Both are part of UArizona Hydrology & Atmospheric Sciences. Learn more about this project on the Power Forecasting website.
Current research topics for solar power include:
- Implementation of state of charge forecasts for co-located PV and Battery Energy Storage Systems.
- Improving sub-hourly Global Horizontal Irradiance forecasts using satellite image processing.
- Development of power forecasts for networks of residential rooftop PV based on zip code.
Possible Internship Focus Areas:
1. Data analysis to investigate historic forecast performance or real-time forecast issues.
2. Maintaining and improving forecast performance monitoring processes and forecast delivery
3. Verify design schematics for co-located PV and Battery Energy Storage Systems. Review and develop existing experimental forecast methodology for co-located PV-BESS.
4. Troubleshoot a data feed issue from an inverter located on UofA’s ENR2 building rooftop. There’s an issue with the ModBus card; either an issue with the UA private secured communication network or an inverter issue where ModBus points are not getting the correct values from the inverter point database.
Key Internship Requirements:
1. Must have experience with Python computer programming.
2. Familiarity with PV-BESS system designs.
Preferred Experience:
1. Experience with Python and scientific Python libraries (NumPy, SciPy, Pandas).
2. Experience with Git and GitHub, and an active GitHub account.
3. Familiarity with Docker, using MySQL and developing RESTful API endpoints.
4. Familiarity with data transmission from inverters.