Residential photovoltaic (PV) solar systems are a growing part of the energy mix, but these systems are often poorly designed, deployed, and managed. They generate a significant amount of data that could be used to help drive improvements, but this data generally is not being used effectively today.
A key to improving residential solar system deployments is to enable to installers and homeowners to better visualize and understand how well their systems are performing and how they can be improved. Some questions that could be answered with the data that is readily available include:
The primary data source for this project is time-series sample data generated by one or more local solar installations. I have developed a server application that cleans, synchronizes, and transforms the raw data to make it more useful. The content, format, and location of the processed data is described here: SPA Data Flow.
The server application generates two data files, a "Daily Data File" and a "Trend Data File". The SPA Data Flow document provides links to both files. The "Trend Data File" is the easiest to work with and should be the focus of this project.