Big Data Big Data analysis of household electricity use
Large amounts of data on household electricity use are becoming available with the widespread deployment of smart meters and adoption of smart electric devices by consumers. These data can be used by consumers to conserve energy or shift usage away from peak load times when it is most expensive. It also can be used by utilities to improve planning for capacity, peak use, and grid optimization.
This project uses data from the Pecan Street Institute in Austin, TX on electricity use by about 1200 households in several parts of Texas, as well as Colorado and California. The data is captured at one-minute and fifteen-minute intervals, and covers specific appliances (e.g., air conditioners, refrigerators, stoves) as well as electric vehicles (EVs) and rooftop solar systems where they are in use. The project team is cleaning, analyzing and visualizing the data using big data tools to look at issues such as:
1. Hourly, daily, and seasonal patterns of electricity use, and how those are related to weather and other factors.
2. The output of rooftop solar and how it is related to electricity usage.
3. How electricity costs would be affected under different pricing plans, and how consumers could participate in power markets by selling solar power, adjusting demand in response to price changes, and incorporating storage (including EV batteries).
4. Privacy and security issues associated with capturing, storing and sharing detailed energy data.
The project will advance knowledge of factors influencing energy usage, the potential value of household renewable energy, and the possible dynamics of distributed energy markets under different regulatory and pricing regimes.