This project focuses on getting the most savings from installing batteries alongside solar panels for homes. During certain times of the day, solar panels can produce more than the home consumes. When this happens, the excess energy can be sold back to the utility to offset some cost of energy that the homeowner buys from the grid. For utilities that provide time-of-use rates, the same unit of energy is worth more or less depending on when it is bought from or sold to the grid. By using batteries, that energy can be time-shifted to be the most financially beneficial to the homeowner.  

The objectives of this project were to create a program to minimize electrical utility costs based on storage capacity, pricing structure, and generation + consumption for a given time period; build forecast models of how a given home would generate and consume energy; combine the optimizer and forecasts to build a tool that could recommend how to use batteries to maximize savings; and compare the predictive optimizer performance against other methods for controlling the battery.