Estimating Energy Consumption for a Building Using Dilated Convolutional Neural Networks

Certain examples described herein relate to systems and methods for estimating energy consumption data for a building. A system () for estimating an energy use of a building uses a dilated convolutional neural network architecture () to receive time-series data () for the building and to predict one or more time-series data points () representing an estimated energy consumption for the building. A method for estimating an energy use of a building includes obtaining time-series data for the building, providing the time-series data as input to a dilated convolutional neural network architecture, and predicting one or more time-series data points representing an estimated energy consumption for the building using the dilated convolutional neural network architecture. The systems and methods may be used to help users and building controllers reduce energy use within a building.