Helsinki Energy Demand Prediction
This project aims to predict aggregate electricity demand from a selected list of locations in the City of Helsinki by using the 3 leading methods: a classical Box-Jenkins model, a Deep Learning Neural Network, and a Facebook Prophet model.
The project itself is divided into 2 parts. The first one is about predicting daily electricity demand using the first 2 models. The second part use Facebook Prophet to do forecasting on hourly demand.
The data is fetched from the Nuuka open API, courtesy of Avoindata.fi. You can visit our Medium article here, or the project website here.
Authors: Bruce Nguyen and Son Le.