The goal of the project was to predict real-time electricity market prices accurately. The researchers developed a new model called GFNARX, which showed comparable accuracy to existing models but was more cost-effective. By using this model to predict prices, a 25.5% reduction in electricity costs was achieved compared to buying all electricity on the day ahead market. This shows that predicting real-time prices can help reduce electricity costs for assets.