Energy sustainability and environmental preservation have become worldwide concerns
with the many manifestations of climate change and the continually increasing demand for …

Big data analytics is the journey to turn data into insights for more informed business and
operational decisions. As the chemical engineering community is collecting more data …

This paper presents a recurrent neural network model to make medium-to-long term
predictions, ie time horizon of⩾ 1 week, of electricity consumption profiles in commercial and …

Energy storage can help integrate local renewable generation, however the best
deployment level for storage remains an open question. Using a data-driven approach, this …

There has been growing interest in using energy storage to capture solar energy for later
use in the home to reduce reliance on the traditional utility. However, few studies have …

Little is known about variations in electricity use at finely-resolved timescales, or the drivers
for those variations. Using measured electricity use data from 103 homes in Austin, TX, this …

Despite the rapid uptake of small-scale solar photovoltaic (PV) systems in recent years,
public availability of generation and load data at the household level remains very limited …

Residential air conditioning loads (ACLs) are promising demand response (DR) resources
with a certain flexibility and controllability that can enhance the operational flexibility and …

Advanced metering technologies coupled with informatics creates an opportunity to form
digital multi-utility service providers. These providers will be able to concurrently collect a …

Restructuring of power systems along with the integration of renewable energy resources in
electricity networks have transformed traditional distribution networks (DNs) into new active …