Novel statistical methods for opportunity detection in energy time series

This project seeks to develop novel statistical opportunity detection methods inspired by, and feeding back into, end user energy demand systems.

Due to contemporary sensor and IoT technologies, it is now possible to monitor energy usage across a range of devices and locations in real time. This provides an opportunity to synthesise data from numerous sources with a view to identifying different usage patterns, and thereby possible energy saving strategies. To achieve this, we will seek to develop novel methods to characterise such energy series, building on advances in changepoint detection, as well as other methods for detecting anomalous structures in signals. Where feasible, we will also seek to make generic software implementing such methods available in the form of reproducible software.