Energy Analytics

As ever more data is being created by the power sector, a question of huge importance is how do we use this data and what other value (social, environmental and monetary!) does it offer? At present, this remains an open question and as a result the analysis of this data is an exciting area in energy research.

Our research into the energy system employs data analytics in a number of areas. Ultimately, the common goal for our data analytics in the energy sector is to use data generated by the power sector to enhance the sustainability, cost-effectiveness or reliability of the power network. Specific applications of analytics in our research include operation planning, energy markets, renewable energy integration, data visualisation and education. For example, we have investigated the ability of mobile phone data to enhance large scale building energy models, since ultimately the occupants in those buildings are the drivers of the energy use. This is crucial in planning the development of new urban areas or retrofitting in existing urban buildings. We have also looked at the economic case for PV and battery systems for residential consumers, identifying which consumers may be better suited for these types of energy efficiency measures and examining the economic arguments.

Our research in this area is built on a broad understanding of energy systems and their operation, statistics, machine learning, programming and energy use across multiple vectors and sectors. We are always interested in new projects in this area, which has a strong crossover with the areas of energy forecasting and energy system modelling.