It is clear that energy is changing, with renewable sources, decentralisation and smart grids disrupting how we think about, generate, and consume it.
In order to succeed in this changing environment, businesses need to embrace these changes, as well as the data they possess.
Data science related techniques, including artificial intelligence, machine learning, natural language processing and data mining, amongst many others, have the power to affect transformative change in small businesses.
Data that a company holds about itself may be able to provide a wealth of new insights and decision-making tools, and data science is the key to unlocking that new knowledge.
Data science has the power to:
- Forecast demand for power and heat
- Assess the characteristics and quality of materials
- Use open and public datasets to inform company decisions and operations
- Reduce fuel use by optimising routes of company vehicles
The Data Innovation Accelerator at Cardiff University helps SMEs in East Wales access the above information and more.
They offer the time and support of their data science team to give Small and Medium Sized Enterprises a detailed ‘data innovation health check’ or a collaborative project to tackle real challenges facing the business.
The DIA has been part-funded by the European Regional Development Fund through the Welsh Government with the aim of increasing the successful translation of research and innovation at Cardiff University into new and improved commercial products, processes and services.
“Data science can help companies to do things more efficiently and to minimise waste. This is really relevant as we move to a more sustainable energy system,” says Dimitra Mavridou, data scientist at the Data Innovation Accelerator.
“Data science tools can, for example, help companies to develop more eco-friendly and efficient practices, supporting compliance with environmental regulations or helping make financial savings.”
The DIA worked with a Cardiff based specialist technical consultancy, Sustainable Energy Ltd to build energy demand predictions using artificial intelligence time series forecasting techniques.
Accurate energy demand forecasting provides data for designing efficient decentralised energy networks, a vital element of the transition towards a more sustainable energy system and the fight against climate change.
Sustainable Energy Ltd provides independent consultancy in the renewable and low carbon energy sector and has been at the forefront of developing decentralised low carbon energy networks across the UK.
Part of their work requires the running of heat and electricity consumption models to predict energy demands in individual buildings. However, when assessing and designing solutions to decarbonise whole cities, these forecasts need to be accurate and able to quickly predict future trends for a range of different building types based on both a long term (daily consumption data) and short term (hourly consumption data) basis.
This was not previously available to Sustainable Energy and the development of an artificial intelligence model that would incorporate live monitored data, open data sets and meteorological data was identified as a solution for creating data sets for analysing and designing solutions for city wide decarbonisation.
In the project, Sustainable Energy provided data and knowledge and worked closely with the DIA to implement artificial intelligence into a smart energy model.
As part of Cardiff University’s Data Innovation Research Institute, the DIA also belongs to the School of Computer Science and Informatics, alongside initiatives including Supercomputing Wales, the National Software Academy and the Airbus Centre of Excellence in Cyber Security Analytics.
The DIA supports Small and Medium Sized Enterprises based in the local authorities of Cardiff, Flintshire, Monmouthshire, Newport, Powys, Wrexham, and the Vale of Glamorgan.
If you think your company could benefit from a data health check, contact the DIA on: [email protected] or 029225 11407.
The Data Innovation Accelerator is part-funded by the European Regional Development Fund through the Welsh Government