Energia Group highlights possibilities of machine learning & AI in energy sector
As one of Ireland's leading renewable energy developers and suppliers of green electricity, Energia Group proudly employs numerous scientists working across various fields, from marine biology to data science.
11 November 2022: As one of Ireland's leading renewable energy developers and suppliers of green electricity, Energia Group proudly employs numerous scientists working across various fields, from marine biology to data science. Ahead of Science Week, which runs from the 13th to the 20th of November, Energia Group is celebrating the infinite possibilities and the role of science in the energy sector and how that contributes to Ireland's climate goals. Neil Mc Caul, Gregory Balogh and Anchit Bhagat are working together on an innovative artificial intelligence solution that can support energy traders in the decisions they make.
Neil Mc Caul, Energy Trading Development Manager with Energia Group has more than 15 years energy trading experience. He has seen first-hand how the rapid increase in digitalization plus the added complexity of many additional energy sources such as solar, increased levels of wind (both onshore & offshore) and battery storage has changed the energy trading industry. Commenting on the changes, Neil said, “The historical practice of trading by commercial intuition, supported by limited analytics, is being challenged by more data-driven, machine-based trading.”
Speaking about the innovative machine learning and trading project, Neil said, “The aim of the project is to develop a machine learning system to provide decision support and additional confidence to the trading team. It is about bringing together the skillsets of traders who have a deep and detailed understanding of the market with the insights data scientists can garner from machine learning and artificial intelligence.”
The project has been announced as a finalist the in 2022 AI Awards which will be held later this month. The project demonstrates the importance of collaboration between academia and industry.
Gregory Balogh recently graduated from Queens University Belfast with a Masters in Data Analytics and is currently a PhD candidate exploring the topic of explainable AI in Queens University. Gregory is a Data Scientist working on the Trading Development team and he is responsible for designing and building artificial intelligence solutions to support trading decisions.”
Speaking about what he enjoys most about his role, Gregory said, “I like the challenges, the people and most importantly, the fact that the energy market is very dynamic and complex. I love that I am working as part of a team creating innovative trading solutions.
Highlighting the variety of roles open to data scientists, Gregory said, “Data science is an incredibly interesting and broad field, the same techniques can be applied in any industry: marketing, finance, medicine, healthcare, manufacturing, and autonomous vehicles to name but a few. Data science can help humanity understand these industries even more by uncovering previously unseen patterns and correlations.”
Anchit Bhagat also recently graduated from Queens University Belfast with a Masters in Data Analytics. Anchit works as a Data Analyst alongside his colleagues Neil and Gregory on the Trading Development team. Speaking about his role, Anchit said, “The concept of bringing Machine Learning into trading is really exciting. Each day is challenging as you try to understand how factors like wind availability or energy demand across the island can play significant role in identifying market patterns. I really enjoy the collaborative aspect of my role working closely with energy traders and bringing my data insights to the table to enable strong trading decisions.
Speaking about what he enjoys most about working in Data Science, Anchit said, “Data Science is about converting lots of complex data into useful information and insights helping the business to make rational decisions and solve complex problems based on large volumes of data. With the help of data science, you can in a way predict the future based on historical experiences or events.”