Yuliia Siur shares her experience in the Industrial Master's Programme in IT

Yuliia Siur graduated from the Computer Science Master’s Programme and completed the Industrial Master’s Programme in IT at the Institute of Computer Science. As a part of the programme, she spent 11 months working with Eesti Energia. The experience taught her a lot, and she was happy to share it with us. 

"When I started the Industrial Master's Programme in IT at Eesti Energia, I didn't have any experience in the energy sector. However, I was genuinely interested in it due to the growing focus on green energy. I chose a project to forecast the net consumption (difference in energy import and export) for Estonian prosumers who both produce (solar energy) and consume energy.

The Industrial Master’s Programme was incredibly beneficial for me. It ensured a balanced time distribution, so I had enough time with the company and for my classes. Having two supervisors—one from the university and one from the company—was also a great advantage. Their different perspectives, academic and business, helped me learn how to solve business problems with scientific solutions and find a balance between these two approaches.

While working on my thesis Prosumer Net Consumption Forecasting: The Impact of Behind-the-Meter Self-Consumption and Weather Forecast, I found an important but overlooked topic: the impact of on-site consumption, or self-consumption, of unmeasured solar energy, on forecasting energy import and export in prosumers. In my thesis, we evaluated existing methods and proposed a new approach to address this hidden self-consumption, showing our method's partial superiority.

In the research, I focused on the development of a day-ahead net consumption forecasting technique using data from Estonian prosumers. I presented additive and integrated models with various new features aimed at mitigating uncertainty arising from weather forecast variables and unmeasured self-consumption. The approach enabled models to efficiently capture complex relationships between input and target variables. The experimental results provided empirical evidence that the uncertainty arising from weather predictions and unmeasured self-consumption is improved in our consumption model developed for the additive method.

Moreover, I had the opportunity to present my work at the 44th International Symposium on Forecasting. My speech focused on exploring existing methods for net consumption forecasting, considering the impact of unmeasured self-consumption. I was amazed by the interest it caused. Discussions with specialists from various countries (Sweden, Turkey, Saudi Arabia, etc.) revealed that the influence of unmetered self-consumption is relevant not only in Estonia but globally.

Overall, joining the Industrial Master’s Programme in IT was one of my best decisions. It allowed me to work with Eesti Energia, gain deep insights into the energy sector from academic and business perspectives, and meet amazing people who supported my growth. I'm excited to continue developing as a Data Scientist in the energy sector, stay with Eesti Energia, and pursue my research as a hobby."

We are looking for companies to join the Industrial Master's Programme in IT as partners! Find more info on the programme. If interested, contact Mari-Anne Suurpere (mari-anne.suurpere@ut.ee).