Master thesis: AI-Driven Peak Load Forecasting And Flexibility In Power Grids - Solvina
RejlersSweden2 days ago
Full-timeEducation, Training
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Are you approaching the end of your studies and it's time to write your thesis? Why not take the opportunity to do it at Solvina?
During the spring semester 2026, we at Solvina offer a thesis opportunity within AI-driven peak load forecasting and flexibility in power grids! ✨
ABOUT THE THESIS:
The electrification of transport and industry, combined with rapidly growing intermittent renewable generation, is transforming how distribution grids operate.
Operators face new challenges such as local capacity shortages, voltage fluctuations, and thermal overloads.
Artificial Intelligence (AI) and Machine Learning (ML) enable a new generation of predictive and adaptive tools for real-time grid forecasting and flexibility control, supporting a more resilient and efficient power grid.
Aim
To develop and evaluate an AI-based platform that combines machine learning and real-time grid data to deliver accurate peak load and reliability forecasts while optimizing power distribution and flexibility resources.
The system should identify patterns, predict demand peaks, with special focus on probabilistic forecasting and safe control of flexibility assets (e.g., batteries, demand response).
Suggested Tasks
We are looking for one or two master students in:
✔️Power system engineering
✔️Data science/Machine learning
✔️ Engineering physics
Or any other similar program.
You are analytical, curious, and eager to apply AI in energy system operations. You should have a strong interest in power systems. Proficiency in programming and data analysis is required.
Swedish or English is required.
What You Get
Welcome to Solvina and Rejlers - home of the learning minds! Together we are on an exciting journey of change with the common goal of building tomorrow's society
During your thesis we will offer you:
During the spring semester 2026, we at Solvina offer a thesis opportunity within AI-driven peak load forecasting and flexibility in power grids! ✨
ABOUT THE THESIS:
The electrification of transport and industry, combined with rapidly growing intermittent renewable generation, is transforming how distribution grids operate.
Operators face new challenges such as local capacity shortages, voltage fluctuations, and thermal overloads.
Artificial Intelligence (AI) and Machine Learning (ML) enable a new generation of predictive and adaptive tools for real-time grid forecasting and flexibility control, supporting a more resilient and efficient power grid.
Aim
To develop and evaluate an AI-based platform that combines machine learning and real-time grid data to deliver accurate peak load and reliability forecasts while optimizing power distribution and flexibility resources.
The system should identify patterns, predict demand peaks, with special focus on probabilistic forecasting and safe control of flexibility assets (e.g., batteries, demand response).
Suggested Tasks
- Collect and analyse real or simulated grid data (load, weather, voltage, generation)
- Develop ML-based forecasting models for peak load and reliability indicators
- Evaluate performance against real grid data.
We are looking for one or two master students in:
✔️Power system engineering
✔️Data science/Machine learning
✔️ Engineering physics
Or any other similar program.
You are analytical, curious, and eager to apply AI in energy system operations. You should have a strong interest in power systems. Proficiency in programming and data analysis is required.
Swedish or English is required.
What You Get
Welcome to Solvina and Rejlers - home of the learning minds! Together we are on an exciting journey of change with the common goal of building tomorrow's society
During your thesis we will offer you:
- Supervision by experts at Solvina
- Possibility to access real industrial datasets and collaboration with grid operators
- Possibility to publish and present your work at industry seminars
Key Skills
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