Company Name:

Rebase Energy

Incubation Round:

Explore, Experiment, Evolve

Application Track:

Track 1

Proposed by:


Data Provider:


Challenge Name:

Smart open-source agents for buildings optimisation

Product Description

Datahub: Provides through an API weather, asset and market data tailored for the energy industry in an “AI ready” format. Data can be directly consumed by machine learning algorithms to forecast for example energy supply and demand.

Toolkit: Provides tools to process data from the Datahub for applications within energy forecasting and optimisation. Our toolkit is open source and includes integrations with several useful datasets and computation tools for forecasting and optimization. This allows users to develop their own machine learning algorithms at speed and deploy them at scale in just a few clicks.

Rebase Energy is an API-first company. Everything can be accessed through APIs.

More specifically, Rebase Energy enables data interoperability through adoption of RESTful API design and OpenAPI standard (in progress).

Rebase Energy has contributed and is conforming to the standards for energy forecastings developed by the IEA Wind Task 36 on Wind Power Forecasting. In the future, more sector-specific standards are planned to be adhered especially within energy modelling for buildings.

Here are a couple of APIs that Rebase Energy has built:

Reach Timeline

*Expose phase is open to all Experiment phase teams






Company maturity:

Live funding and product-market fit

Investment level:


Funding raised:

< EUR 100,000

Collaboration opportunity:

Company Description

Rebase Energy was founded in 2018 by Sebastian Haglund El Gaidi and Mihai Chiru. The main company hypothesis came from Sebastian who previously worked with power trading in a big utility company and saw a need to improve the way data is used in managing and operating the power system. This is an increasingly important problem in tomorrow’s highly complex energy system based on distributed and intermittent energy resources. Rebase Energy is now a team of 6 people with strong backgrounds and expertise in energy and data science from both the industry and academia.
  • IEA Wind Task 36 on Wind Power Forecasting
  • FIWARE Accelerate
  • Linux Foundation Energy (in progress)

Sebastian Haglund El Gaidi

Sebastian holds a Master of Science from Royal Institute of Technology in Energy Engineering. During his studies he worked with an energy visualisation startup in Stockholm, a solar panel installer in Madagascar and a wind farm developer in France. Sebastian has experience in energy markets from working with a large utility company in the Nordics.

Mihai Chiru

Mihai holds a Master of Science from Royal Institute of Technology in Distributed Systems. He has worked more than 10 years in the energy industry as a IT and data science consultant for several utility companies. Mihai was the winner of the prestigious KDD cup in 2016, which is a world known machine learning competition.

Ilias Dimoulkas

Ilias is currently pursuing his PhD in the department of Electric Power and Energy Systems at KTH. His research work involves optimization and forecasting techniques in the power systems. He and his team obtained a second position in the wind power forecasting competition organized by the International Conference on the European Energy Market 2017. Before Ilias started his PhD, he worked with performing calculations and installation of PV systems in Greece.

Henrik Kälvegren

Henrik holds a Bachelor in Computer Science from Royal Institute of Technology. Before joining the Rebase Team, Henrik worked as a student consultant in a full stack development project. Henrik thrives in creating products that are accessible and intuitive to the end-customer. He knows the importance of building a user experience that both solves the users’ everyday problems, as well as being easy to grasp and understand.

Velibor Zeli

Velibor is the team weather expert. He knows a lot about the physical processes governing the dynamics of the atmosphere. Velibor is currently a PhD. student at the Fluid Dynamics department at KTH. His research is in understanding and developing turbulence models for the atmospheric boundary layer.

Addis Moiteaux

Addis has an energy background with experience working in the Silicon Valley with a large energy utility fostering innovation and collaboration with startups and with a Stockholm-based startup that provides energy solutions to real-estate owners and connects their energy assets to help balance the electricity grid.