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Data Science Intern at Alpiq

In the frame of the European Union sponsored project EDGEFLEX, Alpiq is looking for a MSc/PhD student/intern.

EDGEFLEX aims at favoring the integration of intermittent energies (solar, wind) into the electricity network, as well as making them more profitable for investors.

Among other optimization tasks under the responsibility of Alpiq, is the development of a novel wind forecasting model. The objective is to improve on the performance of the resulting forecasts with respect to traditional site-specific models, in the time span covering 1 to 6 hours before delivery.

This task set-up will consist in:

•    A cloud-based setup for the forecasting algorithms.
•    Connections using IoT to the wind parks to read their states in near real-time.
•    Reading weather variable measurements from weather stations spread out over large geographical areas (up to 500 km around a park) as well as measurements from devices installed within the park
•    Grid based weather forecasts covering that same geographical area.

Your main responsibilities
The main innovation in this task consists in setting up a neural network to perform the forecast itself. It shall articulate as follows:
•    This neural network will have to be specified, designed in a fashion that will maximize the potential outcome, with the help of previous Alpiq’s experience
•    Then trained with historical data from our german intermittent power plants.
•    Then it shall be tested, with the goal to be more accurate in its forecasting output than with traditional algorithms.
•    Ultimately, a comparison with the traditional site-specific forecasts will be performed and documented.
 

Your qualifications
•    MSc/PhD student with strong computer science education
•    Advanced knowledge in Machine learning - the deployment of neural networks
•    Genuine interest in decarbonized energy production is a plus
•    Strong analytical skills
•    English proficient

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by Tsutomu Narushima