The PhD candidate should have Msc degree and great skills in machine learning relevant to the problem.
The candidate should
Input:
actual production timeseries, current effect, weather forecast and weather history, precipitation and temperature, snow melting, impact field and earth conditions.
Output:
12-36 hours ahead from 1300 day x-1 through day x, continually rerun prediction of production for all available hours day x, upto intraday market close D-60 (60 minutes before delivery).
Goal 2: Predicting prices:
Input:
Weather Norway and Europe; Anticipated demand versus supply; Volume of volatile production (wind, run-off river)
Current and historical spot prices; Current and historical intraday prices; Current and historical regulating prices
Output:
How likely is intraday to be different from spot (day ahead)?
How likely is regulating prices to be different from spot?
In what direction is it most likely to go (up-regulation or down-regulation)?
Salary: 562 500 Krone/Year; three years.
PhD Program: PhD in Process, Energy, and Automation Engineering (PEAE) at USN, link. Academic background : “Applicants must hold a Master of Science degree relevant to our research projects.”
Supervisor: Prof. Dieu Tien Bui, University of South-Eastern Norway