Long term power production planning involves resolving a comprehensive market model with power consumers, producers, and transmission lines, down to the individual reservoirs and hydro power stations and pumps in coupled water courses. This is done by running simulation software that outputs a fairly large amount of data in the range of 15 - 20 GB each time a simulation is run.
We have helped building an analysis platform for this problem that contains a domain model in which simulation results are inserted after they are computed. Furthermore, we have developed advanced techniques for retrieving and visualizing the results in terms of time series data and statistics, along with advanced aggregation of results to allow forecasts to be viewed in ways earlier not feasible.
Diako holds a Ph.D. in Computational Mathematics from the University of Oslo. As a student at both Mathematics and Physics departments at the University of Oslo, he has acquired a broad knowledge in various physical and mathematical theories, and numerical methods.
Roar has a master’s degree in High Energy Physics from the University of Oslo, completed in 2018. In his thesis he studied two different models of particle production at high energies, one statistical using the thermodynamical equations and one using the properties of a theoretical particle called Pomeron.