Smart Senja electrical network expansion modeling

• Main Author: Marthinussen, Oskar
• Format: Master Thesis
• Language: English
• Published: UiT The Arctic University of Norway 2023
• Subjects: mathematical optimization; network expansion; GenX; smart grid; island operation; renewable energy; EOM-3901; Norway; Senja; Northern Norway
• Online Access: https://hdl.handle.net/10037/30229

The addition of variable renewable energy sources into the electrical energy systems of the world has been increasing in recent years. This form of distributed energy production with high production volatility can introduce massive challenges in operating a lower voltage distribution network. One of these affected networks is on the island of Senja in northern Norway, with an eldering radial electrical network with a single connection to the national transmission grid. In this study, prescriptive analysis of the network through mathematical optimization is implemented to investigate if there are more effective solutions to this problem other than building more electrical lines. In selected parts of the island, the electrical network experiences electrical faults of different magnitude and concern affecting 1500 hours a year. In this thesis, the model GenX is presented which prescribes solutions reducing these faults to zero while also cutting costs compared to the baseline scenario of today’s system. Results from the model indicate that simple installments of distributed power generation in conjunction with electrical energy storage drastically improve network capacity and industrial expansion opportunities. Also investigated is the feasibility of operating the electrical network on the island without any connection to the external grid. Meant as a proof of concept for the application of mathematical optimization on electrical grids in other more remote parts of the world. The model proves that investments in local electricity production positively impact the system at a fraction of the cost of building new regional distribution infrastructure. Finally, some drawbacks of the chosen analytical tool used to construct the mathematical optimization model are presented alongside selected methods applicable to apprehend or circumvent these limitations.