Master & SIE Projects

Description:

An energy model called OREES has been developed within our team to find the best locations of future renewable energies in Switzerland. This model uses as inputs the transmission (high voltage) grid, the electricity demand on the nodes of the network, and also weather data. This latter is used to estimate the production from dispatchable resources and non-dispatchable resources such as hydropower or the solar panels and the wind turbines, respectively. Our current scenarios are based on the use of past or future weather data, however the increase in compound events (e.g. low wind and radiation over long periods) have not been specifically investigated in those scenarios. These compound events can have a major impact on the plants and the demand; thus, this project consists in evaluating the economic cost of such effects and how it affects the optimization of the future renewable energies dispatch. The first step of this project involves the building and pre-processing of a compound events database by the student. In a second stage, this database with be used in the energy model. Then the results of this energy model will be analyzed to finally estimate the cost and impact of compound events on the Swiss electricity system.

Goals:

Evaluate the effects of compound events on the Swiss energy system using an optimization model for the electricity system.

Benefits:

• Getting familiar with electricity system and its challenges;
• Learn data gathering and processing methods;
• Getting the basic knowledge of optimization models;
• Generate a meaningful result in the context of the Swiss energy transition.

Required:

• Working autonomously with help from the supervisors;
• Basic knowledge on climate change trends and statistics;
• Basic use of python.