Public defence in the field of Systems and Operations Research, M.Sc. (Tech) Tuomas Rintamäki

Title of the thesis: Optimization and time-series models for large-scale integration of variable renewable energy sources

Thesis defender: Tuomas Rintamäki
Opponent: Professor Ramteen Sioshansi, Carnegie Mellon University, US
Custos: Professor Ahti Salo, Aalto University School of Science, Department of Mathematics and Systems Analysis

Traditionally, power systems have consisted of predictable loads and controllable generation sources. Global goals to reduce emissions have motivated the large-scale introduction of variable renewable energy sources (VRES) in these systems. VRES such as wind and solar power are less predictable, controllable, and have low marginal costs. Consequently, the large-scale deployment of VRES affects the adequacy and flexibility requirements of power systems and the pricing of electricity in day-ahead and intraday markets.

This Dissertation develops optimization and time-series models to answer research questions related to the large-scale integration of VRES in power markets. We build on power system data to implement time-series models to estimate the impact of wind and solar power on power prices in the Nordic and Northwestern European regions. Moreover, we develop three mathematical optimization models: (i) a model to optimize capacity payments to flexible conventional generation to reduce balancing costs due to the variability of VRES; (ii) a model to optimize the day-ahead and intraday offerings of a flexible generator in the presence of VRES; (iii) a model for long-term generation and transmission expansion to meet emission-reduction targets while considering uncertain demand and VRES.

The main contributions of this Dissertation are as follows. First, the time-series and optimization models expand on the state-of-the-art by accounting for new features, such as intraday market dispatch. Second, we develop methods to solve the optimization problems efficiently and accurately. Third, we gain insights into a long-term transmission and generation expansion plans that help meet emission-reduction goals and estimates about the impact of wind and solar power on day-ahead prices, for instance. Such insights support the design of more effective policies for VRES integration and inform producers and consumers alike on the impact of VRES. The results of the Dissertation have been exploited by other researchers in estimating the impact of VRES in other regions, for example.

Keywords: optimization, time-series models, game theory, renewable energy, power systems

Thesis available for public display 10 days prior to the defence at Aaltodoc. 

Contact information: tuomas.rintamaki@aalto.fi