Determining an Optimal Level of Power System Investments Under Large Scale Penetration of Solar Power in Saudi Arabia

Sammanfattning: The Saudi Arabia government set ambitious plans to adopt renewable energy sources in the energy mix as part of its strategy to diversify its economy away from oil. Ac- cording to the renewable energy project development office (REPDO), the total RES capacity installed would amount to 27.3 GW by 2023 and 58.7 GW by 2030.  Due to the geographic location of Saudi Arabia, solar energy is a promising renewable energy source. However, there are many challenges to achieving a future where so- lar generation represents a significant portion of the Saudi generation mix.  These concerns relate to the characteristics of solar PV (e.g., Variability, Aerosols, intermit- tency). As a result, measures should in place to take full advantage of the ambitiousplans.By modeling the generation of PV using real-time measurements, it is possible to quantify the potential energy produced (e.g., Power DC output from the PV panel). Also, through optimization techniques, it is possible to optimize future investments (e.g., capacity and transmission line investments) to minimize the costs while ensur- ing a reliable power system.  In this thesis, the model accounts for the variability in the hourly solar production for an entire year, by investing in the required capacity to meet the hourly demand and the necessary PV-operational reserves for multiple interconnected regions. Also, the model optimizes the investments over a given fu- ture growth in demand (electricity consumption) while accounting for the current generation mix, fuel prices, and PV deployment in each region.The model could be used to investigate multiple policies and their outcomes (e.g., fuel prices,  PV regional deployment,  PV capacity).   In this thesis,  two cases have been simulated based on the policymaker’s plans for adopting PV. The first case ex- amines 9.5 GW of installed PV capacity by 2023, while the second looks into 40 GW of installed PV capacity by 2030. The outcome is quantified by measuring the system costs and CO2 emissions.