Investment and Operation Co-Optimization of Integrating The Regional Plans of The Netherlands at High Spatial and Temporal Resolution

Abstract

Energy transition goals to reduce carbon emissions are a driver key for an increase share of variable renewable energy sources (vRES). To achieve 49% of CO2 reduction by 2030 compared to 1990, the Netherlands set a plan to generate 84 TWh of electricity from renewable energy sources, where 35 TWh need to be generated exclusively from onshore renewable energy sources (large -scale solar PV and wind onshore). Since large renewable energy projects require inter-municipal decision-making rather than a decision-making at a local level, the Netherlands introduced an instrument called regional energy strategy (RES) in the climate agreement. RES consists of dividing the country into thirty regions,
in where each region needs to identify the necessary installed capacity of vRES and storage units along with the necessary investments in the grid. So far, the energy regions set their vRES plans, where 26 TWh of electricity generation from large-scale solar PV and wind onshore is expected. The regional transition entails many uncertainties. On one side, the electrification of different sectors such as industry and transport will lead to an increase in electricity demand. On the other side, the electricity grid has reached it’s maximum capacity in some regions. Therefore, the vRES plans (large-scale solar PV) set by the energy regions might not be achieved as planned. Therefore, in order to implement the energy region’s plans into the Dutch power system optimally, uncertainties in electricity supply and demand need to be taken into account. The approach adopted in this thesis consists first of the modelling of the Dutch power system as a thirty-region power system reflecting both the electricity grid and the energy regions. Second, developing a high spatio-temporal resolution electricity supply and demand profiles. Third, creating different scenarios to capture uncertainty in electricity supply and demand, where a two-phase scenario planning is developed. Generation type and capacity uncertainty (achievement of 50% and 100% of large-scale planned solar PV projects by the energy regions) are presented in the first phase and the allocation of the installed capacities to segments of two different electricity load shapes (medium growth and high growth) as a second phase decision. Last, optimizing the investment costs in generation and transmission expansion with energy storage units under the different scenarios. The optimization problem is formulated as a two-stage optimization problem. In the first stage, the investment costs in energy storage units along with the transmission lines to incorporate the 26 TWh planned electricity generation are minimized under the different scenarios in electricity supply and demand. In the second stage, the outcomes of the first optimization problem (the required energy storage and transmission lines capacities) are used as input in the second optimization problem, where the investment costs in generation, transmission and storage units to meet the 35 TWh electricity generation are minimized under the same scenarios. The generation expansion consists of expanding the generation from large-scale solar PV and wind onshore from 26 TWh to 35 TWh. The results of the first optimization problem show that under a medium growth of electricity demand, the target to reduce CO2 emissions by 49% can be reached under the achievement of both 50% and 100% of planned large-scale solar PV. However, under a high growth of electricity demand, the national target to reduce CO2 emissions by 49% by the achievement of 50% of large-scale solar PV is not reached. Both transmission lines (at different voltage levels) and storage units (battery and hydrogen) need to be expanded to incorporate the 26 TWh electricity generation. The best technology to generate the remaining 9 TWh according to the results of the second optimization problem is wind onshore. Moreover, the best location is Rotterdam-Den Haag region. As a result, the 35 TWh electricity generation can be integrated into the electricity grid in a cost-optimal way by using energy storage systems, flexible gas supply and the expansion of several transmission lines at the 380kV and 150kV voltage level. This work can be extended to explore other directions such as the variations of both CO2 cap and price, the coupling to other sectors such as gas network and the interconnection between surrounding countries.