Using energy carrier price information to understand trade-offs between different configurations of a fully sector-coupled energy system model

Abstract

Although there is a common understanding that the use of variable renewable energy sources (VRES) is needed in our collective attempt to decarbonise society, the type of technology that we should deploy, and where is not so clear. Stakeholders from real-world projects use the outcomes from optimisation models to aid their decision-making process. One of such outcomes that decision-makers use is the price information of energy carriers in the required temporal and spatial resolution. In the current state, price information is embedded in the form of shadow prices within linear optimisation problems. As a result, price information is relatively easy to extract for conventional, power-sector focussed energy system models. However, when these energy system models are multi-carrier and sector-coupled in which energy carriers undergo several conversion stages, the extraction of price information becomes less trivial. Furthermore, even when price information is extracted in the form of shadow prices, they might not represent real-world price information. This master thesis research aims to develop a generally applicable price information generation method to extend the use of shadow-price based methods in conventional models to more complex multi-carrier fully sector-coupled models. The price information generation method is developed in Python which is tested within the Calliope modelling framework for a multi-carrier fully sector-coupled energy system. It does this by extracting the shadow prices from a linear optimisation problem of the North Sea Euro Calliope model which is adapted from the Euro-Calliope model. The shadow prices are then compared against current real-world prices for the energy carrier electricity. Results show that the shadow prices do not represent real-world prices accurately, however the use of shadow prices can be extended to understand trade-offs between different configurations of fully sector-coupled energy system models. A use case for the shadow prices has been conducted to analyse the price stability of Dutch electricity prices for different hydrogen shares within the energy system for different weather scenarios. Initial results show that the price stability of electricity in the Netherlands could be improved by increasing the share of hydrogen in the energy system. The increase of the hydrogen share within an energy system does not significantly affect the payback time of the energy system and the levelized cost of energy (LCOE) for electricity technologies. This research project shows that shadow prices could be used to understand trade-offs in different configurations of fully sector-coupled energy systems and aid the decision-making for the type and location of technologies to fulfil energy demands in the future. Recommended future research include an improvement of the North Sea Calliope model using a bottom-up approach and the analysis of other sectors within the fully sector-coupled energy system such as hydrogen and heat.