Improving the simulation-based optimization in the REMod model to deal with complexity in energy system modeling

To reflect the complexity of the energy transition, a current challenge in modeling national energy transition pathways is to combine high resolution in time, space, techno-economic and sector coupling details in a single model. To address this challenge, the paper discusses improvements in the simulation-based optimization approach, which is used by the energy system model REMod as an alternative to the widely used linear optimization approach. The REMod model uses a simulation of the energy system coupled with a black-box optimization algorithm to optimize the transformation path. To limit the computational complexity, while taking into account the hourly operation of the energy system along the whole transformation path, various aspects have to be considered: performance of the simulation, choice of the optimization algorithm and selection of the termination criterion and population size. The model employs a novel method of endogenous interpolation to incorporate the entire transformation path into the objective function, and it can be evaluated in parallel. This allows for an increase in complexity both in technological details and in geographical resolution, enabling a long-term energy system model to be solved that is unique in terms of its techno-economic and sector coupling details, temporal resolution, and multi-regional representation. The approach cannot guarantee global optimality, which leads to variance in the results that requires careful consideration when interpreting them. With its system-wide focus on transition pathways, the model complements existing models that excel in specific sectors or operational optimization, for example.