Mopo iproduces high resolution datasets for energy system modelling and a system to build model instances fit for purpose (e.g. high resolution for the country under study while keeping other regions in lower resolution for computational efficiency). The datasets will cover all important energy domains: demand in industries, buildings, transport, availability and time series for renewable energy, costs and characteristics of energy conversion, transmission and storage technologies as well as existing infrastructures. The first versions of the datasets have been made available.
Mopo enhances the open-source workflow, data and scenario management tool Spine Toolbox. Handling large amounts of complex data for scenario-based modelling is time consuming and error-prone endeavor. Spine Toolbox helps to avoid mistakes, automate processes, connect data to models, link different models and visualize results. During Mopo, several improvements have already been made, for example, to the core data structures and user interfaces.
Mopo enhances the state-of-the-art energy system model generator SpineOpt.jl. As the existing SpineOpt is already a very extensive model with lot of capabilities, the focus will be on improving the performance and usability of SpineOpt. During Mopo, the execution speed of SpineOpt has already been improved, its user constraints have been made more flexible, and the input data structure has been simplified without taking away any of its flexibility.
Mopo will perform three case studies: European-wide full sector energy system model, high-detail industrial region and analysis for the decarbonisation of Baltic countries in high resolution.
