The overall objective of Mopo is to develop a validated, user-friendly, feature-rich, innovative and well-performing energy system modelling toolset to serve public authorities, network operators, industry and academia to plan sustainable and resilient energy systems in a cost-effective manner. Mopo will include 1) component tools to produce all necessary energy system data; 2) system tool to manage data, scenarios and modelling workflows, to visualise data and to maintain datasets in multi-user environment without losing the track of changes; 3) planning tool to optimise all energy sectors in detail, including sector specific physics and highly flexible representation of temporal, spatial and technological aspects – user can choose how to model depending on the specific needs. The project is based on existing state-of-the-art tools including Spine Toolbox and SpineOpt. The advanced capabilities will be demonstrated through an industrial case (with detailed sector-specific physics) and Pan-European case (resilient pathways). The project will also produce an open access Pan-European dataset at hourly temporal resolution and high spatial resolution (NUTS2 capable). It can be fed into SpineOpt or used by other modelling groups. Mopo tools can recreate data at resolution required by the end-user – also for future climates. End-user requirements, feedback and tool validations will be important part of Mopo – the consortium includes representatives from all end-user categories. Partners will also have skills in user-interfaces, computational efficiency, data processing, code testing, community building and all aspects related to energy systems (technologies, sectors, resources). Mopo project aims to benefit 60% of network operators and public authorities within 2 years of the project end. The tools will be modular, which allows different organisations to adopt the parts that benefit their existing modelling systems.

Spine project will create a toolbox for modelling integrated energy systems. The Toolbox will be modular and adaptable, making the toolbox suitable for both detailed modelling of complex features in energy systems as well as for large-scale problems. This is a novel approach to energy system modelling, which allows a much broader set of problems being addressed within a single modelling tool. The adaptability comes from a design where the input data defines the temporal, spatial, technological, regulatory and sectoral dimensions of the model instance. Model instances can also be chained in order to allow iterative approaches for solving especially large problems (e.g. planning a large system while considering high operational detail). The Spine Toolbox will support the full modelling chain from data acquisition to processing of results. Through automated features of the toolbox it will be easy to generate a large number of scenarios from user-defined data collections. It can connect to different tools and models, both external and internal. The internal tools developed in the project include an input data verification tool, a tool to post-process outputs, parallelization service and the actual Spine Model. The Spine Toolbox and the Spine Model will be deployed by open sourcing all the developments. The project will initiate, grow and support a user community where the project partners will participate as they will replace many of their existing tools with the Spine Toolbox. The Spine project will use the toolbox to contribute to the expected impacts of the call. A series of case studies will help the project to expand specific modelling capabilities in the Spine Model, deploy the Toolbox to potential users, and produce analysis relevant to the expected impacts of the call. Policy and business relevant results will be communicated to the relevant stakeholders, demonstrating the future uses of the toolbox in policy-support and business decision-support.