Project Details
Description
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 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).
| Acronym | MOPO |
|---|---|
| Status | Active |
| Effective start/end date | 1/01/23 → 31/12/26 |
Collaborative partners
- VTT Technical Research Centre of Finland (lead)
- Technical University of Denmark (DTU)
- University College Dublin
- Netherlands Organisation for Applied Scientific Research (TNO)
- Katholieke Universiteit Leuven (KU Leuven)
- Energy Reform Ltd.
- Flemish Institute for Technological Research (VITO)
- Netherlands eScience Center
- Electric Power Research Institute Europe DAC
- Fluxys
- Fondazione iCons
- Fortum Power and Heat Oy
- Netherlands Ministry of Instrastructure and Water Management
- KTH Royal Institute of Technology
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
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SDG 7 Affordable and Clean Energy
Funding category
- Horizon Europe
Keywords
- HORIZON-CL5-2022-D3-01-13
- data processing
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Debunking the speed-fidelity trade-off: Speeding-up large-scale energy models while keeping fidelity
Tejada-Arango, D. A., Kiviluoma, J. & Morales-España, G., Jul 2025, In: International Journal of Electrical Power and Energy Systems. 168, 110674.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access1 Link opens in a new tab Citation (Scopus) -
Metric functionals and weak convergence
Gutiérrez, A. W. & Nevanlinna, O., 2025, (Submitted) In: arXiv preprint.Research output: Contribution to journal › Article › Scientific
File29 Downloads (Pure) -
Comparison of SpineOpt and PyPSA in Hydro Power System Modelling
Liu, Y., Amelin, M. & Rasku, T., 2024, 20th International Conference on the European Energy Market, EEM 2024 - Proceedings. IEEE Institute of Electrical and Electronic Engineers, (International Conference on the European Energy Market, EEM).Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
Activities
- 2 Public or invited talk
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SpineOpt overview
Rasku, T. (Speaker)
13 Jan 2026Activity: Talk or presentation types › Public or invited talk
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New SpineOpt input data structure
Rasku, T. (Speaker)
31 Mar 2026Activity: Talk or presentation types › Public or invited talk