PRESS RELEASE Published On 15 Oct 2025

Energy system project reveals pioneering optimisation tool

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The EU-funded project Mopo has released a new info-pack on SpineOpt, a user-friendly energy system optimisation tool designed to empower the design of resilient and integrated energy systems.

As Europe moves towards climate neutrality, energy planners, policymakers, and researchers face the challenge of building future energy systems that integrate renewables, hydrogen, storage, and cross-sector solutions. SpineOpt offers a flexible, data-driven modelling framework to explore these complex interactions and provide insights into efficient investment pathways.

 

The Mopo info-pack is available for download on the project website at this link. The brief shows how SpineOpt can be applied in both real-world and theoretical use cases:

  • Spine H2-IRL: Seven real-world energy scenarios assess the role of hydrogen infrastructure, storage, and renewables in achieving net-zero constraints. They do this by comparing business-as-usual pathways with the use of alternative technologies in Ireland’s energy transition.
  • Offshore infrastructure study: Five transition scenarios for an oil and gas (O&G) platform explore options such as electrification, integration of offshore wind, and repurposing for blue and green hydrogen production.

 

Beyond case studies, the info-pack highlights SpineOpt’s features: flexible temporal and stochastic structures, multi-stage optimisation, investment pathway analysis, and built-in algorithms for handling uncertainty and near-optimal solutions. These functionalities allow users to model complex systems in detail, while keeping the approach adaptable to evolving energy challenges.

 

SpineOpt is a flexible toolkit that helps address challenges in the energy transition. This info-pack shows how open science can be combined with practical applications to support better decisions for Europe’s energy future.

 

About Mopo
Mopo is a Horizon Europe project combining component tools producing input data to create model-ready datasets, scenario and workflow management, and medium and long-term energy system planning. The aim is to provide a user-friendly, open-source and validated set of tools to benefit decision-makers in network operation, industry and public authorities.

 

 

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