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This call focuses on developing a sophisticated, integrated cross-regional network and market model to optimize long-duration energy storage (LDES) in energy systems dominated by intermittent and stochastic renewable energy sources. The objective is to create a spatially and temporally detailed model capable of analyzing LDES performance and optimizing its strategic integration. Projects should aim to optimize LDES investment and operational costs, develop business cases for future energy markets, and assess marginal abatement costs of different technologies and their combinations within the involved regions.
The initiative seeks to increase knowledge on the cost-benefit of integrating low-cost long-duration storage in relevant grid locations to optimize cost and operation. It also aims to explore cross-regional approaches to long-term storage and cross-sector integration, focusing on balancing electrical grid infrastructure with technologies, buildings, and power management solutions, including thermal networks and storage. Additionally, the call encourages the development of clean flexibility long-term energy storage solutions that couple electricity with other energy carriers to optimize the integration of renewables and effectively increase grid hosting capacity. Supporting cost-effective decarbonization and improving LDES economics through market revenue streams, such as nodal and locational pricing, are also key objectives.
Projects should be based on a comprehensive understanding of existing systems in at least two adjacent regions, best represented in the form of a digital twin or similar. Consortia should include system operators, technology providers, and other relevant stakeholders. The scope includes improving the integration of long-duration (>12h) storage within the context of system-wide optimization of grid enhancement strategies in synergy with power plant infrastructure. This encompasses the use of relevant, validated historical data sets, visualization, scenario analysis, model sensitivity analysis, and data set optimization. The project is expected to identify technical and regulatory barriers and propose recommendations and policy actions to promote the best solutions and support their replication.
Opening Date: 06 May 2025
Deadline: 16 September 2025
Data provided by Sciencebusiness.net
This funding opportunity represents a pre-agreed draft that has not yet been officially approved by the European Commission. The final, approved version is expected to be published in the first quarter of 2025. This draft is provided for informational purposes and may be used to preliminarily form consortia and develop project ideas, but it is offered without any guarantees or warranties.
Expected Outcome
• Development of a novel, integrated cross-regional network and market model capable of analyzing LDES performance and optimizing its strategic integration.
• Optimization of LDES investment and operational costs and business cases in future energy markets, including marginal abatement costs of different technologies.
• Increased knowledge on the cost-benefit of low-cost long-duration storage integrated in relevant grid locations.
• Exploration of cross-regional approaches to long-term storage and cross-sector integration to balance electrical grid infrastructure with technologies, buildings, and power management solutions.
• Development of clean flexibility long-term energy storage solutions coupling electricity with other energy carriers to optimize integration of renewables and increase grid hosting capacity.
• Support for cost-effective decarbonization and market revenue streams to improve LDES economics, such as nodal and locational pricing.
Scope
• Base the project on a comprehensive understanding of existing systems in at least two adjacent regions, represented as a digital twin or similar.
• Include system operators, technology providers, and other relevant stakeholders in the consortium.
• Improve integration of long-duration (>12h) storage within system-wide optimization of grid enhancement strategies in synergy with power plant infrastructure.
• Utilize relevant historical data sets, visualization, scenario analysis, model sensitivity analysis, and data set optimization.
• Identify technical and regulatory barriers and propose recommendations and policy actions to promote best solutions and support replication.