The initiative, funded by CDTI, brings together leading technology centres to develop advanced solutions for forecasting, distributed control and intelligent operation of electricity networks.
CIDETEC Energy Storage participates as a key member in the new R5DES network of excellence, a technological R&D&I project promoted by the CDTI Cervera Network and led by the Instituto Tecnológico de la Energía (ITE). The other members forming part of the network are Tekniker, Ikerlan and Centro Tecnológico ITG, creating a highly complementary ecosystem of capabilities in energy, digitalisation and innovation for electricity networks.
R5DES takes its name from the five pillars of the energy system of the future:
Efficient distribution, distributed energy, digitalisation, flexible demand and decarbonisation, and is framed within the Energy 5D strategy: Digital, Distributed, Decarbonised, Decentralised and Dynamic.
The objective of this project is to drive new capabilities and technologies that improve the operation of electricity networks in the face of critical events, growing new energy demands and the expansion of decentralised generation. R5DES will therefore help strengthen the resilience, flexibility and sustainability of the Spanish electricity system, consolidating the adoption of advanced technologies and enhancing sector competitiveness.
In addition, the network’s strategic plan is structured around axes such as the creation of high-level scientific capabilities, advanced training, technology transfer and the international positioning of the participating centres. The kick-off meeting held at ITE marked the official start of activities, identifying synergies and opportunities for the next three years of implementation.
CIDETEC’s contribution to R5DES:
CIDETEC Energy Storage will contribute advanced capabilities in storage, digital modelling and techno-economic analysis, reinforcing its strategic role in the energy transition. Specifically, CIDETEC will:
- Increase its capabilities in predictive digital modelling of degradation in storage systems and electrolysers through digital twins and advanced estimators.
- Develop sizing tools and demand and generation forecasting models based on Machine Learning to optimise the location of Distributed Energy Resources (DERs).
- Validate battery SOC/SOH estimators under real conditions using HIL environments.
- Contribute to the development of Energy Management Systems (EMS) integrating storage and renewables within multi-energy schemes.
- Strengthen energy market analysis and the assessment of economic vulnerabilities of large consumers.
- Advance regulatory and techno-economic assessment of storage, including LCOS metrics, identifying barriers and proposing solutions.
- Provide expertise in the design of replicable business models in aggregation and flexibility, with a focus on scalability and sustainability.
The project is funded by CDTI and supported by the Ministry of Science, Innovation and Universities under file reference CER-20251021.









