Periodic Reporting for period 1 - INTEREST (INTEGRATED DIGITAL SOLUTION FOR SUSTAINABLE AND RELIABLE MANAGEMENT OF INTERNATIONAL RENEWABLE ENERGY SYSTEMS.)
Reporting period: 2024-09-01 to 2026-02-28
Europe’s energy system is undergoing a major transition driven by climate‑neutrality targets, energy security, and rapid growth of renewable energy. At the same time, electrification and sector coupling are increasing system complexity. This creates new operational challenges linked to variable renewable generation, decentralised assets, ageing infrastructure, and the need to maintain reliability and affordability.
Digitalisation is a key enabler of this transition through digital twins, forecasting, automation, and intelligent control. However, current solutions are often fragmented, limited to single assets or single energy carriers, and not sufficiently integrated for real‑time operation. There is therefore a need for scalable and secure digital approaches that can coordinate multi‑carrier energy systems and support energy communities and cross‑sector integration.
In this context, INTEREST aims to develop, integrate, and validate an advanced digital solution for the sustainable and reliable management of renewable and multi‑carrier energy systems. The project combines digital twins, forecasting, health monitoring, fault detection, hierarchical and distributed model predictive control, and secure communication into a unified operational framework, addressing the full system hierarchy from individual assets and energy communities to distribution‑level operation.
The pathway to impact is based on progressing from method development to system integration and validation in representative real‑world use cases, generating evidence for deployment and wider uptake. By improving reliability, flexibility, and resilience of renewable‑based energy systems, INTEREST contributes to European priorities on climate neutrality, digital transformation, and citizen participation. Social sciences and humanities are integrated through stakeholder and regulatory analysis and consideration of societal acceptance to support practical implementation and uptake of digitalised energy solutions.
Digitalisation is a key enabler of this transition through digital twins, forecasting, automation, and intelligent control. However, current solutions are often fragmented, limited to single assets or single energy carriers, and not sufficiently integrated for real‑time operation. There is therefore a need for scalable and secure digital approaches that can coordinate multi‑carrier energy systems and support energy communities and cross‑sector integration.
In this context, INTEREST aims to develop, integrate, and validate an advanced digital solution for the sustainable and reliable management of renewable and multi‑carrier energy systems. The project combines digital twins, forecasting, health monitoring, fault detection, hierarchical and distributed model predictive control, and secure communication into a unified operational framework, addressing the full system hierarchy from individual assets and energy communities to distribution‑level operation.
The pathway to impact is based on progressing from method development to system integration and validation in representative real‑world use cases, generating evidence for deployment and wider uptake. By improving reliability, flexibility, and resilience of renewable‑based energy systems, INTEREST contributes to European priorities on climate neutrality, digital transformation, and citizen participation. Social sciences and humanities are integrated through stakeholder and regulatory analysis and consideration of societal acceptance to support practical implementation and uptake of digitalised energy solutions.
Work performed so far has focused on the technical and scientific development, integration, and preliminary validation of an integrated digital solution for renewable and multi‑carrier energy systems. Activities in RP1 covered multi‑energy system modelling and data handling, renewable generation and load forecasting, asset health modelling and fault detection, hierarchical and distributed optimisation and control, definition of a scalable system architecture, and the preparation of realistic validation environments and use‑case datasets. These activities establish the scientific and technological foundations required for system‑level validation in the next project phases.
A central achievement is the development of modular, real‑time capable digital twins for electricity networks and thermal networks (district heating/cooling), as well as key renewable and sector‑coupling assets. Component‑level models for power systems (e.g. network elements and loads) and thermal systems (e.g. piping networks, pumps, storage and conversion units) were implemented with interoperability and control‑oriented design in mind, enabling consistent simulation, analysis and integration across energy vectors. Plug‑and‑play concepts were implemented via standardised interfaces to support flexible configuration and future scaling of multi‑carrier system representations.
In parallel, a unified forecasting framework for renewable generation was designed and validated, including short‑term forecasting models for wind and photovoltaic generation, intended for operational integration with the digital twin and control layers. These forecasting capabilities support predictive operation by reducing uncertainty in renewable production and enabling anticipatory decision‑making for system optimisation and control.
A further core technical achievement is the development of health and fault‑aware methods. A health model library was established for multiple asset classes relevant to the project (e.g. storage and conversion assets), together with fault detection approaches combining model‑based and data‑driven techniques. This work provides the basis for predictive maintenance, early anomaly identification, and health‑aware operation, and it supports the extension of asset‑level health models toward integrated system‑level digital twin functionality.
On the control and optimisation side, key elements of the parameter and state estimation toolbox and hierarchical/distributed model predictive control approaches were developed and tested in simulation. The project advanced reconfigurable and self‑healing control concepts to enable continued operation under faults, asset disconnection, or topology changes, supporting resilience and adaptability in decentralised multi‑energy systems. Cybersecurity considerations were analysed and incorporated through security‑aware monitoring and detection concepts aligned with the needs of digitalised energy infrastructures.
A scalable and interoperable system integration architecture was defined and implemented in initial form, enabling the Energy Management System layer to interface with the advanced digital components (digital twins, forecasting, etc). Integration and validation procedures were prepared, including system‑level testing approaches intended to ensure consistent interoperability and readiness for pilot deployment.
Finally, the project defined and structured representative real‑world use cases and validation frameworks, including energy community and sector‑coupled electricity/thermal scenarios across different contexts.
A central achievement is the development of modular, real‑time capable digital twins for electricity networks and thermal networks (district heating/cooling), as well as key renewable and sector‑coupling assets. Component‑level models for power systems (e.g. network elements and loads) and thermal systems (e.g. piping networks, pumps, storage and conversion units) were implemented with interoperability and control‑oriented design in mind, enabling consistent simulation, analysis and integration across energy vectors. Plug‑and‑play concepts were implemented via standardised interfaces to support flexible configuration and future scaling of multi‑carrier system representations.
In parallel, a unified forecasting framework for renewable generation was designed and validated, including short‑term forecasting models for wind and photovoltaic generation, intended for operational integration with the digital twin and control layers. These forecasting capabilities support predictive operation by reducing uncertainty in renewable production and enabling anticipatory decision‑making for system optimisation and control.
A further core technical achievement is the development of health and fault‑aware methods. A health model library was established for multiple asset classes relevant to the project (e.g. storage and conversion assets), together with fault detection approaches combining model‑based and data‑driven techniques. This work provides the basis for predictive maintenance, early anomaly identification, and health‑aware operation, and it supports the extension of asset‑level health models toward integrated system‑level digital twin functionality.
On the control and optimisation side, key elements of the parameter and state estimation toolbox and hierarchical/distributed model predictive control approaches were developed and tested in simulation. The project advanced reconfigurable and self‑healing control concepts to enable continued operation under faults, asset disconnection, or topology changes, supporting resilience and adaptability in decentralised multi‑energy systems. Cybersecurity considerations were analysed and incorporated through security‑aware monitoring and detection concepts aligned with the needs of digitalised energy infrastructures.
A scalable and interoperable system integration architecture was defined and implemented in initial form, enabling the Energy Management System layer to interface with the advanced digital components (digital twins, forecasting, etc). Integration and validation procedures were prepared, including system‑level testing approaches intended to ensure consistent interoperability and readiness for pilot deployment.
Finally, the project defined and structured representative real‑world use cases and validation frameworks, including energy community and sector‑coupled electricity/thermal scenarios across different contexts.
Results beyond the state of the art
INTEREST advances the state of the art by moving beyond isolated digital tools toward a fully integrated, real‑time operational framework for multi‑carrier energy systems. While many existing approaches focus on single assets, single energy vectors, or offline optimisation, INTEREST integrates digital twins, forecasting, health monitoring, fault detection, and hierarchical/distributed control across electricity and thermal systems within a common architecture.
A key innovation is the operational use of digital twins enriched with health and fault information to enable predictive, health‑aware decision‑making. By linking predictive maintenance outputs directly with distributed model predictive control, INTEREST goes beyond current practice and enables self‑healing and resilient system operation, including continued operation under faults, asset unavailability, or topology changes. The vertically nested and scalable architecture supports decentralised operation while ensuring system‑wide coordination, which is essential for energy communities and high renewable penetration.
Cybersecurity is treated as an integral design requirement, rather than an add‑on, strengthening trust and robustness of digital energy solutions. Overall, INTEREST has progressed beyond conceptual research by validating key methods in realistic scenarios and preparing their application in representative operational contexts.
Key needs to ensure further uptake and success
1) Large‑scale demonstration and validation in operational environments to quantify system‑level benefits (reliability, flexibility, resilience) and confirm performance under real constraints.
2) Standardisation and interoperability through well‑defined interfaces and alignment with relevant energy data and communication standards to reduce integration barriers.
3) Supportive regulatory frameworks, especially for energy communities, sector coupling, and flexibility services, to enable practical implementation and value capture.
4) Market and financing readiness, including clear value propositions and cost/benefit evidence for utilities, DSOs, and energy communities, supported by scalable deployment pathways.
INTEREST advances the state of the art by moving beyond isolated digital tools toward a fully integrated, real‑time operational framework for multi‑carrier energy systems. While many existing approaches focus on single assets, single energy vectors, or offline optimisation, INTEREST integrates digital twins, forecasting, health monitoring, fault detection, and hierarchical/distributed control across electricity and thermal systems within a common architecture.
A key innovation is the operational use of digital twins enriched with health and fault information to enable predictive, health‑aware decision‑making. By linking predictive maintenance outputs directly with distributed model predictive control, INTEREST goes beyond current practice and enables self‑healing and resilient system operation, including continued operation under faults, asset unavailability, or topology changes. The vertically nested and scalable architecture supports decentralised operation while ensuring system‑wide coordination, which is essential for energy communities and high renewable penetration.
Cybersecurity is treated as an integral design requirement, rather than an add‑on, strengthening trust and robustness of digital energy solutions. Overall, INTEREST has progressed beyond conceptual research by validating key methods in realistic scenarios and preparing their application in representative operational contexts.
Key needs to ensure further uptake and success
1) Large‑scale demonstration and validation in operational environments to quantify system‑level benefits (reliability, flexibility, resilience) and confirm performance under real constraints.
2) Standardisation and interoperability through well‑defined interfaces and alignment with relevant energy data and communication standards to reduce integration barriers.
3) Supportive regulatory frameworks, especially for energy communities, sector coupling, and flexibility services, to enable practical implementation and value capture.
4) Market and financing readiness, including clear value propositions and cost/benefit evidence for utilities, DSOs, and energy communities, supported by scalable deployment pathways.