Periodic Reporting for period 2 - InnoCyPES (Innovative Tools for Cyber-Physical Energy Systems)
Okres sprawozdawczy: 2023-06-01 do 2025-11-30
The InnoCyPES project, funded under the Horizon 2020 Marie Skłodowska‑Curie Actions, has successfully concluded its mission (June 2021 – November 2025). By tightly integrating the data lifecycle with energy system engineering, InnoCyPES has delivered innovative tools and methodologies that support a secure, stable, and digitalized European energy infrastructure.
Selected Key Achievements:
1. Training the Next Generation of Experts
A core achievement of InnoCyPES was the recruitment and training of 15 Early‑Stage Researchers (ESRs) enrolled in PhD programmes addressing highly innovative and societally relevant research topics. The project fostered a strong international and interdisciplinary research community through four training schools (Copenhagen, Trondheim, Novi Sad, and Delft), a summer school in Lecce, and a dedicated workshop in Vienna.
Digital Infrastructure Design
InnoCyPES introduced novel methods for the design of IoT‑based communication networks for offshore power plants, with a strong focus on enhanced system resilience. The project also developed model‑driven tools for virtualized protection and control, promoting interoperability through the use of standardized data models.
2. Strengthening Cybersecurity
The project developed and validated advanced methodologies for real‑time detection and localization of cyber threats in power systems. Key results include the identification of Sampled Value (SV) injection attacks in digital substations and the application of Vertical Federated Learning to detect false‑data‑injection attacks, enabling effective threat detection while preserving data privacy through information exchange rather than raw data sharing.
3. Innovations in Grid Stability and Control
InnoCyPES researchers proposed new solutions to improve control design and stability assessment of grid‑forming converters, addressing a critical challenge in modern converter‑dominated power systems.
4. Advanced Data Analytics for Asset Management
The project developed real‑time analytics for power‑quality disturbance detection in power systems. In addition, novel data‑driven methods based on historical fault data were explored to support improved asset management in distribution grids.
5. Digital Testing and Validation Methods
InnoCyPES made significant contributions to testing and model validation using software‑ and hardware‑in‑the‑loop approaches. In particular, software‑in‑the‑loop methods were tested and validated for wind turbines, demonstrating strong potential for real‑time digital simulation and large‑scale testing of wind power plants and complex converter‑based systems.
6. Quantifying the Value of Digitalization
To support industrial decision‑making and policy analysis, the project introduced novel system‑dynamics‑based models for Cost‑Benefit Analysis (CBA). These models capture the complex and often intangible value streams associated with digital solutions, which are difficult to assess using traditional evaluation approaches.
Impact on Europe’s Energy Transition
By bringing together 24 partners, including 11 beneficiaries and 13 partner organizations, InnoCyPES successfully bridged the gap between academic research excellence and industrial application. The tools, methods, and trained experts emerging from the project provide a strong foundation for Europe’s transition towards a decentralized, resilient, and carbon‑neutral energy system.
Selected Key Achievements:
1. Training the Next Generation of Experts
A core achievement of InnoCyPES was the recruitment and training of 15 Early‑Stage Researchers (ESRs) enrolled in PhD programmes addressing highly innovative and societally relevant research topics. The project fostered a strong international and interdisciplinary research community through four training schools (Copenhagen, Trondheim, Novi Sad, and Delft), a summer school in Lecce, and a dedicated workshop in Vienna.
Digital Infrastructure Design
InnoCyPES introduced novel methods for the design of IoT‑based communication networks for offshore power plants, with a strong focus on enhanced system resilience. The project also developed model‑driven tools for virtualized protection and control, promoting interoperability through the use of standardized data models.
2. Strengthening Cybersecurity
The project developed and validated advanced methodologies for real‑time detection and localization of cyber threats in power systems. Key results include the identification of Sampled Value (SV) injection attacks in digital substations and the application of Vertical Federated Learning to detect false‑data‑injection attacks, enabling effective threat detection while preserving data privacy through information exchange rather than raw data sharing.
3. Innovations in Grid Stability and Control
InnoCyPES researchers proposed new solutions to improve control design and stability assessment of grid‑forming converters, addressing a critical challenge in modern converter‑dominated power systems.
4. Advanced Data Analytics for Asset Management
The project developed real‑time analytics for power‑quality disturbance detection in power systems. In addition, novel data‑driven methods based on historical fault data were explored to support improved asset management in distribution grids.
5. Digital Testing and Validation Methods
InnoCyPES made significant contributions to testing and model validation using software‑ and hardware‑in‑the‑loop approaches. In particular, software‑in‑the‑loop methods were tested and validated for wind turbines, demonstrating strong potential for real‑time digital simulation and large‑scale testing of wind power plants and complex converter‑based systems.
6. Quantifying the Value of Digitalization
To support industrial decision‑making and policy analysis, the project introduced novel system‑dynamics‑based models for Cost‑Benefit Analysis (CBA). These models capture the complex and often intangible value streams associated with digital solutions, which are difficult to assess using traditional evaluation approaches.
Impact on Europe’s Energy Transition
By bringing together 24 partners, including 11 beneficiaries and 13 partner organizations, InnoCyPES successfully bridged the gap between academic research excellence and industrial application. The tools, methods, and trained experts emerging from the project provide a strong foundation for Europe’s transition towards a decentralized, resilient, and carbon‑neutral energy system.
The reporting period has yielded significant achievements, which are thoroughly documented in the submitted deliverables.
The research conducted by the Early Stage Researchers (ESRs) has produced several notable outcomes, summarized as follows:
- Design method of an IoT/cloud‑enabled monitoring system for offshore wind power plants
- A software‑defined networking (SDN)–based communication network for virtualized system and service design
- Information model specifications supporting software‑defined protection, automation, and control in power systems
- Real‑time recognition techniques for cyberattacks
- Data requirements, fusion techniques, and enrichment methods for reliability assessment of medium‑voltage cable faults in distribution grids
- Optimal design methodologies for hybrid offshore wind power plants supplying offshore oil and gas facilities
- Transient stability analysis of grid‑forming converters and associated benchmark simulation models
- Privacy‑preserving federated learning approaches for distribution grid state estimation
- Machine‑learning‑based assessment methods combining simulated and field measurements for grid compliance evaluation
- Data‑driven and hybrid estimation of wind turbine and system behavior during grid faults
- System‑dynamics‑based assessment of the costs and benefits of digital investments for technology developers and asset owners
- Identification of digitalization barriers in distribution systems and preliminary policy recommendations using system dynamics model
In total, InnoCyPES has produced 100+ scientific outputs, including journal articles and conference papers. A large portion of these works has already been published, with others currently undergoing peer review or in the publication pipeline. In addition to publications, the project has delivered two software packages, two patent applications, several open‑source tools and datasets, and one testbed, all of which have been released or made publicly accessible. A comprehensive summary of communication activities, conference participation, and dissemination outputs is provided in the appendix of this report.
The research conducted by the Early Stage Researchers (ESRs) has produced several notable outcomes, summarized as follows:
- Design method of an IoT/cloud‑enabled monitoring system for offshore wind power plants
- A software‑defined networking (SDN)–based communication network for virtualized system and service design
- Information model specifications supporting software‑defined protection, automation, and control in power systems
- Real‑time recognition techniques for cyberattacks
- Data requirements, fusion techniques, and enrichment methods for reliability assessment of medium‑voltage cable faults in distribution grids
- Optimal design methodologies for hybrid offshore wind power plants supplying offshore oil and gas facilities
- Transient stability analysis of grid‑forming converters and associated benchmark simulation models
- Privacy‑preserving federated learning approaches for distribution grid state estimation
- Machine‑learning‑based assessment methods combining simulated and field measurements for grid compliance evaluation
- Data‑driven and hybrid estimation of wind turbine and system behavior during grid faults
- System‑dynamics‑based assessment of the costs and benefits of digital investments for technology developers and asset owners
- Identification of digitalization barriers in distribution systems and preliminary policy recommendations using system dynamics model
In total, InnoCyPES has produced 100+ scientific outputs, including journal articles and conference papers. A large portion of these works has already been published, with others currently undergoing peer review or in the publication pipeline. In addition to publications, the project has delivered two software packages, two patent applications, several open‑source tools and datasets, and one testbed, all of which have been released or made publicly accessible. A comprehensive summary of communication activities, conference participation, and dissemination outputs is provided in the appendix of this report.
The project is advancing state‑of‑the‑art developments in both cyber and physical system design for the energy sector. Beyond scientific publications, its results are being leveraged through contributions to standardization bodies (e.g. IEC), patent applications, and the release of open‑source software tools.
WP1 introduces a new information model that goes beyond conventional component‑specific standards by encompassing diverse system elements. The work also explores integrating IoT/Cloud technologies into existing SCADA infrastructures. Intrusion‑detection mechanisms for both IT and OT environments are under development. These results show strong potential to influence next‑generation SCADA design for offshore wind and future smart grid standardization.
WP2 focuses on improving data quality and ensuring efficient, secure data management. Data enrichment methods are applied to various datasets to support enhanced reliability assessment and operational insights for distribution grids. A new data management system is being designed to support distributed data collection, curation, and extraction across heterogeneous data sources, covering both relational and non‑relational formats.
WP3 develops advanced data‑driven applications that use information both within and beyond traditional SCADA systems. Industrial datasets are processed using modern analytics to enhance reliability, stability, and overall system performance. The project also curates the first large‑scale dataset combining historical fault records from multiple distribution grids with external factors such as weather and excavation activities, enabling improved understanding of reliability drivers.
WP4 contributes to digital twin development for renewable generation and energy systems using both data‑driven and model‑based approaches. These digital representations integrate historical data, measurements, simulations, and test results, reducing reliance on full‑scale field tests. WP4 also develops digital twins for power plants and grids, with key outputs already contributing to emerging standards for Software/Hardware‑in‑the‑Loop (S/HiL) testing of renewable‑based systems.
WP5 develops new approaches for evaluating the costs and benefits of digital investments, addressing limitations in current assessment methods that struggle to capture impacts on physical system operation. WP5 also examines the environmental sustainability of digitalization and proposes a framework for governance, regulation, and policy to support the sector’s transformation. System‑dynamics‑based models have been developed for distribution grids and offshore wind, and key barriers to digitalization have been identified through expert interviews.
WP1 introduces a new information model that goes beyond conventional component‑specific standards by encompassing diverse system elements. The work also explores integrating IoT/Cloud technologies into existing SCADA infrastructures. Intrusion‑detection mechanisms for both IT and OT environments are under development. These results show strong potential to influence next‑generation SCADA design for offshore wind and future smart grid standardization.
WP2 focuses on improving data quality and ensuring efficient, secure data management. Data enrichment methods are applied to various datasets to support enhanced reliability assessment and operational insights for distribution grids. A new data management system is being designed to support distributed data collection, curation, and extraction across heterogeneous data sources, covering both relational and non‑relational formats.
WP3 develops advanced data‑driven applications that use information both within and beyond traditional SCADA systems. Industrial datasets are processed using modern analytics to enhance reliability, stability, and overall system performance. The project also curates the first large‑scale dataset combining historical fault records from multiple distribution grids with external factors such as weather and excavation activities, enabling improved understanding of reliability drivers.
WP4 contributes to digital twin development for renewable generation and energy systems using both data‑driven and model‑based approaches. These digital representations integrate historical data, measurements, simulations, and test results, reducing reliance on full‑scale field tests. WP4 also develops digital twins for power plants and grids, with key outputs already contributing to emerging standards for Software/Hardware‑in‑the‑Loop (S/HiL) testing of renewable‑based systems.
WP5 develops new approaches for evaluating the costs and benefits of digital investments, addressing limitations in current assessment methods that struggle to capture impacts on physical system operation. WP5 also examines the environmental sustainability of digitalization and proposes a framework for governance, regulation, and policy to support the sector’s transformation. System‑dynamics‑based models have been developed for distribution grids and offshore wind, and key barriers to digitalization have been identified through expert interviews.