Results:

• A Data-driven Approach to Grid Impedance Identification for Impedance-based Stability
• A Robust Circuit and Controller Parameters’ Identification Method of Grid-Connected Voltage-Source Converters Using Vector Fitting Algorithm 
• Cyber-Physical Power System Testing Platform for Topology Identification in Power Distribution Grids
• Delayed Integrity Check
• Distributed ADMM* strategy for optimal control of DERs and OLTCs in a radial distribution grid
• DSOs cooperation with vendors in handling cyber-attacks in control systems 
• Effect of Communication Failures on State Estimation of 5G-Enabled Smart Grid
• Improving Smart Grid Cyber Security through 5G Enabled IoT and Edge Computing
• Method and tool for analysing the performance and dependability of advanced communication technologies
• Modelling framework for study of the differences between centralized and decentralized smart grid services
• Observability in TSO/DSO interface
• Operational functions and applications for the next generation distribution control centres
• Risk considerations by tighter integration of AMI/SCADA/DMS 
• State estimation algorithm for monitoring distribution grid
• Use case: New concept of using mobile battery in distribution grids

Smart grid operation
CINELDI's Knowledge base

The goal of this research area is to develop, implement, test, and evaluate new concepts, tools, and solutions that can integrate emerging information, communication, and cyber security technologies to facilitate smart grid operations. Information and Communication Technologies (ICT) and cyber security technologies are two of the cornerstones that are key for enabling the smart energy transition. Two of the greatest challenges in this research area are: Assisting tools to accelerate the deployment of ICT and tools for handling cybersecurity issues.

CINELDI is contributing to increasing knowledge in the use of emerging ICT technologies in the distribution system. For example, methods and tools for analyzing the performance and dependability of advanced communication technologies [1] [2] [3], resources allocation in 5G networks[4]–[6] , simulation tools for reliability assessment is done in [7], a communication architecture to facilitate the distribution grid automation using 5G was proposed in [8], the test of smart meters for enabling power quality monitoring in a controlled environment [9], and ICT technologies in a lab setup [10].

CINELDI is increasing the understanding of cybersecurity issues that will occur in future distribution systems. For example, the identification and impact of cybersecurity risks were done in [11], a customized model-based risk analysis was proposed in [12], and a risk assessment with the integration of ICT devices was performed in [13], toward new smart grid security using 5G was presented in [14], the need of DSO“s cooperation for handling cyber-attacks was presented in [15] and threat modeling tools for smart grid cybersecurity in [16].

It is crucial to advance the understanding of cybersecurity and the impact of new ICT devices in the distribution grid. CINELDI results can support the next generation of tools for cybersecurity risk analysis [11] [12]. These tools will be essential for decision-making in the upcoming digital transformation. Moreover, CINELDI can help in the integration of new ICT technologies by providing tools for analysing communication failures such as vulnerabilities, interdependencies, and dependencies [1], [17]. In addition, in [18], a novel concept using blockchain as a second-tier security mechanism to support time-critical self-healing operations in smart distribution grids is proposed and validated in simulation studies.

Selected publications from CINELDI:

1. T. Amare, M. Garau, and B. E. Helvik, “Dependability Modeling and Analysis of 5G Based Monitoring System in Distribution Grids”, in Proceedings of the 12th EAI International Conference on Performance Evaluation Methodologies and Tools, Palma Spain, Mar. 2019, pp. 163–166. doi: 10.1145/3306309.3306334.
2. R. Muka, F. B. Haugli, H. Vefsnmo, and P. E. Heegaard, “Information Inconsistencies in Smart Distribution Grids under Different Failure Causes modelled by Stochastic Activity Networks”, in 2019 AEIT International Annual Conference (AEIT), Florence, Italy, Sep. 2019, pp. 1–6. doi: 10.23919/AEIT.2019.8893378.
3. F. B. Haugli and P. E. Heegaard, “Modeling framework for study of distributed and centralized smart grid system services”, presented at the 2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 2021.
4. H. V. K. Mendis, P. E. Heegaard, and K. Kralevska, “5G Network Slicing as an Enabler for Smart Distribution Grid Operations”, AIM, 2019. doi: 10.34890/881.
5. H. V. K. Mendis, P. E. Heegaard, V. Casares-Giner, F. Y. Li, and K. Kralevska, “Transient Performance Modelling of 5G Slicing with Mixed Numerologies for Smart Grid Traffic”, in 2021 IEEE 26th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Porto, Portugal, Oct. 2021, pp. 1–7. doi: 10.1109/CAMAD52502.2021.9617808.
6. R. Muka, M. Garau, B. Tola, and P. E. Heegaard, “Effect of 5G communication service failure on placement of Intelligent Electronic Devices in Smart Distribution Grids”, in 2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), Aachen, Germany, Oct. 2021, pp. 308–314. doi: 10.1109/SmartGridComm51999.2021.9632333.
7. M. Garau, R. Muka, P. E. Heegaard, and B. E. Helvik, “Co-simulation and Discrete Event Simulation for Reliability Assessment of Power System and ICT: A Comparison,” in 2021 5th International Conference on System Reliability and Safety (ICSRS), Palermo, Italy, Nov. 2021, pp. 66–73. doi: 10.1109/ICSRS53853.2021.9660630.
8. K. Mehmood, H. V. K. Mendis, K. Kralevska, and P. E. Heegaard, “Intent-based Network Management and Orchestration for Smart Distribution Grids”, arXiv, May 12, 2021. Accessed: Oct. 21, 2022. [Online].
9. H. Taxt and K. Ljøkelsøy, “Laboratorietest av måling av overharmoniske spenninger med AMS-måler”, SINTEF Energy Research, 2020.
10. M. Z. Degefa, S. Sanchez-Acevedo, and R. Borgaonkar, “A Testbed for Advanced Distribution Management Systems: Assessment of Cybersecurity”, presented at the ISGT 2021, Espoo, FInland, 2021.
11. A. Omerovic, H. Vefsnmo, O. Gjerde, S. T. Ravndal, and A. Kvinnesland, “An Industrial Trial of an Approach to Identification and Modelling of Cybersecurity Risks in the Context of Digital Secondary Substations”, in Risks and Security of Internet and Systems, vol. 12026, S. Kallel, F. Cuppens, N. Cuppens-Boulahia, and A. Hadj Kacem, Eds. Cham: Springer International Publishing, 2020, pp. 17–33. doi: 10.1007/978-3-030-41568-6_2.
12. A. Omerovic, H. Vefsnmo, G. Erdogan, O. Gjerde, E. Gramme, and S. Simonsen, “A Feasibility Study of a Method for Identification and Modelling of Cybersecurity Risks in the Context of Smart Power Grids”, in Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk, Heraklion, Crete, Greece, 2019, pp. 39–51. doi: 10.5220/0007697800390051.
13. K. Bernsmed, M. G. Jaatun, and C. Frøystad, “Is a Smarter Grid Also Riskier?”, in Security and Trust Management, vol. 11738, S. Mauw and M. Conti, Eds. Cham: Springer International Publishing, 2019, pp. 36–52. doi: 10.1007/978-3-030-31511-5_3.
14. R. Borgaonkar, I. Anne Tøndel, M. Zenebe Degefa, and M. Gilje Jaatun, “Improving smart grid security through 5G enabled IoT and edge computing”, Concurrency Computat Pract Exper, vol. 33, no. 18, Sep. 2021, doi: 10.1002/cpe.6466.
15. M. Bartnes, “Nettselskapers involvering av underleverandører i hendelseshåndtering ved cyberangrep”, Feb. 04, 2020 (accessed Mar. 16, 2022).
16. L. H. Flå, R. Borgaonkar, I. A. Tøndel, and M. Gilje Jaatun, “Tool-assisted Threat Modeling for Smart Grid Cyber Security”, in 2021 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA), Jun. 2021, pp. 1–8. doi: 10.1109/CyberSA52016.2021.9478258.
17. T. A. Zerihun, M. Garau, and B. E. Helvik, “Effect of Communication Failures on State Estimation of 5G-Enabled Smart Grid”, IEEE Access, vol. 8, pp. 112642–112658, 2020, doi: 10.1109/ACCESS.2020.3002981.
18. B. G. Gebraselase, C. M. Adrah, T. Amare, B. E. Helvik and P. E. Heegaard, “Blockchain Support For Time-Critical Self-Healing In Smart Distribution Grids,” IEEE/Novi Sad, Serbia/ ISGT Europe 2022.