Description of the work completed in the reporting year and the scientific results obtained
In 2025, key work on the design and modeling of the energy-digital ecosystem architecture and on assessing the impact of implementing IT and digital solutions in the energy sector was completed under the project "Digital Transformation and Energy Transition: Symbiosis and Synergy of Technological Trends" (No. 24-28-01796).
A system of requirements and constraints for the energy-digital ecosystem architecture was developed. The system encompasses stakeholders, drivers, assessments, goals, principles, functional and non-functional requirements, as well as regulatory, physical, and organizational constraints. The description focuses on requirements for the functional structure, end-to-end processes, IT support, and technological infrastructure: asset monitoring and management, support for large telemetry streams, ensuring low latency for critical channels, data format and semantic requirements, as well as reliability, certification, and cybersecurity requirements. For practical use, a table framework and a motivational extension model in Archi (ArchiMate Motivation View) have been prepared, linking drivers to goals, requirements, and constraints.
A meta-model of the energy-digital ecosystem architecture has been developed—an abstract framework of entities, relationships, and rules that is universal for various technological implementations. The meta-model is based on the "generation → distribution → consumption" lifecycle and includes a physical and technical layer (assets, sensors, networks), a data and digital twin layer (telemetry, semantics, digital twins), an application layer (SCADA/EMS, data platforms, analytics, AI services), and a technology layer (cloud/edge solutions, networks, storage, security tools). The meta-model defines the rules for integrating layers, data exchange points, and key end-to-end control loops, ensuring the reproducibility of architectural solutions.
Based on the meta-model, a reference model of the architecture of a power generating company was created as an industry-wide, replicable structure, focused on the "generation" core and its connections to distribution and consumption. The reference model captures the following invariants: management of physical assets and digital twins, telemetry collection and storage, analytics and AI layers, integration buses, peripheral and cloud infrastructure, business processes, and regulatory frameworks. Specific implementation options for reference model elements are proposed for different generation types (thermal power plants, hydroelectric power plants, nuclear power plants, and renewable energy sources), ranging from thermal power plant fuel logistics to hydrological models of hydroelectric power plants and massively distributed edge systems for renewable energy sources.
For impact assessment, an integrated approach is proposed, combining three interrelated components: a methodology for calculating investment needs during the transition to a low-carbon economy, a methodology for investment assessment of internal IT projects of energy companies, and an approach to project activity and portfolio management. The methodology for calculating investment needs is based on economic and mathematical modeling of sectoral balance and takes into account both direct ("first-order") capacity costs and secondary investments in the production of this capacity. The model includes built-in mechanisms for assessing efficiency and sensitivity to input parameters. The methodology for evaluating internal IT projects utilizes KPI trees, traditional investment analysis tools, and sensitivity analysis to more accurately validate projects that do not always generate direct revenue but improve reliability and efficiency. The project management approach is recommended to adapt PMBOK/ISO-21500 standards by introducing the service design manager role and using multi-agent systems (MAS) for IT support of portfolio management, which increases flexibility and coordination across multiple concurrent initiatives.
Research methods and tools include analysis and synthesis, architectural modeling (Archi/ArchiMate), service-oriented analysis of socio-economic systems, data modeling, economic-mathematical modeling, KPI trees, and sensitivity analysis. The results are presented in tabular and graphical artifacts, accompanied by publications in the collection Lecture Notes in Networks and Systems (2025), and are available for practical validation and replication.
The research results form a methodological basis for designing and evaluating digital transformations in the energy sector, linking strategic decarbonization goals with architectural solutions, investment calculations, and project management.
Articles presenting research results:
- Bezruchko, D., Ilin, I., Sluzhaev, A., Esser, M. (2025). Methodology for Assessing the Economic Efficiency of Internal Investment Projects in Energy Sector Companies. In: Ilin, I., Youzhong, M. (eds) Digital Systems and Information Technologies in the Energy Sector. Lecture Notes in Networks and Systems, vol 1244. Springer, Cham. https://doi.org/10.1007/978-3-031-80710-7_4
- Ilin, I., Bezruchko, D., Rukina, P. (2025). Development of a Methodology for Assessing the Investment Needs of the Low-Carbon Economy. In: Ilin, I., Youzhong, M. (eds) Digital Systems and Information Technologies in the Energy Sector. Lecture Notes in Networks and Systems, vol 1244. Springer, Cham. https://doi.org/10.1007/978-3-031-80710-7_1
- Bezruchko, D., Ilin, I., Kudryavtseva, T., Gugutishvili, D. (2025). Economic Efficiency Evaluation of Digital Projects Management Improvement. In: Ilin, I., Youzhong, M. (eds) Digital Systems and Information Technologies in the Energy Sector. Lecture Notes in Networks and Systems, vol 1244. Springer, Cham. https://doi.org/10.1007/978-3-031-80710-7_9
- Tarasova, T., Levina, A., Shchenikov, E., Esser, M. (2025). Energy System Architecture Incorporating the Internet of Energy Solution. In: Ilin, I., Youzhong, M. (eds) Digital Systems and Information Technologies in the Energy Sector. Lecture Notes in Networks and Systems, vol 1244. Springer, Cham. https://doi.org/10.1007/978-3-031-80710-7_20
- Kalyazina, S., Ilin, I., Levina, A. (2025). A Multi-Agent System in the IT Architecture of Project Portfolio Management of an Energy Company. In: Ilin, I., Youzhong, M. (eds) Digital Systems and Information Technologies in the Energy Sector. Lecture Notes in Networks and Systems, vol 1244. Springer, Cham. https://doi.org/10.1007/978-3-031-80710-7_19