Guest Editors
Prof. Dr. Saidjon S. Tavarov
Email: tabarovsaid@mail.ru
Affiliation: Polytechnic Institute, South Ural State University, Chelyabinsk, Russia
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Research Interests: renewable energy forecasting, power system reliability, stochastic modelling, grid integration of PV and wind, LSTM and GARCH applications in energy
Prof. Dr. Alexander I. Sidorov
Email: sidorovai@susu.ru
Affiliation: Department of Life Safety, South Ural State University, Chelyabinsk, Russia
Homepage:
Research Interests: power system safety, electrical installation maintenance, occupational safety in energy sector, protection systems in urban and industrial grids
Summary
1) Background and Importance
The global transition toward decarbonization and the radical shift in the structure of generation capacities have placed modern power systems under unprecedented stress. The integration of renewable energy sources (RES) through inverter-based interfaces significantly reduces equivalent system inertia, leading to increased vulnerability and high-frequency power fluctuations. Traditional deterministic approaches are no longer sufficient to ensure static and dynamic stability in the face of the stochastic and heteroscedastic nature of solar and wind generation. For regions with complex orography and high reliance on hydropower, such as Tajikistan and other Central Asian countries, the challenge is intensified by the need to synchronize volatile RES schedules with water-energy balances. Addressing these uncertainties through advanced mathematical modeling and digital transformation is critical for the resilience of future energy infrastructures.
2) Aim and Scope
This Special Issue aims to provide a platform for researchers and practitioners to present innovative solutions for forecasting, modeling, and optimizing power systems with a high share of RES. We seek to bridge the gap between theoretical stochastic mathematics and practical dispatch control. The scope encompasses the development of hybrid intelligence models, entropy-based complexity assessments, and predictive management strategies that enhance the reliability and safety of modern grids. We encourage submissions that offer both high scientific novelty and practical applicability to real-world power system operations.
3) Suggested Themes
We invite original research, case studies, and review articles on topics including, but not limited to:
· Hybrid Stochastic Models: Integration of Deep Learning (LSTM, CNN) with econometric models (GARCH) for high-precision RES forecasting.
· Uncertainty Quantification: Entropy-based analysis and probabilistic (interval) forecasting of non-stationary energy processes.
· Grid Resilience and Safety: Advanced safety protocols and reliability assessments for decentralized and urban electrical networks.
· Operational Optimization: Predictive spinning reserve management and water-energy balance optimization in hydro-solar cascades.
· Digital Transformation: Implementation of "Smart Forecaster" modules and AI-driven algorithms into Automated Dispatch Control Systems (ADCS/SCADA).
· Stability Analysis: Impact of low-inertia RES integration on system frequency and voltage stability.
· Climate-Adaptive Energy Systems: Modeling the effects of extreme weather and complex terrain on renewable generation patterns.
Keywords
renewable energy integration, stochastic forecasting, hybrid LSTM-GARCH models, power system stability, uncertainty quantification, smart grid & ADCS, energy resource management
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