Proceedings of the International scientific and practical conference ―Science, Technology and Culture in the Era of Globalization‖ (December 24-26, 2025) / Publisher website: www.naukainfo.com. – Geneva, Switzerland, 2026. – 234 p.

189 among distributed edge devices in order to improve the efficiency and reliability of energy systems. The role of federated learning in ensuring user privacy and increasing the adaptability of control algorithms is discussed. The article also explores the possibilities of integrating CEAI with blockchain and smart contract technologies, facilitating the development of transparent and secure platforms for energy trading and supports decentralized energy communities. This opens new prospects for optimizing energy production, storage, and consumption. Overall, the conducted analysis demonstrates that the convergence of local renewable energy generation and advanced digital solutions establishes a framework for developing more resilient and adaptive energy systems capable of effectively addressing global challenges and ensuring energy security. Keywords: decentralized energy, renewable energy sources, rooftop photovoltaic systems, energy resilience, edge AI, collaborative artificial intelligence, federated learning, solar energy, decentralized energy grids, energy security. Global transformations of energy systems in the 21st century are driven by the simultaneous impact of climate, economic, and security-related factors. High dependence on fossil fuels, the centralized nature of energy supply, and the increasing vulnerability of critical infrastructure during crises highlight the need for a transition toward more flexible and resilient energy supply models. In this context, renewable energy sources are regarded as a key component of the long-term transformation of the energy sector. The main types of renewable energy include solar, wind, hydropower, bioenergy and geothermal energy, each characterized by distinct technical, spatial, and economic attributes. Wind and hydropower have traditionally been associated with large-scale generation facilities that require substantial capital investment and connection to centralized grids. Bioenergy and geothermal technologies have limited territorial suitability and depend on local resource availability, which constrains their widespread implementation.