The shift towards decentralized energy systems demands innovative strategies to manage renewable energy integration, optimize resource allocation, and ensure grid stability. This review investigates the application of game theory and robust predictive control as essential tools for decentralized and peer-to-peer energy management. Game theory facilitates strategic decision-making and cooperation among prosumers, distributors, and consumers, enabling efficient energy trading and dynamic resource distribution. Robust predictive control complements this by addressing uncertainties in renewable energy generation and demand, ensuring system stability through adaptive and real-time optimization. By examining recent advancements, this study highlights key methodologies, challenges, and emerging technologies such as blockchain, artificial intelligence, and digital twins, which enhance these approaches. The review also explores their alignment with global sustainability objectives, emphasizing their role in promoting affordable clean energy, reducing emissions, and fostering resilient urban energy infrastructures. A systematic review methodology was employed, analyzing 153 selected articles published in the last five years, filtered from an initial dataset of over 200 results retrieved from ScienceDirect and IEEE Xplore. Practical insights and future directions are provided to guide the implementation of these innovative methodologies in decentralized energy networks.

This paper proposes a real-time energy management strategy for low-voltage microgrids that combines short-horizon forecasting with a rule-based supervisory controller to coordinate battery energy storage usage and reactive power support provided by flexible alternating current transmission technologies. The central contribution is the forecast-informed, joint orchestration of active charging and reactive power dispatch to regulate voltage and preserve stability under large photovoltaic variability and uncertain electric vehicle demand. The work also introduces a resilience response index that quantifies performance under external disturbances, forecasting delays, and increasing levels of electric-vehicle integration. Validation is carried out through time-domain numerical simulations in MATLAB/Simulink using realistic solar irradiance and electric vehicle charging profiles. The results show that the coordinated strategy reduces voltage deviation events, maintains stable operation across a wide range of scenarios, and enables electric vehicle charging to be supplied predominantly by renewable generation. Sensitivity analysis further indicates that support from flexible alternating current devices becomes particularly decisive at high charging demand and in the presence of forecasting latency, underscoring the practical value of the proposed approach for distribution-level microgrids.