Intelligent Energy Management in Renewable-Integrated Smart Grids: A Review of Advanced Metering, Demand Response, Energy Storage and Ai-Based Forecasting

A sustainable electricity system must supply growing demand with an increasing share of solar, wind and hydro generation whose output cannot be scheduled at will. Balancing such a system depends less on adjusting a few large power plants and more on managing energy intelligently across millions of consumers, storage units and distributed generators. This review focuses on the demand side and the information layer of the smart grid. It examines advanced metering infrastructure, which provides two-way communication between utilities and consumers; demand response and demand-side management, which shift or reduce consumption in response to prices or signals; energy storage and electric vehicles, which absorb surplus renewable energy and release it when needed; and forecasting of load and renewable generation using statistical and machine-learning models. Representative studies on each topic are compared. A layered architecture for an intelligent energy management system is presented in which consumer devices, smart meters, communication networks, an energy management platform and utility services cooperate to minimise cost, losses and emissions while maintaining reliability. Communication requirements, cyber security, privacy and consumer participation are discussed as challenges, and directions such as reinforcement-learning-based demand response and local energy markets are identified.