Applications of Artificial Intelligence Blockchain & ML for Microgrid Optimization Grid in Pakistan

the need for power solutions has increased due to the fast growth of distributed energy resources (DERs) and the growing demand for sustainable power solutions has accelerated the need for Microgrids as a reliable and efficient energy infrastructure. In Pakistan power distribution system is centralized and suffer from huge losses and these losses government recover from public. Due to these issues electricity is very expensive compared to any other country. The modern techniques can be adopted to resolve these issues such as by implementing distributed energy resources and modern algorithms AI and ML. In this paper we explore energy trading and power control in Microgrids using modern technologies, with a particular focus on the application of Artificial Intelligence (AI) and Machine Learning (ML) techniques. AI and ML enable real-time data analytics, predictive modeling, and automated decision-making, which are essential for optimizing energy generation, storage, and consumption within Microgrids. The integration of intelligent algorithms facilitates dynamic pricing, peer-to-peer (P2P) energy trading, and adaptive power flow control to ensure cost efficiency, reliability, and resilience. Furthermore, the use of reinforcement learning, deep learning, and forecasting models enhances demand prediction, fault detection, and optimal scheduling. The study also focuses on, how modern AI and ML driven approaches can revolutionize Microgrids management, enabling decentralized, autonomous and economically viable energy ecosystems.