Intelligent Pairing of Electric Vehicles and Renewable Energy Integration in Smart Grid

This thesis develops simple, intelligent control methods to manage electric vehicles and rooftop solar power in local electricity networks. It addresses problems caused by fluctuating charging demand and solar generation, such as voltage instability and network congestion. The research uses machine learning and local measurements to control vehicle charging, support network voltage, and coordinate substation equipment in real time. These methods reduce the need for complex communication systems. The work shows that coordinated control improves power quality, reduces costs for users, and supports wider adoption of electric vehicles and renewable energy.