Optimization of Internet of Things (IoT) for Smart Grid Energy Management Using Artificial Intelligence (AI) Techniques to Reach SDG7

The Sustainable Development Agenda for 2030, which was endorsed by all UN members, offers a strategic roadmap for a sustainable future and prosperity. All nations, regardless of economic standing, are urged to take action in response to the 17 Sustainable Development Goals (SDGs). This study centers on SDG7, which mandates affordable and sustainable energy availability. Power systems must satisfy the growing demand for improved quality and dependability in distribution networks while being sustainable, secure, and cost-effective. Artificial intelligence (AI) is the most effective method for managing massive data flows and storage in an Internet of Things (IoT) network. With the invention of high-speed internet networks and numerous smart sensors, the IoT is becoming increasingly popular. The world is shifting toward adopting renewable energy sources to generate electricity with the integration of AI and the IoT. This paper proposes an improved method for simulating an inverter-based microgrid using an Artificial Neural Network (ANN) and inverter control for optimization of the IoT for renewable energy management control of DC-AC microgrid with PV-Wind system to succeed in SDG7. MATLAB/Simulink is used for simulations and the results show optimization from the system Vph_max, VL-L, and Vph_rms.