In the pursuit of sustainable and reliable energy, researchers are increasingly turning to artificial intelligence (AI) to enhance power quality in smart grids. A recent study published in the journal *Electric Power Systems Research* by Musawenkosi Lethumcebo Thanduxolo Zulu from the University of KwaZulu-Natal, Durban, South Africa, explores how AI can optimize the integration of renewable energy sources like solar photovoltaic (PV) and wind power into microgrids.
The study focuses on a power management strategy (PMS) called Inverter Control and Artificial Neural Network (ICANN) technique, which aims to improve power quality in DC–AC microgrids with PV-wind hybrid systems. “Inverter control is critical in distributed generation microgrids to achieve low operational costs and high reliability,” Zulu explains. “The application of artificial neural networks (ANNs) is vital in this context.”
The research highlights the growing importance of microgrids, which facilitate distributed energy resources (DERs) and form integrated energy coordination centered around critical clients. However, integrating and controlling multiple DERs while managing the energy transition presents significant challenges. Zulu’s study proposes a combined control strategy that leverages AI to enhance power quality, ensuring access to affordable, reliable, sustainable, and modern energy for all.
The simulations, conducted using MATLAB/SIMULINK, reveal promising results. Measures of inverter control, voltage levels (VL-L), and phase voltage root mean square (Vph_rms) indicate that the power generated from the hybrid microgrid is reliable. The technique produced satisfactory results, with the PV/wind hybrid microgrid system demonstrating stability and outstanding performance.
The implications of this research for the energy sector are substantial. As the world moves towards renewable energy sources, the need for efficient and reliable power management strategies becomes increasingly critical. AI techniques like ICANN can play a pivotal role in optimizing power quality and ensuring the stability of microgrids.
“This research is a step forward in the integration of renewable energy sources into the grid,” says Zulu. “It shows that AI can be a powerful tool in achieving sustainable and reliable energy systems.”
The study not only contributes to the advancement of power management strategies but also underscores the broader role of AI in achieving the United Nations’ Sustainable Development Goal 7 (SDG7), which aims to ensure access to affordable, reliable, sustainable, and modern energy for all.
As the energy sector continues to evolve, the integration of AI techniques like ICANN could shape future developments, paving the way for more efficient, reliable, and sustainable power systems. The research by Zulu and his team offers a glimpse into the potential of AI in transforming the energy landscape, making it a compelling narrative for professionals in the field.