Exploration of predictive models in optimising renewable energy integration in grid systems

Abstract

This study analyzes key trends in energy research by mapping keyword associations using network visualization and bibliometric data. The results show a strong relationship between technical aspects such as control systems and energy optimization with policy and sustainability. New technologies like blockchain and prosumers are increasingly integrated into energy systems to improve transparency and efficiency. In addition, grid stability and optimization of power system parameters are becoming significant in ensuring reliable and efficient system performance. Keywords such as sustainability, carbon neutrality, and renewable energy also show increasing attention to the transition to renewable sources. This study uses algorithms and artificial intelligence to emphasise the importance of technological innovation in energy system optimization and management. The conclusions of this analysis emphasize the need for a holistic approach that combines technical innovation, supportive energy policies, and a focus on sustainability to achieve a clean and efficient energy transition.