Bagasse-based cogeneration, which turns waste from the sugar industry into power and heat simultaneously, has become a vital renewable energy source. Recent years have seen a surge in technological advancements in this field due to growing demands for low-carbon trade, cost effectiveness, and sustainable energy. In bagasse-based cogeneration systems, artificial intelligence (AI) has started to revolutionize trade-oriented decision-making, energy forecasting, predictive maintenance, and operational efficiency. This study looks at how AI can be incorporated into bagasse-based cogeneration and how it could change the way that energy is traded internationally. The study examines how recent industrial practices, technical developments, and legislative frameworks impact the deployment of AI in bioenergy systems using a secondary data technique. The results demonstrate how AI improves energy reliability, lowers operational risks, and boosts the competitiveness of international trade in renewable energy. The study adds to the expanding body of knowledge on intelligent bioenergy systems and provides important information for stakeholders in international trade, energy producers, and policymakers.
R.Rathidevi et al. (Thu,) studied this question.