The development and application of bioenergy and biofuels conversion technology can play a significant role for the production of renewable and sustainable energy sources in the future. However, the complexity of bioenergy systems and the limitations of human understanding make it difficult to build models based on experience or theory for accurate predictions. Recent developments in data science and machine learning (ML), can provide new opportunities. Accordingly, this critical review provides a deep insight into the application of ML in the bioenergy context. The latest advances in ML assisted bioenergy technology, including energy utilization of lignocellulosic biomass, microalgae cultivation, biofuels conversion and application, are reviewed in detail. The strengths and limitations of ML in bioenergy systems are comprehensively analysed. Moreover, we highlight the capabilities and potential of advanced ML methods when encountering multifarious tasks in the future prospects to advance a new generation of bioenergy and biofuels conversion technologies.

生物能源和生物燃料转化技术的开发和应用，对于未来可再生和可持续能源的生产将发挥重要作用。然而，生物能源系统的复杂性和人类理解的局限性使得基于经验或理论构建模型以进行准确预测变得困难。数据科学和机器学习 (ML) 的最新发展可以提供新的机会。因此，这篇批判性评论对机器学习在生物能源领域的应用提供了深入的了解。详细综述了ML辅助生物能源技术的最新进展，包括木质纤维素生物质能源利用、微藻培养、生物燃料转化与应用等。全面分析了 ML 在生物能源系统中的优势和局限性。