Department of Engineering, School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, 47500, Selangor Darul Ehsan, Malaysia; Tan Sri Leo Moggie Distinguished Chair in Energy Informatics, Institute of Informatics and Computing in Energy (IICE), Universiti Tenaga Nasional (UNITEN), Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia.
Department of Engineering, School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, 47500, Selangor Darul Ehsan, Malaysia.
J Environ Manage. 2024 Sep;368:122085. doi: 10.1016/j.jenvman.2024.122085. Epub 2024 Aug 14.
The production of renewable biofuel through microalgae and green technology can be a promising solution to meet future energy demands whilst reducing greenhouse gases (GHG) emissions and recovering energy for a carbon-neutral bio-economy and environmental sustainability. Recently, the integration of Energy Informatics (EI) technology as an emerging approach has ensured the feasibility and enhancement of microalgal biotechnology and bioenergy applications. Integrating EI technology such as artificial intelligence (AI), predictive modelling systems and life cycle analysis (LCA) in microalgae field applications can improve cost, efficiency, productivity and sustainability. With the approach of EI technology, data-driven insights and decision-making, resource optimization and a better understanding of the environmental impact of microalgae cultivation could be achieved, making it a crucial step in advancing this field and its applications. This review presents the conventional technologies in the microalgae-based system for wastewater treatment and bioenergy production. Furthermore, the recent integration of EI in microalgal technology from the AI application to the modelling and optimization using predictive control systems has been discussed. The LCA and techno-economic assessment (TEA) in the environmental sustainability and economic point of view are also presented. Future challenges and perspectives in the microalgae-based wastewater treatment to bioenergy production integrated with the EI approach, are also discussed in relation to the development of microalgae as the future energy source.
通过微藻和绿色技术生产可再生生物燃料，可以成为满足未来能源需求的有前途的解决方案，同时减少温室气体（GHG）排放，并为碳中和的生物经济和环境可持续性回收能源。最近，能源信息学（EI）技术的集成作为一种新兴方法，确保了微藻生物技术和生物能源应用的可行性和增强。在微藻领域应用中集成 EI 技术，如人工智能（AI）、预测建模系统和生命周期分析（LCA），可以提高成本、效率、生产力和可持续性。通过 EI 技术的方法，可以实现数据驱动的洞察和决策、资源优化以及更好地了解微藻培养的环境影响，这是推进该领域及其应用的关键步骤。本文综述了基于微藻的废水处理和生物能源生产系统中的常规技术。此外，还讨论了最近从 AI 应用到使用预测控制系统进行建模和优化的 EI 在微藻技术中的集成。还从环境可持续性和经济角度介绍了生命周期分析（LCA）和技术经济评估（TEA）。还讨论了与将微藻作为未来能源的发展相关的，基于微藻的废水处理到生物能源生产与 EI 方法相结合的未来挑战和前景。
