Resources - AWS Prescriptive Guidance

Resources

AWS resources:

Ontology and case studies:

Additional reading:

  • Amasyali, Kadir, Mohammed Olama, and Aniruddha Perumalla. 2020. “A Machine Learning-based Approach to Predict the Aggregate Flexibility of HVAC Systems.” U.S. Department of Energy, Office of Scientific and Technical Information. https://www.osti.gov/servlets/purl/1632099.

  • Chen, Xianzhong et al. 2023. “Hot spot temperature prediction and operating parameter estimation of racks in data center using machine learning algorithms based on simulation data.” Building Simulation. https://doi.org/10.1007/s12273-023-1022-4.

  • Fu, Qiming et al. 2022. “Applications of reinforcement learning for building energy efficiency control: A review.” Journal of Building Engineering 50. https://doi.org/10.1016/j.jobe.2022.104165.

  • Wang, Huilong et al. 2022. "A machine learning-based control strategy for improved performance of HVAC systems in providing large capacity of frequency regulation service.” Applied Energy 326. https://doi.org/10.1016/j.apenergy.2022.119962.