@inproceedings{f36b2bf985ca4d54903ab67fe5feb011,
title = "Optimizing boiler control in real-time with machine learning for sustainability",
abstract = "In coal-fired power plants, it is critical to improve the operational efficiency of boilers for sustainability. In this work, we formulate real-time boiler control as an optimization problem that looks for the best distribution of temperature in different zones and oxygen content from the flue to improve the boiler's stability and energy efficiency. We employ an efficient algorithm by integrating appropriate machine learning and optimization techniques. We obtain a large dataset collected from a real boiler for more than two months from our industry partner, and conduct extensive experiments to demonstrate the effectiveness and efficiency of the proposed algorithm.",
keywords = "Boiler Control, Combustion Optimization, Sustainability",
author = "Yukun Ding and Jinglan Liu and Jinjun Xiong and Meng Jiang and Yiyu Shi",
note = "Publisher Copyright: {\textcopyright} 2018 Association for Computing Machinery.; 27th ACM International Conference on Information and Knowledge Management, CIKM 2018 ; Conference date: 22-10-2018 Through 26-10-2018",
year = "2018",
month = oct,
day = "17",
doi = "10.1145/3269206.3272024",
language = "English",
series = "International Conference on Information and Knowledge Management, Proceedings",
publisher = "Association for Computing Machinery ",
pages = "2147--2154",
editor = "Norman Paton and Selcuk Candan and Haixun Wang and James Allan and Rakesh Agrawal and Alexandros Labrinidis and Alfredo Cuzzocrea and Mohammed Zaki and Divesh Srivastava and Andrei Broder and Assaf Schuster",
booktitle = "CIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management",
address = "United States",
}