PEMS for a Cogeneration Unit
Development of Predictive Emissions Monitoring Systems for a Cogeneration Unit
Project
My publications and projects:
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Minxing Si et al., 2021. Fuel consumption analysis and cap and trade system evaluation for Canadian in situ oil sands extraction. Renewable and Sustainable Energy Reviews, vol (146), 111145. DOI: https://doi.org/10.1016/j.rser.2021.111145. https://www.sciencedirect.com/science/article/abs/pii/S1364032121004342
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Minxing Si et al., 2021. Discovering Energy Consumption Patterns with Unsupervised Machine Learning for Canadian In Situ Oil Sands Operations. Sustainability, 13(4), 1968. DOI: 10.3390/su13041968. https://www.mdpi.com/2071-1050/13/4/1968. Download
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Minxing Si and Ke Du. 2020. Development of a predictive emissions model using a gradient boosting machine learning method. Environmental Technology & Innovation, vol. 20 (101028). DOI:10.1016/j.eti.2020.101028. https://www.sciencedirect.com/science/article/abs/pii/S2352186420313286. Download Preprint
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Minxing Si et al., 2020. Evaluation and calibration of a low-cost particle sensor in ambient conditions using machine-learning methods Atmospheric Measurement Techniques,vol. 13 (4). DOI: 10.5194/amt-13-1693-2020. https://www.atmos-meas-tech.net/13/1693/2020/. Download
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Minxing Si et al., 2019. Development of Predictive Emissions Monitoring System Using Open Source Machine Learning Library – Keras: A Case Study on a Cogeneration Unit. IEEE Access,vol. 7, pp. 113463-113475. DOI: 10.1109/ACCESS.2019.293055. https://ieeexplore.ieee.org/document/8771122. Download
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Shirley Thompson and Minxing Si. 2014. Energy efficiency assessment by process heating assessment and survey tool (PHAST) and feasibility analysis of waste heat recovery in the reheat furnace at a steel company. Renewable and Sustainable Energy Reviews, vol 40, 814 - 819.DOI: 10.1016/j.rser.2014.07.140. https://www.sciencedirect.com/science/article/abs/pii/S1364032111000839
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Minxing Si et al., 2011. Strategic analysis of energy efficiency projects: Case study of a steel mill in Manitoba. Renewable and Sustainable Energy Reviews, vol 5 (6), 2904 - 2908. DOI: 10.1016/j.rser.2011.02.035. https://www.sciencedirect.com/science/article/abs/pii/S1364032114005929
PEMS for a Steam Generator
Development of a predictive emissions model using a gradient boosting machine learning method
Evaluation and calibration of a low-cost particle sensor
Evaluation and calibration of a low-cost particle sensor in ambient conditions using machine-learning methods