Development of web-based interface for dry-low emission gas turbine using raspberry Pi
MOCHAMMAD Faqih, JEREMY Peter James, MADIAH Binti Omar, ROSDIAZLI Bin Ibrahimdownload PDF
Abstract. In recent years, Dry-Low Emission (DLE) mode has been popular in gas turbine applications which can reduce emission production while maintaining high performance by operating the combustion at a low firing temperature. However, this type of combustor is prone to experience trips due to lean blowout occurrences and combustion instability. Dynamic simulation is needed to investigate the system’s behavior in mitigating the tripping problem. Therefore, this paper proposed a simulator of the DLE gas turbine using Raspberry Pi, which can be accessed through the local server. Rowen’s model is modified to represent the DLE gas turbine system, and its physical model is developed using open-source software, namely Scilab/XCos. The model is then attached to a web-based interface developed using Python and HTML programming language. The deployment of the web-based interface enables the gas turbine model to be accessed remotely without caring about the device’s location by connecting the mobile to the same Wi-Fi router. This simulator will help improve the technical know-how of DLE gas turbine operation and can be embedded in the plant control system as a predictive maintenance tool.
Dry-Low Emission Gas Turbine, Rowen’s Model, Scilab/XCos, Raspberry Pi, Python, HTML
Published online 5/20/2023, 9 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: MOCHAMMAD Faqih, JEREMY Peter James, MADIAH Binti Omar, ROSDIAZLI Bin Ibrahim, Development of web-based interface for dry-low emission gas turbine using raspberry Pi, Materials Research Proceedings, Vol. 29, pp 209-217, 2023
The article was published as article 24 of the book Sustainable Processes and Clean Energy Transition
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 Anheden, M. (2000). Analysis of gas turbine systems for sustainable energy conversion (PhD dissertation, Kemiteknik). Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-2914
 Olumayegun, O., Wang, M., & Kelsall, G. (2016). Closed-cycle gas turbine for power generation: A state-of-the-art review. Fuel, 180, 694-717. https://doi.org/10.1016/j.fuel.2016.04.074
 Hazel, T., Peck, G., & Mattsson, H. (2014). Industrial Power Systems Using Dry Low Emission Turbines. IEEE Transactions On Industry Applications, 50(6), 4369-4378. https://doi.org/10.1109/tia.2014.2346697
 Nemitallah, M., Rashwan, S., Mansir, I., Abdelhafez, A., & Habib, M. (2018). Review of Novel Combustion Techniques for Clean Power Production in Gas Turbines. Energy & Fuels, 32(2), 979-1004.
 Faqih, M., Omar, M. B., & Ibrahim, R. B. (2022, August). Development of Rowen’s Model for Dry-Low Emission Gas Turbine Dynamic Simulation using Scilab. In 2022 IEEE 5th International Symposium in Robotics and Manufacturing Automation (ROMA) (pp. 1-5). IEEE.
 Asgari, H., Chen, X., Morini, M., Pinelli, M., Sainudiin, R., Spina, P., & Venturini, M. (2016). NARX models for simulation of the start-up operation of a single-shaft gas turbine. Applied Thermal Engineering, 93, 368-376. https://doi.org/10.1016/j.applthermaleng.2015.09.074
 Omar, M., Ibrahim, R., Abdullah, M., & Tarik, M. (2018). Modelling and System Identification of Gas Fuel Valves in Rowen’s Model for Dry Low Emission Gas Turbine. 2018 IEEE Conference On Big Data And Analytics (ICBDA). https://doi.org/10.1109/icbdaa.2018.8629705
 Faqih, M., Omar, M. B., Ibrahim, R., & Omar, B. A. (2022). Dry-Low Emission Gas Turbine Technology: Recent Trends and Challenges. Applied Sciences, 12(21), 10922.
 Bahashwan, A. A., Ibrahim, R. B., Omar, M. B., & Faqih, M. (2022). The Lean Blowout Prediction Techniques in Lean Premixed Gas Turbine: An Overview. Energies, 15(22), 8343.
 Omar, M., Tarik, M. H. M., Ibrahim, R., & Abdullah, M. F. (2017, November). Suitability study on using rowen’s model for dry-low emission gas turbine operational performance. In TENCON 2017-2017 IEEE Region 10 Conference (pp. 1925-1930). IEEE.
 Tarik, M. H. M., Omar, M., Abdullah, M. F., & Ibrahim, R. (2017, November). Modelling of dry low emission gas turbine using black-box approach. In TENCON 2017-2017 IEEE Region 10 Conference (pp. 1902-1906). IEEE.
 Shalan, H. E., Hassan, M. M., and Bahgat, A. B. G. (2011). Parameter estimation and dynamic simulation of gas turbine model in combined cycle power plants based on actual operational data. J. Am. Sci. 7,303–310.
 Lima, Z., García-Vázquez, H., Rodríguez, R., Khemchandani, S., Dualibe, F., & del Pino, J. (2018). A System for Controlling and Monitoring IoT Applications. Applied System Innovation, 1(3), 26. https://doi.org/10.3390/asi1030026