Document Type : Research Paper

Authors

1 Mechanical Engineering Dept., University of Muhammadiyah Malang, Indonesia.

2 Kebon Agung Sugar Factory Malang, Indonesia.

3 Mechanical Engineering Dept., Brawijaya University, Indonesia.

Abstract

Induction motors and steam turbines are the main components in the sugar cane milling process. This study analyzes the efficiency of induction motors and steam turbines as mill drives at the Kebon Agung Sugar Factory in Malang, Indonesia. This study used experimental methods by observing and testing at the Kebon Agung Sugar Factory. The induction motors analyzed were mills 1, 2, and 5. Meanwhile, the steam turbines analyzed were cane cutter 1, 2, heavy-duty hammer shredder, mill 3, and mill 4. Motor and turbine data were obtained through the control system. Furthermore, the motor and turbine data are processed, and the efficiency comparison is calculated. From the results of the analysis, the average value of the efficiency of an induction motor is more significant when compared to a steam turbine. The average weight of induction motor efficiency is 94.6%, and the average value of steam turbine efficiency is 77.2%. This research recommends that the Kebon Agung Sugar Factory replace the steam turbine with an induction motor in the future. The recommendation given to Kebon Agung Sugar Factory is the use of induction motors on CC 1, CC 2, HDHS, mill 1, and mill 5. An induction motor is a relatively easy install compared to a steam turbine; the construction is robust and highly efficient, requires minimal maintenance, and does not require special equipment during operation.

Graphical Abstract

Highlights

  • The average value of induction motor efficiency was found to be 94.6%
  • The average value of steam turbine efficiency was found to be 77.2%
  • Induction motors in sugarcane milling machines are more efficient than steam turbines

Keywords

Main Subjects

  1. Mudzofar and A. Bowo, Analisis Determinan Impor Gula Indonesia, Efficient: Indonesian J. Dev. Econ., 3 (2020) 880–893.
  2. Wibowo, Energy balance analysis on increasing the capacity of a sugar factory in Indonesia, IOP Conf. Ser.: Earth Environ. Sci., IOP Publishing Ltd, Jan. 2022. https://doi.org/10.1088/1755-1315/963/1/012011
  3. A. Sulaiman, Y. Sulaeman, N. Mustikasari, D. Nursyamsi, and A. M. Syakir, Increasing sugar production in Indonesia through land suitability analysis and sugar mill restructuring, Land, 8 (2019) 61. https://doi.org/10.3390/land8040061
  4. Gangsar and R. Tiwari, Signal based condition monitoring techniques for fault detection and diagnosis of induction motors: A state-of-the-art review, Mech. Syst. Signal Process., 144 (2020) 106908. http://dx.doi.org/10.1016/j.ymssp.2020.106908
  5. Kurnia Pratama, E. Zondra, and H. Yuvendius, Analisis Efisiensi Motor Induksi Tiga Phasa Akibat Perubahan Tegangan, J. Sci. Energy. Technol., 5 (2020) 35–43.
  6. R. Gómez , V. Sousa, J. J. Cabello Eras, A.  S.  Gutiérrez b, P.  R. Viego, E. C. Quispe and G.  de León , Assessment criteria of the feasibility of replacement standard efficiency electric motors with high-efficiency motors, Energy, 239 (2022) 121877. http://dx.doi.org/10.1016/j.energy.2021.121877
  7. Sousa Santos, J. J. Cabello Eras, A. Sagastume Gutierrez, and M. J. Cabello Ulloa, Assessment of the energy efficiency estimation methods on induction motors considering real-time monitoring, Measurement, 136 (2019) 237–247. https://doi.org/10.1016/j.measurement.2018.12.080
  8. P. de Carvalho et al., A method for real-time wireless monitoring of the efficiency and conditions of three-phase induction motor operation, Electr. Power Syst. Res., 157 (2018) 70–82. https://doi.org/10.1016/j.epsr.2017.12.009
  9. M. Stopa, M. R. Resende, A. S. A. Luiz, J. C. G. Justino, G. G. Rodrigues, and B. J. Cardoso Filho, A Simple Torque Estimator for In-Service Efficiency Determination of Inverter-Fed Induction Motors, IEEE Trans. Ind. Appl., 56 (2020) 2087–2096. http://dx.doi.org/10.1109/TIA.2019.2963832
  10. Garcia, P. A. Panagiotou, J. A. Antonino-Daviu, and K. N. Gyftakis, Efficiency assessment of induction motors operating under different faulty conditions, IEEE Trans. Ind. Electron., 66 (2019) 8072–8081. https://doi.org/10.1109/TIE.2018.2885719
  11. K. Baqir, Performance Analysis of Three Phase Cascaded Multi-level Inverter (CMLI) for Induction Motor Drives, Eng. Tech. J., 31 (2013) 2531–2547. https://doi.org/10.30684/etj.31.13A.10
  12. Medica-Viola, V. Mrzljak, N. Anđelić, and M. Jelić, .Analysis of low-power steam turbine with one extraction for marine applications,. Nase More, 67 (2020) 87–95. https://doi.org/10.17818/NM/2020/2.1
  13. Permana and I. Kurniawan, Analisis Perhitungan Daya Turbin Yang Dihasilkan Dan Efisiensi Turbin Uap Pada Unit 1 Dan Unit 2 Di Pt. Indonesia Power Uboh Ujp Banten 3 Lontar, J. Tek. Mesin, 1( 2017)1-8. https://doi.org/10.31000/mbjtm.v1i2.731
  14. Chantasiriwan, The improvement of energy efficiency of cogeneration system by replacing desuperheater with steam–air preheater, Energy Rep., 6 (2020) 752–757. https://doi.org/10.1016/j.egyr.2020.11.135
  15. Mrzljak, Low Power Steam Turbine Energy Efficiency and Losses During the Developed Power Variation, Tehnički glasnik, 12 (2018) 174–180. https://doi.org/10.31803/tg-20180201002943
  16. R. Hasan and M. J. Salih, Modeling and Simulation of the Cogeneration Plant Equipped with Back-Pressure Turbine Operates at Various Control Programs of Exit Steam Temperature, Eng. Technol. J., 31 (2013) 3007–3034.
  17. Mrzljak and I. Poljak, Energy analysis of main propulsion steam turbine from conventional lng carrier at three different loads, Nase More, 66 (2019) 10–18. https://doi.org/10.17818/NM/2019/1.2
  18. Medica-Viola, V. Mrzljak, N. Anđelić, and M. Jelić, Analysis of low-power steam turbine with one extraction for marine applications, Nase More, 67 (2020) 87–95. https://doi.org/10.17818/NM/2020/2.1
  19. Sertsöz, M. Fidan, and M. Kurban, Efficiency Estimation of Induction Motors at Different Sizes with Artificial Neural Networks and Linear Estimation Using Catalog Values, Anadolu Univ. J. Sci. Technol. A – Appl. Sci.  Eng., 19 (2018) 293 - 302. https://doi.org/10.18038/aubtda.333118