Performance improvement of hydraulic turbine generation system using subdivided finite set model predictive current control


Vol. 22, No. 8, pp. 1386-1397, Aug. 2022
10.1007/s43236-022-00462-6




 Abstract

This paper proposes performance improvement of hydraulic turbine generation system (HTGS) using a subdivided finite set model predictive current control (SFS-MPCC). Recently, the differential pressure control valve (DPCV) is replaced by HTGS because of the frequent breakdown in DPCV caused by cavitation in the district heating systems. The HTGS consists of the hydraulic turbine, permanent magnet synchronous generator (PMSG), back-to-back (BTB) converter, and three-phase grid. Especially, BTB converter is composed of a generator-side inverter, DC-link capacitor, and grid-side inverter. In the generator-side inverter, a model predictive current control (MPCC) has been widely used because of its many advantages, such as robustness from parameter variation, fast dynamic response, and unnecessariness of gain tuning. The conventional MPCC uses only eight voltage vectors; thus, it makes a large current ripple, which is directly related to torque ripple. Therefore, to reduce the current and torque ripple, SFS-MPCC, which uses subdivided voltage vectors is proposed. An additional algorithm to reduce the calculation time is proposed because the subdivided voltage vectors increase the calculation time excessively. The effectiveness of the proposed SFS-MPCC is demonstrated by simulation and experimental results.


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Cite this article

[IEEE Style]

Y. J. Lee, Y. Bak, K. Lee, "Performance improvement of hydraulic turbine generation system using subdivided finite set model predictive current control," Journal of Power Electronics, vol. 22, no. 8, pp. 1386-1397, 2022. DOI: 10.1007/s43236-022-00462-6.

[ACM Style]

Young Jae Lee, Yeongsu Bak, and Kyo-Beum Lee. 2022. Performance improvement of hydraulic turbine generation system using subdivided finite set model predictive current control. Journal of Power Electronics, 22, 8, (2022), 1386-1397. DOI: 10.1007/s43236-022-00462-6.