Artificial neural network-based power quality compensator

被引：0
作者：
Tekwani P.N. [1 ]
Chandwani A. [1 ]
Sankar S. [1 ]
Gandhi N. [1 ]
Chauhan S.K. [1 ]
机构：
[1] Department of Electrical Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat
来源：
International Journal of Power Electronics | 2020年 / 11卷 / 02期
关键词：
ANN; artificial neural network; Hysteresis current controller; Power quality; SAPF; Shunt active power filter;
D O I：
10.1504/IJPELEC.2020.105151
中图分类号：
学科分类号：
摘要：
A reliable and efficient adaptive neural network-based active power filter to estimate and compensate harmonic distortion from supply mains is presented in this paper. Nowadays, there is drastic rise of current and voltage harmonics in power systems, caused by nonlinear loads. Active power filters (APF) are used to mitigate harmonics and thereby, improve power quality. This paper deals with application of artificial neural network in shunt active power filter which provides ease in implementation and fast dynamic response compared to conventional active power filters. In depth analysis of neural network applications in the intelligent control and estimation for power quality compensation is presented in this paper. Here, both reference compensating current generation scheme as well as current controller for the active power filter are developed using artificial neural network technique. Effective compensation provided by the proposed artificial neural network-based shunt active power filter is proved through simulation results. Experimental analysis carried out using dSPACE DS1104 also validates power quality improvement by the proposed APF scheme. © 2020 International Journal of Power Electronics. All rights reserved.
引用
收藏
页码：236 / 255
页数：19
相关论文
共 20 条
  • [1] Abdeslam D.O., Wira P., Flieller D., Merckle J., Power harmonic identification and compensation with an artificial neural network method, IEEE International Symposium on Industrial Electronics, ISIE 2006, 3, pp. 1732-1737, (2006)
  • [2] Abdeslam D.O., Wira P., Merckle J., Flieller D., Chapuis Y.-A., A unified artificial neural network architecture for active power filters, IEEE Transactions on Industrial Electronics, February, 54, 1, pp. 61-76, (2007)
  • [3] Bhattacharya A., Chakraborty C., A shunt active power filter with enhanced performance using ANN-based predictive and adaptive controllers, IEEE Transactions on Industrial Electronics, February, 58, 2, pp. 421-428, (2011)
  • [4] Bose B.K., Neural network applications in power electronics and motor drives-An introduction and perspective, IEEE Transactions on Industrial Electronics, February, 54, 1, pp. 14-33, (2007)
  • [5] Chauhan S.K., Tekwani P.N., Current error space phasor based hysteresis controller for two-level and three-level converters used in shunt active power filters, Proc. 39th Annual Conference of the IEEE Industrial Electronics Society (IECON 2013), pp. 8514-8519, (2013)
  • [6] Esfahani M.T., Hosseinian S.H., Vahidi B., A new optimal approach for improvement of active power filter using FPSO for enhancing power quality, Elsevier International Journal of Electrical Power and Energy Systems, July, 69, pp. 188-199, (2015)
  • [7] Gill P., Electrical Power Equipment Maintenance and Testing, pp. 715-759, (2008)
  • [8] Goud G.S., Joshi A.L., Artificial neural network controlled shunt active power filter for power quality improvement, International Research Journal of Engineering and Technology (IRJET), July, 2, 4, pp. 377-383, (2015)
  • [9] Hingorani N.G., Flexible ac transmission, IEEE Spectrum, April, 30, 4, pp. 40-45, (1993)
  • [10] Janggi J.M., Utomo W.M., Yusoh M.A.T.M., Mahadan M.E., Zulkifli S.A., Jumadril J.N., Artificial neural network controller for single-phase active power filter, 2014 IEEE Conference on Energy Conversion (CENCON), pp. 25-30, (2014)
12