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Evaluation of Two Distinct AI Control Methods to Enhance Power Quality

A. Mohan Sai, E. Pavan Kumar, B. Nandha Kishor Naik, P. Bala Chandra Prasad, S. Vasanth, L. Anitha

Abstract


Artificial Intelligence techniques are the latest techniques utilized for the improvement of electrical performance. This study examines and contrasts various artificial harmonic reduction methods for source current. Artificial Intelligence may include Fuzzy logic and Artificial Neural Network. The goal of the modeling is to improve the power quality through the application of principles that cannot be expressed as "true" or "false" but rather as "partially true" called as Fuzzy logic and intelligent features of the neuron cell. Shunt Active Filter is one of the controller that can be used for suppress the source current harmonics and compensates the reactive power. Voltage Source Inverter switching is controlled by a hysteresis current converter. In order to produce the reference compensatory current, the D-Q Frame theory is employed. By utilizing the power system tools, simulations are performed in the MATLAB environment.


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References


Bhim Singh and Jitendra Solanki, ”A Comparison of Control Algorithms for DSTATCOM,” IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 56, NO. 7, pp. 2738 – 2745, JULY 2009.

Alka Singh and Bhim Singh, “Power Quality Issues related to Distributed Energy Source Integration to Utility Grids,”Annual IEEE India Conference (INDICON), December 2010.

R. Deepak Singh, T. Praveen Kumar, Dr.K.Sumanth,” Simulation of SRF Based DSTATCOM With Grid Connected PV Generation System Using Fuzzy Logic Controller For Reactive Power Management,” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol 5, NO.7, pp 6493-6501,July 2016.

H. Prasad and T. D. Sudhakar, “Power Quality Improvement by Mitigation of Current Harmonics using D – STATCOM,” Third International Conference on Science Technology Engineering & Management (ICONSTEM), March 2017.

Bhim Singh and Sabha Raj Arya, “Back-Propagation Control Algorithm for Power Quality Improvement using DSTATCOM,” IEEE Transactions on Industrial Electronics, vol. 61 ,No. 3 , pp. 1204 – 1212, March 2014.

B. Singh, A. Chandra and K. Al-Haddad, Power Quality: Problems and Mitigation Techniques, John Wiley and Sons, U.K., 2015.

Ankita Arora and Prerna Gaur,”Comparison of ANN and ANFIS based MPPT Controller for grid connected PV systems,” Annual IEEE India Conference (INDICON), December 2015.

Manoj Badoni, Alka Singh and Bhim Singh, “Adaptive Neuro Fuzzy Inference System Least Mean Square Based Control Algorithm for DSTATCOM,” IEEE Transactions on Industrial Informatics, vol. 12, no. 2, pp. 483 – 492, April 2016.

Yang Xiao-ping, Zhong Yan-ru and Wang Yan,” A Novel Control Method for DSTATCOM Using Artificial Neural Network,” CES/IEEE 5th International Power Electronics and Motion Control Conference, August 2006


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