Power quality enhancement in single phase two level/five level converters using adaptive-RBFNN algorithm

This paper presents Adaptive Radial Basis Function Neural Network (A-RBFNN) algorithm for the control of two level and five level converters. This paper investigates the performance of five level cascaded H-bridge (CHB) multilevel converter as compared to two level converters in power distribution system to improve power quality of connected system. The CHB multilevel inverter is a popular configuration because of its wide application for high power medium voltage requirement. The power system including two level (2L) and five level (5L) converter is modeled in MATLAB environment. Experimental setup is also developed in the laboratory for hardware verification purpose and both the 2L and 5L CHB converters are integrated to single phase system as compensators. The A-RBFNN algorithm is able to regulate the DC link voltages to its rated value for two H-bridges in 5L configuration. The designed algorithm is able to compensate for PQ issues of the connected system. It is also tested under steady state and dynamic conditions. Further, A-RBFNN is used to extract individual harmonics of any desired order. Finally, comparison is presented based on the performance results of the proposed algorithm with 2L as well as 5L converters.