Harmonic Level Minimization Using Neuro-Fuzzy-Based SVPWM

摘要

Recently, the renewable energy systems play the major role to meet the electricity demand. The Distributed energy source provision of balance between the generation and distribution is an attractive research area in the (DES) for providing better power quality during the Distributed Energy Sources deployment. Hence, this paper focuses on the design of an efficient controlling structure to reduce the noise level in the output voltage. Due to the combination of two renewable resources, there is a need for special controlling architecture for switching devices under dynamic load conditions. The generation of the control signals through the Neuro Fuzzy with variations such as the rate of carrier frequency, duty cycle and the pulse position reduces the impulse response that leads to regulated power to the load. Based on the irradiance of the PV system and the torque variations in the induction motor system, the output from the Neuro Fuzzy- with three varied rate parameters as Rate of Carrier Frequency level (RCF), Ratio of Duty Cycle (RDC), and the Rate of Pulse Position (RPP) unit passes to the Space-Vector Pulse Width modulation (SVPWM) block for switching pulse generation. The difference between the frequency of reference and carrier signals has direct impact on the changes in the pulse width that leads to additional noise in the traditional controller techniques. Alternatively, the proposed work provides pulses to the switching devices based on rate analysis that leads to high switching speed and regulated output voltage. The comparative analysis between the proposed NFRRR-SVPWM with the existing methods states the effectiveness of the rate-based controlling technique in the development of renewable energy resources.