101. A novel adaptive invasive weed optimization technique and least square regression for harmonics minimization in standalone PV applications.
- Author
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Ahmad Ganie, Zahoor, Hamid Bhat, Abdul, and Ahmad, Salman
- Subjects
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MATHEMATICAL optimization , *DIGITAL signal processing , *INDUCTION motors , *LEAST squares , *NONLINEAR equations , *ELECTRIC inverters , *IDEAL sources (Electric circuits) - Abstract
Summary: A novel adaptive invasive weed optimization technique is presented in this paper for harmonics minimization in standalone system based on three‐phase two‐level voltage source inverter. The low switching frequency techniques are preferred to produce good quality waveform and at the same time to reduce the switching losses and device stresses. Nonetheless, the challenging task is to compute the firing angles from the set of highly nonlinear transcendental system of equations. The proposed technique shows faster convergence and capability to compute in wide rage of modulation index. Moreover, multiple solutions also have been obtained in most of the range of modulation index. Various cases have been evaluated and simulation results have been given to validate conceptual results. The closed loop operation and the real‐time implementation of the proposed technique under dynamic operating conditions have been verified for a three‐phase induction motor load using PI controller. The least square regression is used for real‐time implementation of the proposed technique. The TMS320F2812 digital signal processor (DSP) has been employed to generate the pulse width modulated pulses generated from the computational results. The experimental results obtained are in very close concurrence to the computational and simulation results. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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