Abstract
Photovoltaic (PV) inverters essentially convert DC quantities, such as voltage and current, to AC quantities whose magnitude and frequency are controlled to obtain the desired output. Thus, the performance of an inverter depends on its controller. Therefore, an optimum fuzzy logic controller (FLC) design technique for PV inverters using a lightning search algorithm (LSA) is presented in this study. In a conventional FLC, the procedure for obtaining membership functions (MFs) is usually implemented using trial and error, which does not lead to satisfactory solutions in many cases. Therefore, this study presents a technique for obtaining MFs that avoids the exhaustive traditional trial-and-error procedure. This technique is implemented during the inverter design phase by generating adaptive MFs based on the evaluation results of the objective function formulated with LSA. The mean squared error (MSE) of the inverter output voltage is used as an objective function in this study. LSA optimizes the MFs such that the inverter provides the lowest MSE for the output voltage, and the performance of the PV inverter output is improved in terms of amplitude and frequency. First, the design procedure and accuracy of the optimum FLC are illustrated and investigated through simulations conducted in a MATLAB environment. The LSA-based FLC (LSA-FL) are compared with differential search algorithm (DSA)-based FLC (DSA-FL) and particle swarm optimization (PSO)-based FLC (PSO-FL). Finally, the robustness of the LSA-FL is further investigated with a hardware that is operated via an eZdsp F28335 control board. Simulation and experimental results show that the proposed controller can successfully obtain the desired output when different loads are connected to the system. The inverter also has a reasonably low steady-state error and fast response to reference variation.
Highlights
Nowadays, renewable energy (RE) has become the main impetus of the energy sector, primarily because it is environment friendly, clean, and a secure energy source [1]
400 Figure the experiment is conducted in the laboratory to evaluate the overall are measured with differential probes with a scale (X200), as depicted the proposed fuzzy logic PV inverter controller
This paper has presented a novel nature‐inspired optimization technique called as the lightning search algorithm (LSA) to enhance the three‐phase
Summary
Renewable energy (RE) has become the main impetus of the energy sector, primarily because it is environment friendly, clean, and a secure energy source [1]. Given that PV generators can only supply DC power, an inverter is required to connect the load to PV generators [3]. Energies 2016, 9, 120 its capability to provide clean, high-quality power and constant amplitude sinusoidal voltage and frequency, regardless of the load type to which it is connected. A power inverter must have the capability to recover quickly from transients caused by external disturbances without causing power quality problems. In the context of a stand-alone PV generator, the output voltage and current waveforms should be controlled based on the reference values. An efficient PV inverter controller is required [4]. The extensive use of PV generators raises many challenges, such as harmonic pollutions, low efficiency of energy conversion, fluctuation of output power, and reliability of power electronic converters [5]
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