Abstract
This paper proposes an intelligent technique-based optimal controller for harmonics mitigation to maintain the power quality in renewable energy source (RES)-based distribution systems. The proposed intelligent technique is the joint execution of both the fractional-order proportional integral controller and moth-flame optimization with random decision forest. In the proposed approach, moth-flame optimization optimizes the dataset of fundamental and harmonic loop parameters such as terminal voltage and direct current voltage present in the hybrid shunt active power filter. The dataset is generated based on the linear and nonlinear load variation and parameter variation of the renewable energy sources, subject to the minimum error objective function. Based on the accomplished dataset, random decision forest accurately predicts the parameters and produces optimized control signals. The proposed technique guarantees the system with less complexity for the harmonics mitigation of the power quality event and hence the accuracy of the system is raised. Then, the proposed model is executed in the Matrix Laboratory/Simulink working platform and the execution is assessed with the existing techniques. The simulation analysis of the proposed approach is tested using the six test cases with various combinations of nonlinear loads. In all the test cases, the performance of various system parameters, such as source current with and without filter, source voltage, hybrid shunt active power filter current, load current and voltage, is analysed. Furthermore, the total harmonic distortion at different load ratings is also examined.
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More From: Transactions of the Institute of Measurement and Control
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