Abstract
In this paper, the voltage regulation of large-scale grid-tied photovoltaic power plant (GTPVPP) operating during nonlinear PV generation has been discussed. This research proposes the comparative voltage regulation of a novel multilevel inverter with soft-computing techniques such as fuzzy and adaptive neuro-fuzzy inference system (ANFIS)-based control for regulating the voltage of GTPVPP. Due to the interruptible PV generation and at worst-case scenarios, the proposed control scheme is useful to satisfy the load demand by grid integration. In this comparison, the ANFIS-based control scheme improves the dynamic performance, reduces the THD, and improves the efficiency. The fuzzy and proposed ANFIS-based control schemes are developed in MATLAB/Simulink environment and are compared at worst-case solar generation, rapid change of loads, and grid faults.
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Lova Lakshmi, T., Gopichand Naik, M. (2019). Soft-Computing Techniques for Voltage Regulation of Grid-Tied Novel PV Inverter at Different Case Scenarios. In: Wang, J., Reddy, G., Prasad, V., Reddy, V. (eds) Soft Computing and Signal Processing . Advances in Intelligent Systems and Computing, vol 898. Springer, Singapore. https://doi.org/10.1007/978-981-13-3393-4_19
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DOI: https://doi.org/10.1007/978-981-13-3393-4_19
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