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Internet of Things (IoTs) Evolutionary Computation, Enterprise Modelling and Simulation Read chapter Read first chapter

2020 | OriginalPaper | Chapter

13. An IoT-Based Controller Realization for PV System Monitoring and Control

Authors : Jyoti Gupta, Manish Kumar Singla, Parag Nijhawan, Souvik Ganguli, S. Suman Rajest

Published in: Business Intelligence for Enterprise Internet of Things

Publisher: Springer International Publishing

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Abstract

The increased penetration of PV-based micro-grid in distributed feeder system leads to power quality issues, especially under islanded condition. In this study, the artificial neural network is considered as the inverter control system in PV-based micro-grid, which is optimally placed in a 13-node feeder system. Artificial neural network (ANN) improves the performance and efficiency of the inverter and adjusts power quality. The proposed method is simulated through MATLAB/Simulink, and the results are compared for IoT-based PI and IoT-based ANN controllers. IoT-based systems are beneficial from the point of view of historical big data analysis for effective system planning and design. The total harmonic distortion, voltage, and phase angle variations are to be monitored and maintained within a satisfactory range for the enhancement of micro-grid power quality during grid-connected and islanded modes of operation.

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previous chapter An Algorithmic Approach to System Identification in the Delta Domain Using FAdFPA Algorithm
next chapter Development of an Efficient, Cheap, and Flexible IoT-Based Wind Turbine Emulator
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Metadata
Title
An IoT-Based Controller Realization for PV System Monitoring and Control
Authors
Jyoti Gupta
Manish Kumar Singla
Parag Nijhawan
Souvik Ganguli
S. Suman Rajest
Copyright Year
2020
Book
Business Intelligence for Enterprise Internet of Things

Print ISBN: 978-3-030-44406-8

Electronic ISBN: 978-3-030-44407-5

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-44407-5_13

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