LAPSE:2023.8532
Published Article
LAPSE:2023.8532
Flexible Power Point Tracking Using a Neural Network for Power Reserve Control in a Grid-Connected PV System
Jishu Mary Gomez, Prabhakar Karthikeyan Shanmugam
February 24, 2023
Abstract
Renewable energy penetration in the global energy sector is in a state of steady growth. A major criterion imposed by the regulatory boards in the wake of electronic-driven power systems is frequency regulation capability. As more rooftop PV systems are under installation, the inertia response of the power utility system is descending. The PV systems are not equipped inherently with inertial or governor control for unseen frequency deviation scenarios. In the proposed method, inertial and droop frequency control is implemented by creating the necessary power reserve by the derated operation of the PV system. While, traditionally, PV systems operate in normal MPPT mode, a derated PV system follows a flexible power point tracking (FPPT) algorithm for creating virtual energy storage. The point of operation for the FPPT of the PV is determined by using a neural network block set available in MATLAB. For the verification of the controller, it is applied to a PV array in a modified IEEE-13 bus system modeled in the MATLAB/Simulink platform. The simulation results prove that when the proposed control is applied to the test network with renewable energy penetration, there is an improved system inertia response.
Keywords
derated PV systems, FPPT, frequency response, IEEE-13 bus system, inertia response, microgrid systems, MPPT, neural network, photovoltaic systems, renewable energy systems
Suggested Citation
Gomez JM, Shanmugam PK. Flexible Power Point Tracking Using a Neural Network for Power Reserve Control in a Grid-Connected PV System. (2023). LAPSE:2023.8532
Author Affiliations
Gomez JM: School of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India
Shanmugam PK: School of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India
Journal Name
Energies
Volume
15
Issue
21
First Page
8234
Year
2022
Publication Date
2022-11-04
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en15218234, Publication Type: Journal Article
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LAPSE:2023.8532
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https://doi.org/10.3390/en15218234
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