Local Mean Decomposition Based Passive Islanding Detection for Utility Grid Interfaced PV Inverter

The significant utilization of Photovoltaic energy resource (PV) within the distribution grid is exponentially rising over past decades. The adoption of PV sources into utility grid introduces several challenges, one of which is the issue of Islanding. This paper focus on current signals that are ex...

Full description

Saved in:
Bibliographic Details
Published in2024 International Conference on Computational Intelligence for Green and Sustainable Technologies (ICCIGST) pp. 1 - 4
Main Authors Koduri, Omkar, Duvvuri, Sssr Sarathbabu, Madhuri, Sagiraju Geetha, Malladi, Srikanth, Varma, Sagiraju Dileep Kumar, NarasimhaRaju, V S N
Format Conference Proceeding
LanguageEnglish
Published IEEE 18.07.2024
Subjects
Couplings
Energy resources
Hilbert Transform
Indexes
Induction motors
Inverters
Islanding
Islanding Detection
Local Mean Decomposition
Photovoltaic systems
Signal processing algorithms
Switches
Transforms
Utility Grid Interfaced PV system
Online AccessGet full text

Cover

More Information
Summary:The significant utilization of Photovoltaic energy resource (PV) within the distribution grid is exponentially rising over past decades. The adoption of PV sources into utility grid introduces several challenges, one of which is the issue of Islanding. This paper focus on current signals that are extracted from the Point of common coupling (PCC) of grid connected PV system. Local mean decomposition (LMD), an adaptive signal processing detection technique, is developed to further extract rich and relevant characteristics from the extracted current signals. LMD produces a sequence of product functions (PFs). From obtained PFs, to identify the most suitable PF, which it passes in to Hilbert Transform(HT) to compute the energy index from which to detect the islanding or non-islanding condition. The effectiveness of proposed algorithm is validated with different active/reactive power mismatches and different non-islanding conditions like load switching and Induction motor starting etc.
DOI:10.1109/ICCIGST60741.2024.10717547