Multiple Fault Location in a Photovoltaic Array Using Bidirectional Hetero-Associative Memory Network in Micro-Distribution Systems

Long-Yi Chang,Chia-Hung Lin,Min-Hung Chou,Jian-Liung Chen,Chao-Lin Kuo,Neng-Sheng Pai

doi:10.3390/cryst8080327

Abstract

In manual maintenance inspections of large-scaled photovoltaic (PV) or rooftop PV systems, several days are required to survey the entire PV field. To improve reliability and shorten the amount of time involved, this study proposes an electrical examination-based method for locating multiple faults in the PV array. The maximum power point tracking (MPPT) algorithm is used to estimate the maximum power of each PV panel; this is then compared with metering the output power of PV array. Power degradation indexes as input variables are parameterized to quantify the degradation between estimated maximum PV output power and metered PV output power, which can be categorized into normal condition, grounded faults, open-circuit faults, bridged faults, and mismatch faults. Bidirectional hetero-associative memory (BHAM) networks are then used to associate the inputs and locate multiple faults as output variables within the PV array. For a rooftop PV system with two strings, experimental results demonstrate that the proposed model has computational efficiency in learning and detection accuracies for real-time applications, and that its algorithm is easily implemented in a mobile intelligent vehicle.

Highlights

A photovoltaic array is a single electricity-producing unit in which several PV panel components are arranged in parallel to increase output power
Output power an online assistant tooland is necessary forlong-term use in locating multiple faultsAs and conducting is significantly altered by damageAs or faults in one or more PV
Based on an electrical examination, this study proposes the use of the bidirectional hetero-associative memory (BHAM) network [15,16,17,18] to detect multiple faults in a PV array

Summary

Introduction

A photovoltaic array is a single electricity-producing unit in which several PV panel components are arranged in parallel (or in a series configuration) to increase output power. Output power an online assistant tooland is necessary forlong-term use in locating multiple faultsAs and conducting is significantly altered by damageAs or faults in one or more PV panels, study proposes long-term outdoor monitoring. To measure voltage and current on the DC–DC converter site or DC–AC inverter site, electrical examinations are needed; these are required to determine and inverter electrical are to needed; these arepanels required determine and quantify site, output power examinations degradation due possible faulty in a PV to array [6,11,12]. Based on an electrical examination, this study proposes the use of the bidirectional hetero-associative memory (BHAM) network [15,16,17,18] to detect multiple faults in a PV array.

Maximum Output Power Estimation and Fault Feature Extraction

Bidirectional Associative Memory Network

Experimental Results and Discussion

Conclusions