Two Variable Method for Fault Analysis in Grid Tied Solar Photovoltaic System

Abstract

Abstract-To increase the efficiency and reliability of a grid tied solar PV plant, it is important to detect the possible abnormalities and their location in the system. Conventional power devices frequently fails to detect certain types of faults which occur due to inappropriate installation, varying plant conditions and environmental factors such as low irradiance, snow, clouds, bird dropping, dust accumulation. Therefore, it is necessary to identify a vital solution to deal with the internal and external faults of the system. The faults in photovoltaic modules, array strings and inverter sometimes leads to safety issues in the system. This paper proposes a simple two-variable method to detect faults under the abnormal operating conditions of grid tied solar photovoltaic system. Furthermore the internal and external faults are studied using an experimental setup and obtained results indicate the accurate analysis of the fault severity and the change in electrical parameters of the system can be observed and compared with the normal working condition of system. Keyword-Grid-Tied PV system, Inverter fault, Array fault, Fault detection.I. INTRODUCTION Popularity of photovoltaic systems is increasing rapidly worldwide due to the simplicity of installation, no fuel cost, less maintenance and long life. The energy produced by the plants depends upon various factors such as performance characteristics of plant components, geometrical configuration, electrical and mechanical parameter and weather conditions of the site and availability of amount of solar irradiance. The power production capacity of the grid tied photovoltaic (PV) plants ranges from few kilowatts to several megawatts depending upon their usage for domestic to utility scale. The maximum power production of plant reduces in case of abnormality in the system. The conventional protection devices of PV plant consist of over current interrupters, protection relays, ground fault and arc-fault protection devices frequently fails to detect the faults under certain conditions [1]. The challenge is to protect the system from the abnormalities due to protection equipment failure, environmental conditions, maximum power point tracker, blocking diodes and PV module shading. The faults in the system can be detected by comparing the actual electrical parameters which depend upon the system configuration parameters and meteorological data of the plant site with the expected quantities of the system [2]. Thresholds are defined considering PV array parameters such as the amount of irradiance incident at the normal of flat plate collector surface, ambient temperature and electrical quantities of the system so as to detect the presence of abnormalities. Currently, many researchers are working on identifying the techniques to detect the PV system faults in minimum possible time to eliminate them from the system. To locate disconnect in the PV module string the earth capacitance measurement method was developed in [3], another technique that can detect the change in transmis...

An early fault detection approach in grid-connected photovoltaic (GCPV) system

“…Khatri and Kumar also stated that the faults in PV system can be diagnosed by comparing the actual electrical parameters with the expected electrical parameters, in which these parameters are dependable on the system configuration parameters and meteorological data [1,21]. Typically, comparison of the measured data against simulation results is also accepted as one of the examination method for fault detection in PV system.…”

“…An AR algorithm was developed as shown in Figure 4. AR was calculated for each five minutes data of both systems using (1). The graphs of AR in relationship to G were plotted for both systems.…”

“…The solar industry has grown rapidly over the past few years. The momentum of the growth is represented by the number and capacity of Photovoltaic (PV) system installations all over the world [1]. The effectiveness of PV system operational can be influenced by several circumstances which may results in power loss and waste [2].…”

“…Various studies of fault detection were seriously focused. These studies include the fault finding by using mathematical method diagnosis [4], evaluating performance ratio (PR), capture losses, array and grid power losses analysis [1] and also artificial neural network [5]. Numerous fault detection techniques on DC side of PV system have been applied; such as climatic data independent technique (CDI) [6], electrical current-voltage (I-V) measurement (EM) technique [7], measured and modeled PV system outputs (CMM) technique [8], power loss analysis (PLA) technique [9], Machine learning (ML) techniques [10,11], [12], ground fault detection and interruption (GFDI) fuse [12], residual current monitoring devices (RCDs) [12], insulation monitoring devices (IMDs) [13], frequency spectrum analysis (FSA) of the voltage or current waveforms [13], estimating randomness in the voltage signal (ERV) [13], spread spectrum time-domain reflectometry (SSTDR), infrared (IR)/ thermal imaging [14], visual inspection and lock in thermography (LIT) [13].…”