Detection of Internal Resistance Change for Photovoltaic Arrays Using Extremum-Seeking Control MPPT Signals

Li, Xiao; Li, Yaoyu; Seem, John E.; Peng, Lei

doi:10.1109/tcst.2015.2424857

Cited by 40 publications

(15 citation statements)

References 32 publications

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“…Hence, they increase the cost of the protection scheme. In fact, this problem has been solved in several detection methods proposed in [12] - [14] using either low cost power line communication (PLC) or a wireless selfpowered sensor architecture.…”

Section: Introductionmentioning

confidence: 99%

Novel Open-Circuit Photovoltaic Bypass Diode Fault Detection Algorithm

Dhimish

Chen

2019

IEEE J. Photovoltaics

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In this paper, a novel photovoltaic (PV) bypass diode fault detection algorithm is presented. The algorithm consists of three main steps. First, the threshold voltage of the I-V curve is obtained using different failure bypass diode scenarios. Second, the theoretical prediction for the faulty regions of bypass diodes is calculated using the analysis of voltage drop in the I-V curve as well as the voltage at maximum power point. Lastly, the actual I-V curve under any environmental condition is measured and compared with theoretical predictions. The proposed algorithm has been experimentally evaluated using a PV string that comprises three series-connected PV modules, and subtotal nine bypass diodes. Various experiments have been conducted under diverse bypass diodes failure conditions. The achieved detection accuracy is always greater than 99.39% and 99.74% under slow and fast solar irradiance transition respectively.

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Section: Introductionmentioning

confidence: 99%

Novel Open-Circuit Photovoltaic Bypass Diode Fault Detection Algorithm

Dhimish

Chen

2019

IEEE J. Photovoltaics

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“…The above-mentioned methods are for the photovoltaic modules, of which each photovoltaic module needs to be monitored, leading to high costs. In [9][10][11][12][13], the fault diagnosis methods of the photovoltaic arrays were introduced. The fault detection is based on the comparison between the measured and model prediction results of the power production [9].…”

Section: Analysis Of Internal Parameters Of Photovoltaic Array Equivamentioning

confidence: 99%

“…Hu, YH, et al, analyze the terminal characteristics of faulty photovoltaic arrays and reduce the number of sensors by optimizing its locations [10]. In [11], the authors diagnose the fault by detecting the change of PV internal resistance using the signals that are available in Extremum-Seeking Control (ESC)-based Maximum Power Point Tracking (MPPT). The methods in these works can only identify whether there is a fault or not, but the fault type is unknown.…”

Section: Analysis Of Internal Parameters Of Photovoltaic Array Equivamentioning

confidence: 99%

Fault Diagnosis Model of Photovoltaic Array Based on Least Squares Support Vector Machine in Bayesian Framework

Sun

Fan

et al. 2017

Applied Sciences

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Abstract:With the rapid development of the photovoltaic industry, fault monitoring is becoming an important issue in maintaining the safe and stable operation of a solar power station. In order to diagnose the fault types of photovoltaic array, a fault diagnosis method that is based on the Least Squares Support Vector Machine (LSSVM) in the Bayesian framework is put forward. First, based on the elaborate analysis of the change rules of the output electrical parameters and the equivalent circuit internal parameters of photovoltaic array in different fault states, the input variables of the photovoltaic array fault diagnosis model are determined. Second, through the LSSVM algorithm in the Bayesian framework, the fault diagnosis model based on the output electrical parameters and the equivalent circuit internal parameters of the photovoltaic array is built, which can effectively detect the photovoltaic array faults of short circuit, open circuit, and abnormal aging. Then, the simulation model is built to verify the validity of the LSSVM algorithm in the Bayesian framework by comparing it with the model of LSSVM and the Support Vector Machine (SVM). Moreover, a 5 × 3 photovoltaic array and a reference photovoltaic string are established and experimentally tested to validate the performance of the proposed method.

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“…However, the power energy generated from PV modules relies highly on environmental factors such as solar insolation and the ambient temperature [1,2]. Therefore, in order to harvest the maximum power output and improve the efficiency of the entire PV system, many advanced MPPT control methods have been implemented in PV systems [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

An Advanced Maximum Power Point Tracking Method for Photovoltaic Systems by Using Variable Universe Fuzzy Logic Control Considering Temperature Variability

Wang

Yang

Fang³

et al. 2018

Electronics

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In this study maximum power point tracking (MPPT) is applied to the photovoltaic (PV) system to harvest the maximum power output. The output power of the PV effect changes according to external solar irradiation and ambient temperature conditions. In the existing MPPT strategies, most of them only take variations in radiation level into account, rarely considering the impact of temperature changes. However, the temperature coefficients (TC) play an important role in the PV system, especially in applications where ambient temperature changes are relatively large. In this paper, an MPPT method is presented for a PV system that considers the temperature change by using variable universe fuzzy logic control (VUFLC). By considering the ambient temperature change in PV modules, the proposed control method can regulate the contraction and expansion factor of VUFLC, which eliminates the influence of temperature variability and improves the performance of MPPT, therefore achieving fast and accurate tracking control. The proposed method was evaluated for a PV module under different ambient conditions and its control performance is compared with other MPPT strategies by simulation and experimental results.

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Detection of Internal Resistance Change for Photovoltaic Arrays Using Extremum-Seeking Control MPPT Signals

Cited by 40 publications

References 32 publications

Novel Open-Circuit Photovoltaic Bypass Diode Fault Detection Algorithm

Novel Open-Circuit Photovoltaic Bypass Diode Fault Detection Algorithm

Fault Diagnosis Model of Photovoltaic Array Based on Least Squares Support Vector Machine in Bayesian Framework

An Advanced Maximum Power Point Tracking Method for Photovoltaic Systems by Using Variable Universe Fuzzy Logic Control Considering Temperature Variability

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