Automatic supervision and fault detection of PV systems based on power losses analysis

Chouder, Aissa; Silvestre, S.

doi:10.1016/j.enconman.2010.02.025

Cited by 361 publications

(167 citation statements)

References 14 publications

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“…Toward this end, real meteorological conditions of works (Temperatures (T) and Irradiance (G)) and MPP coordinates (Impp, Vmpp, and Pmpp) collected from an actual 3.2 KWp PV plant located within an Algerian Research center (Centre du Développement des Energies Renouvelables (CDER) of Algiers) [23] have been used. This PV plant is composed of two parallel strings of fifteen PV modules type Isofoton 106W-12V for each string.…”

Section: Simulation Resultsmentioning

confidence: 99%

A statistical-based approach for fault detection and diagnosis in a photovoltaic system

Garoudja

Harrou

Sun

et al. 2017

2017 6th International Conference on Systems and Control (ICSC)

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Section: Simulation Resultsmentioning

confidence: 99%

A statistical-based approach for fault detection and diagnosis in a photovoltaic system

Garoudja

Harrou

Sun

et al. 2017

2017 6th International Conference on Systems and Control (ICSC)

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“…There would be five reasons for such errors [22][23][24][25]: (i) climate factors (accumulation of snow, yellow dust, and high temperature); (ii) dirt, fallen leaves, bird feces, and other pollutants; (iii) careless maintenance; (iv) shading; and (v) error due to the data used in the energy simulation. If a PV panel is covered with snow, yellow dust, dirt, or other pollutants, it would be difficult to acquire sufficient surface area for the PV panel to induce electricity generation, resulting in loss in electricity generation.…”

Section: B Reason For Uncertaintymentioning

confidence: 99%

Estimating the Loss Ratio of Solar Photovoltaic Electricity Generation through Stochastic Analysis

Hong¹,

Koo

Lee³

2013

Journal of Construction Engineering and Project Management

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As climate change and environmental pollution become one of the biggest global issues today, new renewable energy, especially solar photovoltaic (PV) system, is getting great attention as a sustainable energy source. However, initial investment cost of PV system is considerable, and thus, it is crucial to predict electricity generation accurately before installation of the system. This study analyzes the loss ratio of solar photovoltaic electricity generation from the actual PV system monitoring data to predict electricity generation more accurately in advance. This study is carried out with the following five steps: (i) Data collection of actual electricity generation from PV system and the related information; (ii) Calculation of simulation-based electricity generation; (iii) Comparative analysis between actual electricity generation and simulation-based electricity generation based on the seasonality; (iv) Stochastic approach by defining probability distribution of loss ratio between actual electricity generation and simulation-based electricity generation ; and (v) Case study by conducting Monte-Carlo Simulation (MCS) based on the probability distribution function of loss ratio. The results of this study could be used (i) to estimate electricity generation from PV system more accurately before installation of the system, (ii) to establish the optimal maintenance strategy for the different application fields and the different season, and (iii) to conduct feasibility study on investment at the level of life cycle.

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“…In this way, it is possible to track the working conditions of each module recognizing faulty units [19,20], preventing mismatch [21] and partial shading, avoiding significant power losses [22] through suitable control actions.…”

Section: Introductionmentioning

confidence: 99%

Proof of Concept of an Irradiance Estimation System for Reconfigurable Photovoltaic Arrays

et al. 2015

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Abstract:In order to reduce the mismatch effect caused by non-uniform shadows in PV arrays, reconfigurable interconnections approaches have been recently proposed in the literature. These systems usually require the knowledge of the solar radiation affecting every solar module. The aim of this work is to evaluate the effectiveness of three irradiance estimation approaches in order to define which can be well suited for reconfigurable PV arrays. It is presented a real-time solar irradiance estimation device (IrradEst), implementing the three different estimation methods. The proposed system is based on mathematical models of PV modules enabling to estimate irradiation values by sensing a combination of temperature, voltage and current of a PV module. Experimental results showed generally good agreement between the estimated irradiances and the measurements performed by a standard pyranometer taken as reference. Finally one of the three methods was selected as possible solution for a reconfigurable PV system.

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Automatic supervision and fault detection of PV systems based on power losses analysis

Cited by 361 publications

References 14 publications

A statistical-based approach for fault detection and diagnosis in a photovoltaic system

A statistical-based approach for fault detection and diagnosis in a photovoltaic system

Estimating the Loss Ratio of Solar Photovoltaic Electricity Generation through Stochastic Analysis

Proof of Concept of an Irradiance Estimation System for Reconfigurable Photovoltaic Arrays

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