This work presents a novel Anti-Islanding (AI) protection of Photovoltaic (PV) Systems based on monitoring the dc-link voltage of the PV inverter. A PV System equipped with AI protection like frequency relays, a rate of change of frequency (ROCOF) relay, and respectively the proposed dc-link voltage relay is simulated under the conditions of islanding and the detection time for all these AI techniques are compared. The study shows under which conditions our proposed dc-link voltage AI relay is the most efficient.

Instructions: 

1. Open the "Banu_PVarray_Grid_det_AI_UPEC2014.slx" file with Matlab R2014a or a newer Matlab release. 2. Open the "Relay Protection Bus B20 (20 kV)" block to see the Anti-Islanding Protection Scheme, including the new "DC-Link Voltage Protection" Method and its settings.

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This work presents a Matlab/Simulink study on anti-islanding detection algorithms for a 100kW Grid-Connected Photovoltaic (PV) Array. The main focus is on the islanding phenomenon that occurs at the Point of Common Coupling (PCC) between Grid-Connected PV System and the rest of the electric power system (EPS) during various grid fault conditions. The Grid-Connected PV System is simulated under the conditions of islanding, and anti-islanding (AI) relay reaction times are measured through the simulation.

Instructions: 

1. Open the "Fault3_50Hz_Banu_PVarray_Grid_IncCondReg_det_AI_2013_.slx" file with Matlab R2013b or a newer release to simulate the 100kW Grid-Connected PV Array (Detailed Model) with Anti-Islanding Relays. 2. To see the Anti-Islanding Protection Relays and its settings, open the "Relay Protection Bus B20 (20kV)" block.

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This work aims to implement in Matlab and Simulink the perturb-and-observe (P&O) and incremental conductance Maximum Power Point Tracking (MPPT) algorithms that are published in the scientific literature.

Instructions: 

1. Open the .slx file (PVArray_DC_DC_Buck_MPPT.slx) in Matlab 2012b or a newer version. 2. Default settings of "PVArray_DC_DC_Buck_MPPT.slx" Simulink model are given in Model Proprieties: File -> Model Proprieties -> Model Proprieties -> Callbacks -> PreLoadFcn* as follow:           load('25PVArrayExperimentalData.mat');           MPPT_IncCond=Simulink.Variant('MPPT_MODE==1')           MPPT_PandO=Simulink.Variant('MPPT_MODE==2')           MPPT_MODE=1           Constant_800=Simulink.Variant('Irradiance_Mode==1')           Constant_1000=Simulink.Variant('Irradiance_Mode==2')           Step=Simulink.Variant('Irradiance_Mode==3')           Irradiance_Mode=2 3. To run the "PVArray_DC_DC_Buck_MPPT.slx" Simulink model with P&O algorithm activate "MPPT_PandO=Simulink.Variant" at the Matlab command prompt by setting the "MPPT_MODE" with "2": "MPPT_MODE=2". Use the same procedure to change "Irradiance_Mode". To simulate the PV Array at 70°C use the command: "load('70PVArrayExperimentalData.mat');" *For more details about Variant Subsystems see the Matlab Documentation: https://www.mathworks.com/help/simulink/examples/variant-subsystems.html

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This work presents the performance evaluation of incremental conductance maximum power point tracking (MPPT) algorithm for solar photovoltaic (PV) systems under rapidly changing irradiation condition. The simulation model, carried out in Matlab and Simulink, includes the PV solar panel, the dc/dc buck converter and the MPPT controller. This model provides a good evaluation of performance of MPPT control for PV systems.

Instructions: 

Open the MDL files in Matlab 2014a or a newer version.

 

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2282 Views

The aim of the database consists of providing the researchers with a collection of power quality real-life impulsive events to test experiments and measurement instruments. The dataset provides signals recordings from the power network of the University of Cádiz during the last five years (electrical network according to the UNE-EN-50160: 2011).

The dataset offers a diversity of real impulsive events, which are specifically acquired in order to test Power Quality Instruments according to the UNE-IEC 61000-4-11: 2005.

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