The dataset contains fundamental approaches regarding modeling individual photovoltaic (PV) solar cells, panels and combines into array and how to use experimental test data as typical curves to generate a mathematical model for a PV solar panel or array.

 

Instructions: 

This dataset contain a PV Arrays Models Pack with some models of PV Solar Arrays carried out in Matlab and Simulink. The PV Models are grouped in three ZIP files which correspond to the papers listed above.

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The work starts with a short overview of grid requirements for photovoltaic (PV) systems and control structures of grid-connected PV power systems. Advanced control strategies for PV power systems are presented next, to enhance the integration of this technology. The aim of this work is to investigate the response of the three-phase PV systems during symmetrical and asymmetrical grid faults.

Instructions: 

1. Open the "Banu_power_PVarray_grid_EPE2014_.slx" file with Matlab R2014a 64 bit version or a newer Matlab release. 2. To simulate various grid faults on PV System see the settings of the "Fault" variant subsystem block (Banu_power_PVarray_grid_EPE2014_/20kV Utility Grid/Fault) in Model Properties (File -> Model Properties -> Model Properties -> Callbacks -> PreLoadFcn* (Model pre-load function)):           MPPT_IncCond=Simulink.Variant('MPPT_MODE==1')           MPPT_PandO=Simulink.Variant('MPPT_MODE==2')           MPPT_IncCond_IR=Simulink.Variant('MPPT_MODE==3')           MPPT_MODE=1           Without_FAULT=Simulink.Variant('FAULT_MODE==1')           Single_phases_FAULT=Simulink.Variant('FAULT_MODE==2')           Double_phases_FAULT=Simulink.Variant('FAULT_MODE==3')           Double_phases_ground_FAULT=Simulink.Variant('FAULT_MODE==4')           Three_phases_FAULT=Simulink.Variant('FAULT_MODE==5')           Three_phases_ground_FAULT=Simulink.Variant('FAULT_MODE==6')           FAULT_MODE=1 3. For more details about the Variant Subsystems see the Matlab Documentation Center: https://www.mathworks.com/help/simulink/variant-systems.html or https://www.mathworks.com/help/simulink/examples/variant-subsystems.html

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4054 Views

The early detection of damaged (partially broken) outdoor insulators in primary distribution systems is of paramount importance for continuous electricity supply and public safety. In this dataset, we present different images and videos for computer vision-based research. The dataset comprises images and videos taken from different sources such as a Drone, a DSLR camera, and a mobile phone camera.

Instructions: 

Please find the attached file for complete description

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109 Views

The datasets consist of operational data and detailed information of three inverter transformers in a 3.275 MW PV plant in the outskirt of Brisbane, Australia. The data includes load current, top-oil temperature, moisture in top oil, ambient temperature, solar irradiance and individual current harmonics (up to 31st order). The time interval of the data is either 1 minute or 3 seconds (dependent on the data type). The data can be used to study the ageing of inverter transformers in this PV plant. 

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147 Views

Over the past two decades,  various machine learning methods are proposed for the prediction of electricity prices.  Existing literature discusses in detail the strength and weaknesses of these methods.  This dataset focuses on the exploration of online personalized machine learning models for the prediction of monthly electricity bills in developing countries. For this purpose, we gathered the dataset of monthly electricity bills of 70 users for one year.

Instructions: 

There are two sheets in it. Sheet one has monthly electricity bills of 39 users for one year from APRIL 2018 to APRIL 2019. Similarly, sheet two has monthly electricity bills of 30 users from May to May. The prices are in PKR.

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19 Views

Distribution 20kV Surge Arrester Historical Inspection Data from year 2007 to 2019 and from an European utility company   

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170 Views

20kV PILC Cable Historical Inspection Data from year 2007 to 2019 from an European utility company 

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92 Views

20kV XLPE Cable Historical Inspection Data from year 2010 to 2019 from an European utility company

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129 Views

Asset health index evalualtion results from an European utility company

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117 Views

This provides the code and data used in the paper "Optimal EV Scheduling in Residential Distribution Networks Considering Customer Charging Preferences" by Mailys Le Cam and Barry Hayes. 

Some material has been adapated from the OpenDSS help files: http://smartgrid.epri.com/SimulationTool.aspx Some data has been taken from the IEEE test feeders archive: http://sites.ieee.org/pes-testfeeders/

 

 

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