Ioan Banu's picture
First Name: 
Last Name: 
Technical University of Iasi
Job Title: 
Renewables Energy Sources, Photovoltaics, Wind Turbines, Power Electronics, Power Systems
Short Bio: 
Ioan-Viorel Banu received the PhD degree in Power Engineering from the Faculty of Electrical Engineering, Energetics and Applied Informatics, “Gheorghe Asachi” Technical University of Iasi, Iasi, Romania in 2015. His research interests include renewable energy sources, modeling of photovoltaic arrays, maximum power point tracking algorithms for photovoltaic systems, power converters for photovoltaic systems, islanding detection in grid-connected photovoltaic systems, and integration of photovoltaic sources into the power grid. Dr. Banu is IEEE member since 2014.

Datasets & Analysis

This dataset contains (1) the Simulink model of a three-phase photovoltaic power system with passive anti-islanding protections like over/under current (OUC), over/under voltage (OUV), over/under frequency (OUF), rate of change of frequency (ROCOF), and dc-link voltage and (2) the results in the voltage source converter and the point of common coupling of the photovoltaic system during islanding operation mode and detection times of analyzed anti-islanding methods.


The anti-islanding protection relays are included in the "Relay Protection Bus B20 (20 kV)" subsystem.


Research on Optimizing the Integration of Renewable Energy Sources into the Electrical Power Systems

In this project one model the photovoltaic and wind power sources in order to analyze how to optimally integrate them in the electrical power systems. Integration requirements like transient regimes associated with fault occurrence, identification of the electrical power systems responsible for disturbances, and optimization of the integration are focus points of the research.


This dataset contain some models of photovoltaic power plants and wind power plants integrated in the electrical power systems carried out in Matlab/Simulink under fault ride-through operation.


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.



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.


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.


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: or


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.


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.


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.


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.


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.


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:


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.


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