scholarly journals Modelling and analysis of grid-connected solar-PV system through current-mode controlled VSC

2020 ◽  
Vol 167 ◽  
pp. 05005
Author(s):  
Elsayed Saad ◽  
Yasser Elkoteshy ◽  
Usama AbouZayed

Recently, solar-PV energy becomes one of the most vital renewable resources of electrical energy as it is utilized in all life applications. In case of connecting the solar-PV system with the utility grid a voltage-sourced converter (VSC) is required to convert the extracted solar-PV array’s DC power into AC. There are many methods to dominate the active and reactive power produced from the VSC. In the following model we use the current mode control as it has some features such as highly output accuracy, protection against over current troubles, robustness against AC side voltage and load variations. As the produced power from the solar cells is intermittent, the point of maximum power has to be tracked using an MPPT technique. Also, in order to reduce the system harmonics a filter must be implemented in the model. In this paper, a complete model of 50KW grid-connected solar-PV system using current-mode controlled two-level three-phase VSC (grid imposed frequency VSC) is implemented. Also, the Incremental Conductance model to track the point of maximum available power (MPPT) and LCL filter has been provided into the system with total harmonic distortion (THD) analysis in PSCAD/EMTDC

Author(s):  
Shital Thorat ◽  
Vaiju N Kalkhambkar

A solar-PV system is generally connected to distributed generation (DG) by the utility grid. The solar inverter retains some capacity after active power generation. Reactive power compensation can be achieved by utilizing the remaining capacity of the solar-PV inverter. This paper introduces an energy management system (EMS) for real and reactive power management. The proposed EMS includes two modes: PV-STATCOM and islanding. In PV-STATCOM mode, the PI control is used whereas for the islanding mode, voltage frequency control is employed. This paper proposes the energy management of reactive power by utilizing the solar photovoltaic (PV) inverter as a static synchronous compensator (PV-STATCOM). Therefore, no other additional flexible AC transmission system controllers or series/shunt capacitors are required. During the islanding mode, the storage provides continuous supply to the load. The system is simulated using single-phase and three-phase modes with the hardware results also revealed. The proposed scheme provides a significant improvement in power factor while reducing the total harmonic distortion.  


2019 ◽  
Author(s):  
Rishal Asri

Sunlight is energy that can be converted into electrical energy. One of the uses is by applying it to the roof ofthe building. The application in this building has restrictions such as the placement of the PV moduleshorizontally and vertically. In the study comparing the results of energy obtained from the PV system withhorizontal and vertical positions with a standard degree angle in the direction of azimuth sunlight. Positionusing the horizontal produces more energy and reaches a performance ratio of more than 80%.


A reliable grid connected Photovoltaic (PV) system require effective control schemes for efficient use of solar energy. This paper presents a three-phase grid tied PV system with decoupled real and reactive power control to achieve desired power factor with Maximum Power Point Tracking (MPPT) controller to get maximum solar energy. The synchronous reference frame (dq) control along with decoupling concept is used to control the DC-AC inverter output, while the Phase Locked Loop (PLL) synchronization technique is used to monitor and synchronize the voltage and current at the grid side. The DC-DC converter with Incremental Conductance (InC) based MPPT model is also designed in this paper due to better accuracy compared to Perturb & Observe (P&O) algorithm. The simulation is performed in MATLAB/SIMULINK and a 31.5 kW PV system is modelled to get 30 kW power with the help of MPPT at Standard Test Conditions (STC). Any power factor value between 0.85 lagging to 0.9 leading can be obtained by changingreference q current in this inverter control strategy. The simulation results show that the change of reactive powerdoes not affecttheactive power values of the system, which verifies the effectiveness of the decoupled control strategy of the inverter.


2021 ◽  
Vol 335 ◽  
pp. 03002
Author(s):  
Chong Jia Joon ◽  
Kelvin Chew Wai Jin

Solar photovoltaic (PV) panels have been widely used to convert the renewable energy from the sun to electrical energy to power electrical loads but suffers from relatively low efficiency between 15% to 22%. Typically, the panels have an average lifespan of 25 to 30 years but could degrade quicker due to the panel overheating. Beyond the optimum working temperature of 25°C, a drop of efficiency by 0.4 to 0.5% for every 1°C had been reported. For solar PV applications in urban regions, passive cooling is beneficial due to limited amount of space and lower energy consumption compared to active cooling. A solar PV system with augmented cooling was conducted at a balcony of a condominium from 10am until 2pm. The solar PV system consisted of an Arduino controller, solar panel module, temperature sensor and LCD monitor. Reusable cold and hot gel packs were attached to the bottom of the solar PV. Both setups of solar PV panel with and without the cooling system were placed at the balcony simultaneously for measurement of temperature, output voltage and current. From this research, the outcome of implementing a cooling system to the solar PV increases the efficiency of the energy conversion.


2019 ◽  
Vol 5 (11) ◽  
pp. 1-9
Author(s):  
Avinash Kumar ◽  
Vivek Kumar Kostha ◽  
Satyam Kumar Prasun

This work deals with neural network control algorithm-based grid connected to solar photo voltaic (PV) system consisting of DC-AC converter. The reference solar-grid current for three-leg VSC are estimated using neural network control algorithm. The neural network control algorithm based solar PV system is modeled in MATLAB R2018a along with SIMULINK.. This study presents an artificial neural network-based controller for regulating the level of active and reactive power output. First, the three phase currents from the VSI are measured and compared with the three reference currents. The neural network is trained to have minimum output error. It was concluded that the power output from the system was found to be190 KVA in case of system having no intelligent controller and 700 KVA in case of system with AAN based control. The voltage of output is maintained to be 20 kV in the grid system for analysis purpose. Thus the proposed control is expected to be implemented in the renewable energy resources for better output.


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