scholarly journals DC-Link Voltage Control of a Grid-Connected Solar Photovoltaic System for Fault Ride-Through Capability Enhancement

2019 ◽  
Vol 9 (5) ◽  
pp. 952 ◽  
Author(s):  
S. Mohamed ◽  
P. Jeyanthy ◽  
D. Devaraj ◽  
M. Shwehdi ◽  
Adel Aldalbahi
Keyword(s):  
Power Converters ◽  
Reactive Power ◽  
Low Voltage ◽  
Voltage Control ◽  
Maximum Power ◽  
Solar Photovoltaic ◽  
Maximum Power Point ◽  
Control Scheme ◽  
Mppt Controller ◽  
Power Point

The high penetration level of solar photovoltaic (SPV) generation systems imposes a major challenge to the secure operation of power systems. SPV generation systems are connected to the power grid via power converters. During a fault on the grid side; overvoltage can occur at the direct current link (DCL) due to the power imbalance between the SPV and the grid sides. Subsequently; the SPV inverter is disconnected; which reduces the grid reliability. DC-link voltage control is an important task during low voltage ride-through (LVRT) for SPV generation systems. By properly controlling the power converters; we can enhance the LVRT capability of a grid-connected SPV system according to the grid code (GC) requirements. This study proposes a novel DCL voltage control scheme for a DC–DC converter to enhance the LVRT capability of the two-stage grid-connected SPV system. The control scheme includes a “control without maximum power point tracking (MPPT)” controller; which is activated when the DCL voltage exceeds its nominal value; otherwise, the MPPT control is activated. Compared to the existing LVRT schemes the proposed method is economical as it is achieved by connecting the proposed controller to the existing MPPT controller without additional hardware or changes in the software. In this approach, although the SPV system will not operate at the maximum power point and the inverter will not face any over current challenge it can still provide reactive power support in response to a grid fault. A comprehensive simulation was carried out to verify the effectiveness of the proposed control scheme for enhancing the LVRT capability and stability margin of an interconnected SPV generation system under symmetrical and asymmetrical grid faults.

New Photovoltaic Module Model And A Comparative Study of MPPT Control Techniques Based On Neural Networks

2021 ◽  
pp. 69-76
Author(s):  
Mourad Talbi ◽  
Nawel Mensia ◽  
Hatem Ezzaouia
Keyword(s):  
Renewable Energy ◽  
Comparative Study ◽  
Temporal Variations ◽  
Operating Conditions ◽  
Maximum Power ◽  
Energy Resources ◽  
Solar Photovoltaic ◽  
Maximum Power Point ◽  
Mppt Controller ◽  
Power Point

Nowadays, renewable energy resources play an important role in replacing conventional fossil fuel energy resources. Solar photovoltaic (PV) energy is a very promising renewable energy resource, which rapidly grew in the past few years. The main problem of the solar photovoltaic is with the variation of the operating conditions of the array, the voltage at which maximum power can be obtained from it likewise changes. In this paper, is first performed the modelling of a solar PV panel using MATLAB/Simulink. After that, a maximum power point tracking (MPPT) technique based on artificial neural network (ANN) is applied in order to control the DC-DC boost converter. This MPPT controller technique is evaluated and compared to the “perturb and observe” technique (P&O). The simulation results show that the proposed MPPT technique based on ANN gives faster response than the conventional P&O technique, under rapid variations of operating conditions. This comparative study is made in terms of temporal variations of the duty cycle (D), the output power ( out P ), the output current ( out I ), the efficiency, and the reference current ( ref I ). The efficiency, D, out P , and out I are the output of the boost DC-DC, and ref I is itsinput. The different temporal variations of the efficiency, D, ref I , out P , and out I (for the two cases: the first case, when T = 25°C and G =1000 W/m2 and the second case, when T and G are variables), show negligible oscillations around the maximum power point. The used MPPT controller based on ANN has a convergence time better than conventional P&O technique.

Design and Modeling of the ANFIS-Based MPPT Controller for a Solar Photovoltaic System

2020 ◽  
Vol 143 (4) ◽  
Author(s):  
Ranganai T. Moyo ◽  
Pavel Y. Tabakov ◽  
Sibusiso Moyo
Keyword(s):  
Boost Converter ◽  
Maximum Power ◽  
Solar Photovoltaic ◽  
Maximum Power Point ◽  
Power Controller ◽  
Pv Module ◽  
Pv Modules ◽  
Mppt Controller ◽  
Simulation Results ◽  
Power Point

Abstract Maximum power point tracking (MPPT) controllers play an important role in improving the efficiency of solar photovoltaic (SPV) modules. These controllers achieve maximum power transfer from PV modules through impedance matching between the PV modules and the load connected. Several MPPT techniques have been proposed for searching the optimal matching between the PV module and load resistance. These techniques vary in complexity, tracking speed, cost, accuracy, sensor, and hardware requirements. This paper presents the design and modeling of the adaptive neuro-fuzzy inference system (ANFIS)-based MPPT controller. The design consists of a PV module, ANFIS reference model, DC–DC boost converter, and the fuzzy logic (FL) power controller for generating the control signal for the converter. The performance of the proposed ANFIS-based MPPT controller is evaluated through simulations in the matlab/simulink environment. The simulation results demonstrated the effectiveness of the proposed technique since the controller can extract the maximum available power for both steady-state and varying weather conditions. Moreover, a comparative study between the proposed ANFIS-based MPPT controller and the commonly used, perturbation and observation (P&O) MPPT technique is presented. The simulation results reveal that the proposed ANFIS-based MPPT controller is more efficient than the P&O method since it shows a better dynamic response with few oscillations about the maximum power point (MPP). In addition, the proposed FL power controller for generating the duty cycle of the DC–DC boost converter also gave satisfying results for MPPT.

scholarly journals INFLUENCE OF POWER CONVERTERS ON PV MAXIMUM POWER POINT TRACKING EFFICIENCY

2014 ◽  
Vol 19 (1) ◽  
pp. 73-80
Author(s):  
Roberto Francisco Coelho ◽  
Walbermark Marques dos Santos ◽  
Denizar Cruz Martins
Keyword(s):  
Power Converters ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

scholarly journals Tracking of Maximum Power Point in Solar PV (SPV) Systems using Perturb & Observe (PO) and Incremental Conductance (IC) Method

2019 ◽  
Vol 8 (12) ◽  
pp. 613-618
Keyword(s):  
Electrical Energy ◽  
Maximum Power ◽  
Energy Utilization ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Maximum Power Point ◽  
Incremental Conductance ◽  
Tracking Time ◽  
Power Point ◽  
Number Of Publications

The solar energy being clean, green & commercially modest, have become one of the most prevalent choice amongst the renewable sources of electrical energy. Utilization of energy generated from Solar photovoltaic (SPV) system rest on the maximum extraction of the power generated. Ideal maximum power point (MPP) tracking (MPPT) is used to transfer 100% generated power from source and transfer it to load. In literature of recent years, a good number of publications found on SPV systems and MPPT. In this paper most popular MPPT techniquesPerturb & Observe (PO) and Incremental Conductance (IC) methods are simulated and implemented. The comparison is also presented on the ground of parameters like tracking time, tracking efficiency etc.

scholarly journals Particle Swarm Optimization-Based Power and Temperature Control Scheme for Grid-Connected DFIG-Based Dish-Stirling Solar-Thermal System

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1300 ◽  
Author(s):  
Yang Li ◽  
Binyu Xiong ◽  
Yixin Su ◽  
Jinrui Tang ◽  
Zhiwen Leng
Keyword(s):  
Particle Swarm Optimization ◽  
Maximum Power ◽  
Solar Thermal ◽  
Control Parameters ◽  
Maximum Power Point ◽  
Swarm Optimization ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Control Scheme ◽  
Power Point

Variable-speed operation of a dish-Stirling (DS) concentrated solar-thermal power generating system can achieve higher energy conversion efficiency compared to the conventional fixed-speed operation system. However, tuning of the controllers for the existing control schemes is cumbersome due to the presence of a large number of control parameters. This paper proposes a new control system design approach for the doubly-fed induction generator (DFIG)-based DS system to achieve maximum power point tracking and constant receiver temperature regulation. Based on a developed thermo-electro-pneumatic model, a coordinated torque and mean pressure control scheme is proposed. Through steady-state analysis, the optimal torque is calculated using the measured insolation and it serves as the tracking reference for direct torque control of the DFIG. To minimize the tracking error due to temperature variation and the compressor loss of the hydrogen supply system, four optimal control parameters are determined using particle swarm optimization (PSO). Model-order reduction and the process of the pre-examination of system stability are incorporated into the PSO algorithm, and it effectively reduces the search effort for the best solution to achieve maximum power point tracking and maintain the temperature around the set-point. The results from computational simulations are presented to show the efficacy of the proposed scheme in supplying the grid system with smoothened maximum power generation as the solar irradiance varies.

scholarly journals Numerical Performance Evaluation of Solar Photovoltaic Water Pumping System under Partial Shading Condition using Modern Optimization

Mathematics ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 1123 ◽  
Author(s):  
Arfaoui ◽  
Rezk ◽  
Al-Dhaifallah ◽  
Elyes ◽  
Abdelkader
Keyword(s):  
Maximum Power ◽  
Solar Photovoltaic ◽  
Matlab Simulation ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Pumping System ◽  
Water Pumping ◽  
Voltage Curve ◽  
Perturb And Observe ◽  
Power Point

Renewable energy is an attractive solution for water pumping systems particularly in isolated regions where the utility grid is unavailable. An attempt is made to improve the performance of solar photovoltaic water pumping system (SPVWPS) under partial shading condition. Under this condition, the power versus voltage curve has more than one maximum power point (MPP), which makes the tracking of global MPP not an easy task. Two MPP tracking (MPPT) strategies are proposed and compared for tracking MPP of SPVWPS under shading condition. The first method is based on the classical perturb and observe (P&O) and the other method is based on a Salp Swarm Algorithm (SSA). Based on extensive MATLAB simulation, it is found that the SSA method can provide higher photovoltaic (PV) generated power than the P&O method under shading condition. Consequently, the pump flowrate is increased. But, under normal distribution of solar radiation, both MPPT techniques can extract the maximum power but SSA is considered a time-consuming approach. Moreover, SSA is compared with particle swarm optimization (PSO) and genetic algorithm (GA). The obtained results ensure the superiority of SSA compared with PSO and GA. SSA has high successful rate of reaching true global MPP.

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