scholarly journals High-Flexibility MPPT Techniques with Communication Scan Network for PV Micro-Grid System

Processes ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 117
Author(s):  
Yu-Kai Chen ◽  
Hong-Wen Hsu ◽  
Chau-Chung Song ◽  
Yu-Syun Chen

This paper proposes the design and implementation of inductor-inductor-capacitor (LLC) converters with modules connected in series with the power scan method and communication scan network (CSN) to achieve MPPT and regulate the output voltage for the PV micro-grid system. The Dc/Dc converters includes six isolated LLC modules in series to supply ±380 V output voltage and track the maximum power point of the PV system. The series LLC converters are adopted to achieve high efficiency and high flexibility for the PV micro-grid system. The proposed global maximum power scan technique is implemented to achieve global maximum power tracking by adjusting the switching frequency of the LLC converter. To improve the system flexibility and achieve system redundancy, module failure can be detected in real time with a communication scan network, and then the output voltage of other modules will be changed by adjusting the switching frequency to maintain the same voltage as before the failure. Additionally, the proposed communication scan network includes the RS-485 interface of the MPPT series module and the CAN BUS communication interface with other subsystems’ communication for the PV micro-grid application system. Finally, a 6 kW MPPT prototype with a communication scan network is implemented and the proposed control method is verified for the PV system.

Author(s):  
Ahmed Ibrahim ◽  
Raef Aboelsaud ◽  
Sergey Obukhov

This paper presents a cuckoo search (CS) algorithm for determining the global maximum power point (GMPP) tracking of photovoltaic (PV) under partial shading conditions (PSC). The conventional methods are fail to track the GMPP under PSC, which decrease the reliability of the power system and increase the system losses. The performance of the CS algorithm is compared with perturb and observe (P&O) algorithm for different cases of operations of PV panels under PSC. The CS algorithm used in this work to control directly the duty cycle of the DC-DC converter without proportional integral derivative (PID) controller. The proposed CS model can track the GMPP very accurate with high efficiency in less time under different conditions as well as in PSC.


Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1460
Author(s):  
Omar Abdel-Rahim ◽  
Nehmedo Alamir ◽  
Mohamed Abdelrahem ◽  
Mohamed Orabi ◽  
Ralph Kennel ◽  
...  

Maximum Power Point Tracking (MPPT) control is an essential part of every photovoltaic (PV) system, in order to overcome any change in ambient environmental conditions and ensure operation at maximum power.. Recently, micro-inverters have gained a lot of attention due to their ability to track the true MPP for each individual PV module, which is considered a powerful solution to overcome the partial shading and power mismatch problems which exist in series-connected panels. Although the LLC resonant converter has high efficiency and high boosting ability, traditional MPPT techniques based on Pulse Width Modulation (PWM) do not work well with it. In this paper, a fixed frequency predictive MPPT technique is presented for the LLC resonant converter to be used as the first-stage in a PV micro-inverter. Using predictive control enhances the tracking efficiency and reduces the steady state oscillation. Operation with fixed switching frequency for the LLC resonant converter improves the total harmonic distortion profile of the system and ease the selection of circuit magnetic component. To demonstrate the effectiveness of the proposed MPPT technique, the system is simulated using MATLAB/Simulink platform. Furthermore, a 150 W hardware prototype is developed and tested. Both simulation and experimental results are consistent and validate the proper operation of the developed system.


Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4849
Author(s):  
Ayman Al-Quraan ◽  
Muhannad Al-Qaisi

The problem of electrical power delivery is a common problem, especially in remote areas where electrical networks are difficult to reach. One of the ways that is used to overcome this problem is the use of networks separated from the electrical system through which it is possible to supply electrical energy to remote areas. These networks are called standalone microgrid systems. In this paper, a standalone micro-grid system consisting of a Photovoltaic (PV) and Wind Energy Conversion System (WECS) based Permanent Magnet Synchronous Generator (PMSG) is being designed and controlled. Fuzzy logic-based Maximum Power Point Tracking (MPPT) is being applied to a boost converter to control and extract the maximum power available for the PV system. The control system is designed to deliver the required energy to a specific load, in all scenarios. The excess energy generated by the PV panel is used to charge the batteries when the energy generated by the PV panel exceeds the energy required by the load. When the electricity generated by the PV panels is insufficient to meet the load’s demands, the extra power is extracted from the charged batteries. In addition, the controller protects the battery banks in all conditions, including normal, overcharging, and overdischarging conditions. The controller should handle each case correctly. Under normal operation conditions (20% < State of Charge (SOC) < 80%), the controller functions as expected, regardless of the battery’s state of charge. When the SOC reaches 80%, a specific command is delivered, which shuts off the PV panel and the wind turbine. The PV panel and wind turbine cannot be connected until the SOC falls below a safe margin value of 75% in this controller. When the SOC goes below 20%, other commands are sent out to turn off the inverter and disconnect the loads. The electricity to the inverter is turned off until the batteries are charged again to a suitable value.


Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2521
Author(s):  
Alfredo Gil-Velasco ◽  
Carlos Aguilar-Castillo

There are multiples conditions that lead to partial shading conditions (PSC) in photovoltaic systems (PV). Under these conditions, the harvested energy decreases in the PV system. The maximum power point tracking (MPPT) controller aims to harvest the greatest amount of energy even under partial shading conditions. The simplest available MPPT algorithms fail on PSC, whereas the complex ones are effective but require high computational resources and experience in this type of systems. This paper presents a new MPPT algorithm that is simple but effective in tracking the global maximum power point even in PSC. The simulation and experimental results show excellent performance of the proposed algorithm. Additionally, a comparison with a previously proposed algorithm is presented. The comparison shows that the proposal in this paper is faster in tracking the maximum power point than complex algorithms.


2018 ◽  
Vol 7 (1) ◽  
pp. 66-85 ◽  
Author(s):  
Afef Badis ◽  
Mohamed Habib Boujmil ◽  
Mohamed Nejib Mansouri

This article concerns maximizing the energy reproduced from the photovoltaic (PV) system, ensured by using an efficient Maximum Power Point Tracking (MPPT) process. The process should be fast, rigorous and simple for implementation because the PV characteristics are extremely affected by fast changing conditions and Partial Shading (PS). PV systems are popularly known to have many peaks (one Global Peak (GP) and several local peaks). Therefore, the MPPT algorithm should be able to accurately detect the unique GP as the maximum power point (MPP), and avoid any other peak to mitigate the effect of (PS). Usually, with no shading, nearly all the conventional methods can easily reach the MPP with high efficiency. Nonetheless, they fail to extract the GP when PS occurs. To overcome this problem, Evolutionary Algorithms (AEs), namely the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are simulated and compared to the conventional methods (Perturb & Observe) under the same software.


Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4971
Author(s):  
Hegazy Rezk ◽  
Ahmed Fathy

A significant growth in PV (photovoltaic) system installations have been observed during the last decade. The PV array has a nonlinear output characteristic because of weather intermittency. Partial shading is an environmental phenomenon that causes multiple peaks in the power curve and has a negative effect on the efficiency of the conventional maximum power point tracking (MPPT) methods. This tends to have a substantial effect on the overall performance of the PV system. Therefore, to enhance the performance of the PV system under shading conditions, the global MPPT technique is mandatory to force the PV system to operate close to the global maximum. In this paper, for the first time, a stochastic fractal search (SFS) optimization algorithm is applied to solve the dilemma of tracking the global power of PV system based triple-junction solar cells under shading conditions. SFS has been nominated because it can converge to the best solution at a fast rate. Moreover, balance between exploration and exploitation phases is one of its main advantages. Therefore, the SFS algorithm has been selected to extract the global maximum power point (MPP) under partial shading conditions. To prove the superiority of the proposed global MPPT–SFS based tracker, several shading scenarios have been considered. The idea of changing the shading scenario is to change the position of the global MPP. The obtained results are compared with common optimizers: Antlion Optimizer (ALO), Cuckoo Search (CS), Flower Pollination Algorithm (FPA), Firefly-Algorithm (FA), Invasive-Weed-Optimization (IWO), JAYA and Gravitational Search Algorithm (GSA). The results of comparison confirmed the effectiveness and robustness of the proposed global MPPT–SFS based tracker over ALO, CS, FPA, FA, IWO, JAYA, and GSA.


2013 ◽  
Vol 441 ◽  
pp. 268-271
Author(s):  
De Da Sun ◽  
Da Hai Zhang ◽  
Yang Liu

Photovoltaic (PV) power systems are widely used today, so its useful to study how to make the PV maximum power output. In this paper a novel approach based on Support Vector Machine (SVM) for maximum power point tracking (MPPT) of PV systems is presented. The output power characteristics of PV cells vary with solar irradiation and temperature, so the controllers inputs is the level of solar radiation and ambient temperature of the PV module, and the voltage at maximum power point (MPP) is the output. Results show that the proposed MPPT controller based on SVM is sensitive to environmental changes and has high efficiency and less Mean Square Error (MSE).


2019 ◽  
Vol 8 (3) ◽  
pp. 5104-5110

In the last few years, several concepts have been developed in the field of Power Quality (PQ) improvements. Features of PQ plays a significant part in power system based applications. Nowadays, technologies in Renewable Energy Source (RES) have got more opportunities for promoting Photo-Voltaic (PV) for generating electric power. It may affect the reliability and stability of entire power system, also produces the switching frequency with irregular manner and variation within the certain region. Also, Incremental-Conductance (IC) method miserably fails to recognize Global Maximum Power Point (MPP) and gets trapped in one of the Local MPP. Since the conventional MPPT (Maximum Power Point Tracking) might not separate the maximum power of the P-V characteristic curve, a novel tracking system needs to be established. In this research work, Kinetic Gas Molecular Optimization (KGMO) is implemented with IC for improving the PQ by providing the adequate switching pulse to inverter for enhancing the system performance. The proposed method reduced the Total Harmonic Distortion (THD) up to 4.67 %, and the efficiency is observed by evaluation over the traditional Radial Basis Function Neural Network (RBFNN) and IC-MPPT techniques. The proposed method is implemented in the MATLAB/Simulink software to analyze the performance of PQ issues.


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