scholarly journals Optimization-Based Capacitor Balancing Method with Selective DC Current Ripple Reduction for CHB Converters

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 243
Author(s):  
Luis Galván ◽  
Pablo Jesús Gómez ◽  
Eduardo Galván ◽  
Juan Manuel Carrasco

From its introduction to the present day, Cascaded H-Bridge multilevel converters were employed on numerous applications. However, their floating capacitor, while advantageous for some applications (such as photovoltaic) requires the usage of balancing methods by design. Over the years, several such methods were proposed and polished. Some of these methods use optimization techniques or inject a zero-sequence voltage to take advantage of the converter redundancies. This paper describes an optimization-based capacitor balancing method with additional features. It can drive each module DC-Link to a different voltage for independent maximum power point tracking in photovoltaic applications. Moreover, the user can specify the independent active power set points to modules connected to batteries or any other energy storage systems. Finally, DC current ripple can be reduced on some modules, which can extend the lifespan of any connected ultra-capacitors. The method as a whole is tested on real hardware and compared with the state-of-the-art. In its simplest configuration, the presented method shows greater speed, robustness, and current wave quality than the state-of-the-art alternative in spite of producing about 1/3 fewer commutations. Its other characteristics provide additional functionalities and improve the adaptability of the converter to other applications.

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 953
Author(s):  
Ali M. Eltamaly

The problem of partial shading has serious effects on the performance of photovoltaic (PV) systems. Adding a bypass diode in shunt to each PV module avoids hot-spot phenomena, but causes multi-peaks in the power–voltage (P–V) characteristics of the PV array, which cause traditional maximum power point tracking (MPPT) techniques to become trapped in local peaks. This problem has forced researchers to search for smart techniques to track global peaks and prevent the possibility of convergence at local peaks. Swarm optimization techniques have been used to fill this shortcoming; unfortunately, however, these techniques suffer from unacceptably long convergence time. Cuckoo search (CS) is one of the fastest and most reliable optimization techniques, making it an ideal option to be used as an MPPT of PV systems under dynamic partial shading conditions. The standard CS algorithm has a long conversion time, high failure rate, and high oscillations at steady state; this paper aims to overcome these problems and to fill this research gap by improving the performance of the CS. The results obtained from this technique are compared to five swarm optimization techniques. The comparison study shows the superiority of the improved CS strategy introduced in this paper over the other swarm optimization techniques.


Processes ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 356 ◽  
Author(s):  
Ai-Qing Tian ◽  
Shu-Chuan Chu ◽  
Jeng-Shyang Pan ◽  
Yongquan Liang

The conventional maximum power point tracking (MPPT) method fails in partially shaded conditions, because multiple peaks may appear on the power–voltage characteristic curve. The Pigeon-Inspired Optimization (PIO) algorithm is a new type of meta-heuristic algorithm. Aiming at this situation, this paper proposes a new type of algorithm that combines a new pigeon population algorithm named Parallel and Compact Pigeon-Inspired Optimization (PCPIO) with MPPT, which can solve the problem that MPPT cannot reach the near global maximum power point. This hybrid algorithm is fast, stable, and capable of globally optimizing the maximum power point tracking algorithm. Therefore, the purpose of this article is to study the performance of two optimization techniques. The two algorithms are Particle Swarm Algorithm (PSO) and improved pigeon algorithm. This paper first studies the mechanism of multi-peak output characteristics of photovoltaic arrays in complex environments, and then proposes a multi-peak MPPT algorithm based on a combination of an improved pigeon population algorithm and an incremental conductivity method. The improved pigeon algorithm is used to quickly locate near the maximum power point, and then the variable step size incremental method INC (incremental conductance) is used to accurately locate the maximum power point. A simulation was performed on Matlab/Simulink platform. The results prove that the method can achieve fast and accurate optimization under complex environmental conditions, effectively reduce power oscillations, enhance system stability, and achieve better control results.


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