scholarly journals A Novel Pigeon-Inspired Optimization Based MPPT Technique for PV Systems

Processes ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 356 ◽  
Author(s):  
Ai-Qing Tian ◽  
Shu-Chuan Chu ◽  
Jeng-Shyang Pan ◽  
Yongquan Liang
Keyword(s):  
Maximum Power Point Tracking ◽  
Optimization Techniques ◽  
Maximum Power ◽  
System Stability ◽  
Global Maximum ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
New Type ◽  
Power Point

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.

scholarly journals Meta-Heuristic Optimization Techniques Used for Maximum Power Point Tracking in Solar PV System

Electronics ◽  
2021 ◽  
Vol 10 (19) ◽  
pp. 2419
Author(s):  
Preeti Verma ◽  
Afroz Alam ◽  
Adil Sarwar ◽  
Mohd Tariq ◽  
Hani Vahedi ◽  
...  
Keyword(s):  
Maximum Power Point Tracking ◽  
Optimization Techniques ◽  
Maximum Power ◽  
Global Maximum ◽  
Solar Pv ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

A critical advancement in solar photovoltaic (PV) establishment has led to robust acceleration towards the evolution of new MPPT techniques. The sun-oriented PV framework has a non-linear characteristic in varying climatic conditions, which considerably impact the PV framework yield. Furthermore, the partial shading condition (PSC) causes major problems, such as a drop in the output power yield and multiple peaks in the P–V attribute. Hence, following the global maximum power point (GMPP) under PSC is a demanding problem. Subsequently, different maximum power point tracking (MPPT) strategies have been utilized to improve the yield of a PV framework. However, the disarray lies in choosing the best MPPT technique from the wide algorithms for a particular purpose. Each algorithm has its benefits and drawbacks. Hence, there is a fundamental need for an appropriate audit of the MPPT strategies from time to time. This article presents new works done in the global power point tracking (GMPPT) algorithm field under the PSCs. It sums up different MPPT strategies alongside their working principle, mathematical representation, and flow charts. Moreover, tables depicted in this study briefly organize the significant attributes of algorithms. This work will serve as a reference for sorting an MPPT technique while designing PV systems.

Sign in / Sign up

Export Citation Format

Share Document