scholarly journals A Novel PV Array Reconfiguration Algorithm Approach to Optimising Power Generation across Non-Uniformly Aged PV Arrays by Merely Repositioning

J ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. 32-53 ◽  
Author(s):  
Mohammed Alkahtani ◽  
Zuyu Wu ◽  
Colin Sokol Kuka ◽  
Muflah S. Alahammad ◽  
Kai Ni
Keyword(s):  
Cost Effective ◽  
Maximum Power ◽  
Global Maximum ◽  
Energy Potential ◽  
Maximum Power Point ◽  
Pv Array ◽  
Point Tracking ◽  
Novel Approach ◽  
Pv Modules ◽  
Power Point

Photovoltaic (PV) module working conditions lack consistency and PV array power outputs fluctuate due to the non-uniform impact that aging has on various PV modules in a PV array. No assessment has been conducted on the energy potential of a non-uniform PV array, despite the fact that the maximum power point (MPP) can be tracked by global maximum power point tracking (GMPPT). Therefore, the present work undertakes such an assessment by devising an algorithm to optimise the PV array electrical structure as the PV modules undergo aging in a non-uniform way. To enable PV arrays with non-uniform aging to produce as much power as possible and to make maintenance more cost-effective, the work puts forward a novel approach for reconfiguring PV arrays, where the PV modules are repositioned by retaining the aged PV modules. By this approach, the selection of the best reconfiguration topology necessitates the information on the electrical parameters associated with the PV modules in an array. Furthermore, the non-uniform aging of the PV modules can engender an incompatibility effect, which can be diminished in the proposed algorithm through iterative sorting of the modules in a hierarchical pattern. To determine how effective the method is for PV arrays with non-uniform aging and of different sizes, such as 3 × 4, 5 × 8 and 7 × 8 arrays, computer simulation and analysis have been conducted, with findings indicating that, irrespective of dimensions, PV arrays with non-uniform aging can have improved power yield.

scholarly journals A Fast GMPPT Algorithm Based on PV Characteristic for Partial Shading Conditions

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1142
Author(s):  
Başoğlu
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Duty Ratio ◽  
Global Maximum ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Pv Modules ◽  
Power Point

Photovoltaic (PV) modules experience some partial shading conditions (PSC) due to some various factors. In that kind of a condition, a few maximum power points (MPPs) possibly appear on the power-voltage (P-V) curve, which increases the tracking difficulties. It is known that maximum power point tracking (MPPT) may not be realized by hill climbing (HC) based conventional MPPT algorithms under PSCs. In this context, this paper presents a novel micro converter based algorithm that was developed by using P-V characteristics of PV modules. Unlike voltage or duty ratio scanning techniques, this paper introduces a new deciding method to determine the correct global MPP (GMPP) region. For this, the proposed method uses some duty ratios that were calculated corresponding to each MPP region. Thus, the initialization of duty ratio is done properly, which results in high tracking speed and accurate tracking of the GMPP. The other advantages of the proposed algorithm are structural simplicity, less computational burden, and ease of implementation with a basic microcontroller. The simulation results show that this algorithm has fast tracking capability and it manages to track GMPP for PSCs correctly, since it includes an artificial scanning procedure. Single ended primary inductance converter (SEPIC) is built in order to validate the proposed global maximum power point tracking (GMPPT) algorithm. The performance of the proposed GMPPT technique is verified by experimental studies. The results show that the proposed GMPPT technique is fast by up to five times than an adaptive full scanning strategy and improved IC algorithm. Furthermore, the proposed algorithm can be commercially used in micro converters, since it is compatible with small number of bypass diodes in a module.

An Advanced MPPT Based on Artificial Bee Colony Algorithm for MPPT Photovoltaic System under Partial Shading Condition

2017 ◽  
Vol 8 (2) ◽  
pp. 647 ◽  
Author(s):  
Salmi Hassan ◽  
Badri Abdelmajid ◽  
Zegrari Mourad ◽  
Sahel Aicha ◽  
Baghdad Abdenaceur
Keyword(s):  
Local Maximum ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Solar Irradiation ◽  
Global Maximum ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Pv Array ◽  
Point Tracking ◽  
Power Point

<p>Maximum power point tracking (MPPT) algorithms are employed in photovoltaic (PV) systems to make full utilization of PV array output power, which have a complex relationship between ambient temperature and solar irradiation. The power-voltage characteristic of PV array operating under partial shading conditions (PSC) exhibits multiple local maximum power points (LMPP). In this paper, an advanced algorithm has been presented to track the global maximum power point (GMPP) of PV. Compared with the Perturb and Observe (P&amp;O) techniques, the algorithm proposed the advantages of determining the location of GMPP whether partial shading is present.</p>

scholarly journals Improved Invasive Weed Optimization Algorithm for Global Maximum Power Point Tracking of PV Array Under Partial Shading Conditions

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Optimization Technique ◽  
Maximum Power ◽  
Global Maximum ◽  
Invasive Weed Optimization ◽  
Maximum Power Point ◽  
Invasive Weed ◽  
Partial Shading ◽  
Pv Array ◽  
Point Tracking ◽  
Power Point

Photovoltaic (PV) array under partial shading conditions (PSCs) has several maximum power points (MPPs) on the power-voltage curve of the PV array. These points; have a unique global peak (GP) and the others are local peaks (LPs). This paper aims to study an improved version of a heuristic optimization technique namely, Invasive Weed Optimization (IWO) to track the global maximum power point (GMPP) of a PV array which is an important issue. The proposed improved IWO (IIWO) algorithm modifies IWO to speed up the convergence and make the system more efficient. In addition to study the effect of changing input parameters of IIWO on its performance. An overall statistical evaluation of IIWO, with standard IWO and Particle Swarm Optimization (PSO) is executed under different shading conditions. The simulation results show that IIWO has faster and better convergence as it can reach the GMPP in less time compared with other techniques.

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