Maximum Power Point Tracking OF Partially Shading PV system Using Particle Swarm Optimization

Обухов, С. Г.; Ibrahim, Аhmed; Aboelsaud, Raef

doi:10.1145/3233347.3233375

Cited by 16 publications

(7 citation statements)

References 16 publications

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“…The non-conventional algorithms such as Particle Swarm Optimization [9], Grey Wolf Optimization [10], Ant Colony Optimization [11] and Artificial Bee Colony [12] that inspired by findings of Darwin related to the growth of the biological kinds [13], have acquired much attention because of their ensured convergence towards the global peak. Certainly, the ability to handle multi-peaks that found on the (powervoltage) P-V curve and convergence speed are among its most advantages [14].…”

Section: Introductionmentioning

confidence: 99%

An Improved Particle Swarm Optimization Algorithm for Maximum Power Point Tracking Of Photovoltaic Cells in Normal and Under Partial Shading Conditions.(Dept.E)

Samir

Elksasy

Saraya

et al. 2021

MEJ. Mansoura Engineering Journal

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Section: Introductionmentioning

confidence: 99%

An Improved Particle Swarm Optimization Algorithm for Maximum Power Point Tracking Of Photovoltaic Cells in Normal and Under Partial Shading Conditions.(Dept.E)

Samir

Elksasy

Saraya

et al. 2021

MEJ. Mansoura Engineering Journal

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“…The microgrid is constituted of energy sources, storage devices and loads. It is operated in two modes grid-connected mode and islanded mode [13]. The Microgrid complexity is usually occurred with flexible modes of operation and use of storage devices integration [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Design and simulation of a microgrid for TIH campus

Ali¹,

Saleh²,

Daoud³

et al. 2020

IJEECS

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<p><span>This paper proposes a methodology for designing and operating a microgrid (MG) for the main campus of the Technical Institution Hawija. In this MG, a battery energy storage system (BESS), photovoltaic (PV) generation system, and controllable loads are included. Due to the high penetration of the PVs, over-voltage issues may occur in this MG. A novel operation strategy is considered by coordinating the BESS, PVs, and loads to prevent power outages and accomplish a secure operation of this MG. In this proposed approach, droop controllers have been implemented to provide the appropriate references for the PVs and BESS to maintain the voltage of the MG within a secure range. The generation of the PVs may be curtailed to guarantee the fidelity of the voltage. The intended simulations will be based on MATLAB/Simulink to show the efficacy of the intended design.</span></p><script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS-MML_HTMLorMML&delayStartupUntil=configured"></script><script id="texAllTheThingsPageScript" type="text/javascript" src="chrome-extension://cbimabofgmfdkicghcadidpemeenbffn/js/pageScript.js"></script>

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“…Cell under PSC generates one global peak (GP) and many local peaks (LPs), but the tracking of GP under (PSCs) effectively are still a big challenge to the researchers [4][5][6][7][8]. Numerous of MPPT techniques have been classified in tracking the MPPT under PSCs, into traditional algorithms [9][10][11], intelligent algorithms [12][13][14][15] and hybrid algorithms [16][17][18][19][20][21][22]. The LPs under PSC can be tracked efficiently and accurately using conventional, soft computing or hyper MPPT algorithms.…”

Section: Introductionmentioning

confidence: 99%

Genetic algorithm to improve power output of photovoltaic system under partial shaded condition

Ibrahim¹,

Nor²,

Nawi³

et al. 2019

IJPEDS

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The Partial Shaded Condition (PSC) is a process of non-optimal power capture in photovoltaic (PV) system; it will happen when one or all the PV solar cells get shaded by external factors. This phenomenon makes a sudden change in cell irradiance and lead to non-optimal power capture and reduces the generated power in PV systems. Cell under PSC generates one global peak (GP) and many local peaks (LPs), but the tracking of GP under (PSCs) effectively are still a big challenge to the researchers. In this paper, Fuzzy Logic Control (FLC) and optimized FLC algorithms were developed to track the PV power during the PSCs. The configuration of both algorithms are designed, simulated and evaluated using MATLAB/Simulink and their performance was compared with other literature techniques to study their capability to track the MPPT under PSCs. Proposed GA-FLC achieved 0.7 S as tracking time to find and track the Global Peak of Maximum power Point (GMPP) under PSCs and the usage of buck/boost converter in this technique achieved 98.5% of tracking accuracy. GA-FLC shows good dynamic performance in terms of tracking accuracy and complexity under PSCs compared to other techniques.

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Maximum Power Point Tracking OF Partially Shading PV system Using Particle Swarm Optimization

Cited by 16 publications

References 16 publications

An Improved Particle Swarm Optimization Algorithm for Maximum Power Point Tracking Of Photovoltaic Cells in Normal and Under Partial Shading Conditions.(Dept.E)

An Improved Particle Swarm Optimization Algorithm for Maximum Power Point Tracking Of Photovoltaic Cells in Normal and Under Partial Shading Conditions.(Dept.E)

Design and simulation of a microgrid for TIH campus

Genetic algorithm to improve power output of photovoltaic system under partial shaded condition

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