Wind driven optimization algorithm based global MPPT for PV system under non-uniform solar irradiance

•Robust global MPPT technique based on wind driven optimization algorithm is proposed.•Partial shading condition for PV system is considered.•The proposed method is compared with other seven techniques.•Seven statistical metrics are used for the evaluation of each MPPT technique. This paper proposes...

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Bibliographic Details
Published in:Solar energy Vol. 180; pp. 429 - 444
Main Authors: Abdalla, Omer, Rezk, Hegazy, Ahmed, Emad M.
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 01.03.2019
Pergamon Press Inc
Subjects:
Algorithms
Errors
Evolutionary algorithms
Evolutionary computation
Feasibility studies
Genetic algorithms
Global MPPT
Inductance
Irradiance
Maximum power tracking
Modern optimization
Partial shading
Particle swarm optimization
Photovoltaic cells
Photovoltaics
PV system
Search algorithms
Shading
Solar cells
Solar energy
Statistical analysis
Statistics
Trigonometric functions
Wind
Partial shading
PV system
Global MPPT
Modern optimization
ISSN:0038-092X, 1471-1257
Online Access:Get full text
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Summary:•Robust global MPPT technique based on wind driven optimization algorithm is proposed.•Partial shading condition for PV system is considered.•The proposed method is compared with other seven techniques.•Seven statistical metrics are used for the evaluation of each MPPT technique. This paper proposes an accurate global maximum power point tracking (MPPT) technique based on Wind Driven Optimization (WDO) algorithm for photovoltaics system (PVS) under non-uniform solar irradiance. Under non-uniform solar irradiance or partial shading conditions (PSC), the power-voltage curve of the PVS has several maximum power points (MPPs), one of which is assumed to be the global peak. This condition complicates the optimal MPP tracking and decreases of the PVS efficiency. Conventional MPPT methods, such as Perturb & Observe, Hill Climbing and Incremental Inductance are likely to be trapped at one of the local MPPs. The major disadvantage of these methods is their incompetence to specify the global MPP under the above mentioned situation. To overcome this problem, global MPPT techniques based on modern optimization algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Harmony Search Algorithm (HSA), Bat Algorithm (Bat), Sine-Cosine Algorithm (SCA), Cuckoo Search (CS), and Genetic Algorithm (GA) are previously developed. The main contribution of this research is to introduce a novel global MPPT based on WDO algorithm. A comprehensive statistical evaluation of WDO, PSO, DE, HSA, Bat, SCA, CS and GA is carried out under different scenarios of shadowing conditions. Seven statistical metrics including the relative error, root mean square error, mean absolute error, standard deviation, success rate, convergence time and efficiency are used to evaluate the powerfulness and the feasibility of the proposed compared to the others. Therefore, the proposed MPPT based on WDO algorithm is considered to be the most effective and superior optimization tool compared to the corresponding ones.
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ISSN:0038-092X
1471-1257
DOI:10.1016/j.solener.2019.01.056