scholarly journals COMPARISON OF MPPT ALGORITHMS FOR PHOTOVOLTAIC SYSTEMS UNDER UNIFORM IRRIADIANCE BETWEEN PSO AND P&O

2020 ◽  
Vol 4 (10) ◽  
pp. 68-77
Author(s):  
Ahmed Hossam EL-Din ◽  
S.S Mekhamer ◽  
Hadi M.El-Helw
Keyword(s):  
Particle Swarm Optimization ◽  
Conventional Method ◽  
Environmental Conditions ◽  
Hardware Implementation ◽  
Low Cost ◽  
Main Idea ◽  
Photovoltaic Systems ◽  
Swarm Optimization ◽  
Tracking Method ◽  
Very High

This paper shows a Comparison between Conventional Method [P&O] and particle swarm optimization [PSO] Based on MPPT Algorithms for Photovoltaic Systems under uniform irradiance and temperature. The main idea is to show that PSO method has a very high tracking speed and has the ability to track MPP under different environmental conditions in addition to an easy hardware implementation using a low-cost microcontroller. MATLAB simulations are carried out under very challenging conditions, namely irradiance and temperature, which reflect a change in the load [KW]. The proposed PSO tracking method Results will be compared with conventional method called [P&O] through MATLAB/SIMULINK.

Subtractive Clustering and Particle Swarm Optimization Based Fuzzy Classifier

2019 ◽  
Vol 8 (3) ◽  
pp. 108-122 ◽  
Author(s):  
Halima Salah ◽  
Mohamed Nemissi ◽  
Hamid Seridi ◽  
Herman Akdag
Keyword(s):  
Particle Swarm Optimization ◽  
State Of The Art ◽  
Particle Swarm ◽  
Main Idea ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Subtractive Clustering ◽  
Data Sets ◽  
Fuzzy Classifier ◽  
Swarm Optimization

Setting a compact and accurate rule base constitutes the principal objective in designing fuzzy rule-based classifiers. In this regard, the authors propose a designing scheme based on the combination of the subtractive clustering (SC) and the particle swarm optimization (PSO). The main idea relies on the application of the SC on each class separately and with a different radius in order to generate regions that are more accurate, and to represent each region by a fuzzy rule. However, the number of rules is then affected by the radiuses, which are the main preset parameters of the SC. The PSO is therefore used to define the optimal radiuses. To get good compromise accuracy-compactness, the authors propose using a multi-objective function for the PSO. The performances of the proposed method are tested on well-known data sets and compared with several state-of-the-art methods.

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