No abstract

Maximum Power Point Tracking (MPPT) techniques are developed to harvest and supply maximum power to the load. This depends on the power generated and the MPPT accuracy. Under quick-changing weather conditions, Incremental Conductance (InCond) and numerous different algorithms may fail to track the exact Maximum Power Point (MPP) which may result in significant power loss. Fuzzy Logic (FL) based MPPT is quick and accurate in tracking the MPP, but the high complexity and the implementation difficulty are their main disadvantages. A novel FL-InCond MPPT improved technique is developed based on the features of InCond and FL techniques to overcome their drawbacks.The newly developed approach can automatically adjust the variation of the duty cycle for tracking the MPP with accuracy. The obtained results are compared with conventional Perturb and observe (P&O) and InCond MPPTs for grid-connected mode under fast weather conditions. It is demonstrated that the developed method outperforms the aforementioned MPPT techniques in terms of tracking response, efficiency and the delivered current quality.

No abstract

The intermittent nature of photovoltaic energy necessitates the incorporation of storage devices to ensure the continuality of loads feeding. In addition, it is important to model, control, and verify the operating of the designed system before implementation. Furthermore, the integration of power electronic interfaces plays a significant role in protecting the system and benefiting from solar energy. To this end, a buck converter is chosen to charge the battery and supply the supercapacitor. The control strategy is based on the maximum power point tracking techniques when the management algorithm recommends MPPT function mode. Otherwise, a feedback constant voltage PI controller is designed. Indeed, perturb and observe and incremental conductance are implemented and compared to analyze the system efficiency within the management strategy to charge the battery, switch between the controllers, and feed a supercapacitor in case of full battery charge. The obtained results using MATLAB/SIMULINK platform confirm the behaviour of the proposed strategy.

<p>Background subtraction is the first and basic stage in video analysis and smart surveillance to extract moving objects. In fact, the background subtraction library (BGSLibrary) was created by Andrews Sobral in 2012, which currently combines 43 background subtraction algorithms from the most popular and widely used in the field of video analysis. Each algorithm has its own characteristics, strengths and weaknesses in extracting moving objects. The evaluation allows the identification of these characteristics and helps researchers to design the best methods. Unfortunately, the literature lacks a comprehensive evaluation of the algorithms included in the library. Accordingly, the present work will evaluate these algorithms in the BGSLibrary through the segmentation performance, execution time and processor, so as to, achieve a perfect, comprehensive, real-time evaluation of the system. Indeed, a background modeling challenge (BMC) dataset was selected using the synthetic video with the presence of noise. Results are presented in tables, columns and foreground masks.</p>