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The partial shading is one of most critical problems facing the Maximum Power Point Tracking (MPPT) techniques for photovoltaic systems. This paper provides a review of challenges and opportunities regarding the problem of partial shading. In addition, it introduces a new technique for tracking the Global Maximum Power Point (GMPP) under different Partial Shading Conditions (PSC). The technique utilizes a two-stage algorithm to accomplish the tracking process efficiently. In the first stage, it applies a Genetic Algorithm (GA) to get the nearest point to the GMPP. In the second stage, it utilizes a new and fast MPPT algorithm to search for the target GMPP starting from the nearest point fetched in step one. In order to evaluate the new technique, a complete microcontroller based prototype is implemented and tested. The experimental results show that the new technique reaches directly to the GMPP in very short time and with limited steady state oscillations. Accordingly, the new technique has a significant improvement in energy extraction efficiency from the photovoltaic array to the load. [ABSTRACT FROM AUTHOR]

Batteries are the power tank of solar power systems. They play the role of power supply when the sun does not shine. This paper provides a review of battery charging control techniques for photovoltaic systems. In addition, it presents a new battery charge controller that keeps on the good features and resolves the drawbacks and limitations of the traditional controllers. The new controller is based on a newly developed maximum power point tracking (MPPT) technique enabling very fast maximum power point (MPP) capture. Moreover, it utilizes the constant current, constant voltage (CCCV) charging scheme to reduce the battery charging time. In addition, it enables accessing all system parameters remotely for monitoring and administration purposes. In order to determine the performance parameters of the proposed controller, a prototype was implemented together with microcontroller based DC–DC converter. The experimental results show that, the new controller tracks the MPP faster than the conventional controllers do. Moreover, the charging period is significantly reduced. Moreover, the proposed controller has high accuracy and minimizes the steady state oscillation errors around the target MPP. [ABSTRACT FROM AUTHOR]

The development of maximum power point tracking (MPPT) is continuing in order to increase the energy transfer efficiency of the solar photovoltaic system. This paper provides a review of the conventional maximum power point tracking techniques that is enhanced by the presentation of a new technique. The new method is based on a genetic neural algorithm in order to predict the closest point to the maximum power point (MPP), which will be the kickoff point of the search process. Not only does the new technique start the search process from the nearest point to the MPP, but also the developed search algorithm is very fast. Consequently, the time taken to reach the MPP is reduced. In order to determine the new MPPT performance, a complete photovoltaic generator system is modeled and simulated using the MATLAB/SIMULINK package. Simulation results show that the new technique reaches the MPP in less than 100 sample times compared to tens of thousands of samples for conventional methods. Furthermore, the new technique reaches directly the target MPP with small deviation from the intended values. Consequently, the new technique has a significant improvement in energy extraction efficiency from the photovoltaic array to the load, in addition to higher tracking speed and system stability compared to the conventional ones. [ABSTRACT FROM AUTHOR]