Integrated energy management converter based on maximum power point tracking for photovoltaic solar system

This paper presents an integrated power control system for photovoltaic systems based on maximum power point tracking (MPPT). The architecture presented in this paper is designed to extract more power from photovoltaic panels under different partial obscuring conditions. To control the MPPT block, the integrated system used the ripple correlation control algorithm (RCC), as well as a high-efficiency synchronous direct current (DC-DC) boost power converter. Using 180 nm complementary metal-oxide-semiconductor (CMOS) technology, the proposed MPPT was designed, simulated, and layout in virtuoso cadence. The system is attached to a two-cell in series that generates a 5.2 V average output voltage, 656.6 mA average output current, and power efficiency of 95%. The final design occupies only 1.68 mm2.

Artificial Neural Network Based MPPT Algorithm for Modern Household with Electric Vehicle

This paper deals with implementation of artificial neural network in the maximum power point tracking (MPPT) controller algorithm for modern household where electric vehicle (EV) was purchased. The proposed MPPT algorithm was designed to achieve the best possible efficiency of the MPP (maximum power point) tracking and the best possible energy harvesting to charge the EV’s battery. The artificial neural networks have strong advantage in fast input to output response of signals and the finding of MPP is faster than in commonly used algorithms. In this article, the optimised simulation model based on artificial neural network will be introduced. The proposed artificial neural network algorithm was designed for non-shielded photovoltaic panels.

An Alternative Perturbation and Observation Modifier Maximum Power Point Tracking of PV Systems

Under the current situation, it is necessary to harness solar energy to generate more electricity. However, the disadvantage of solar energy is that it takes a lot of space to install solar panels. An option to optimize PV systems is to improve the maximum power point tracking (MPPT) algorithm based on symmetrical management has the advantage of being easy to use without updating the devices. The improved algorithm achieves symmetry between the maximum power point (MPP) and the output of the PV array, resulting in less power loss and increased system efficiency. This paper presents the MPPT of photovoltaic using the current control modifier perturbation and observation plus fuzzy logic control (CCMP&O−FLC MPPT). The algorithm of CCMP&O−FLC MPPT is applied to reduce the setting time and to reduce oscillation around the set-point at a steady state. This concept was experimented with using a boost converter with MATLAB/Simulink software package and implemented by STM32F4VGA microcontroller. The simulation and experiment results are obtained by comparison with traditional P&O under similar operating conditions. The CCMP&O−FLC MPPT can track MPP faster when the irradiation is rapidly changing and, therefore, can reduce the PV system losses. In addition, the advantages of this proposed method can also be applied to improve the performance of existing systems without modifying existing equipment, unlike modern methods that cannot be applied to older systems. The results showed that the MPPT time and the power output efficiency of the proposed algorithm were 146 milliseconds and 99.5%, respectively.