Low cost microcontroller implementation of Takagi–Sugeno Fuzzy MPPT controller for photovoltaic systems

Maximum power point trackers have a significant role in optimizing the energy conversion efficiency in a photovoltaic system. The numeric achievements of MPPT algorithm can be implemented and tested by using several embedded boards as Digital Signal Processor, Field-Programmable Gate Array, Arduino, and dspace. Alternatively, for the low cost, availability and simplicity, the PIC microcontrollers can be used compared with the other hardware devices. Therefore, this paper presents the implementation of a Takagi–Sugeno fuzzy controller on a low cost PIC microcontroller, for tracking the maximum power point of a PV module. The PV system consists of a PV emulator, DC-DC converter, and resistive load. The different steps in design, simulation and realization of the T-S Fuzzy logic controller are discussed. The proposed controller system was evaluated by comparing its performance metrics, in terms of efficiency and the Integral Square Error, with existing technique in the literature. The results corresponding to the experimental validation show that the proposed MPPT controller is able to ensure a perfect tracking of the maximum power point with variation of irradiance and is performing better than reported in a previous work

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

In the field of wind turbine performance optimization, many techniques are employed to track the maximum power point (MPPT), one of the most commonly used MPPT algorithms is the perturb and observe technique (PO) because of its ease of implementation. However, the main disadvantage of this method is the lack of accuracy due to fluctuations around the maximum power point. In contrast, MPPT control employing neural networks proved to be an effective solution, in terms of accuracy. The contribution of this work is to propose a hybrid maximum power point tracking control using two types of MPPT control: neural network control (NNC) and the perturbation and observe method (PO), thus the PO method can offer better performance. Furthermore, this study aims to provide a comparison of the hybrid method with each algorithm and NNC. At the resulting duty cycle of the 2 methods, we applied the combination operation. A DC-DC boost converter is subjected to the hybrid MPPT control.  This converter is part of a wind energy conversion system employing a permanent magnet synchronous generator (PMSG). The chain is modeled using MATLAB/Simulink software. The effectiveness of the controller is tested at varying wind speeds. In terms of the Integral time absolute error (ITAE), using the PO technique, the ITAE is 9.72. But, if we apply the suggested technique, it is smaller at 4.55. The corresponding simulation results show that the proposed hybrid method performs best compared to the PO method. Simulation results ensure the performance of the proposed hybrid MPPT control.