Abstract
In this paper, two main contributions are presented to manage the power flow between a wind turbine and a solar power system. The first one is to use the fuzzy logic controller as an objective to find the maximum power point tracking, applied to a hybrid wind-solar system, at fixed atmospheric conditions. The second one is to respond to real-time control system constraints and to improve the generating system performance. For this, a hardware implementation of the proposed algorithm is performed using the Xilinx System Generator. The experimental simulation results show that the suggested system presents high accuracy and acceptable execution time performances. The proposed model and its control strategy offer a proper tool for optimizing the hybrid power system performance which we can use in smart house applications.
Highlights
Wind and solar energies present the most famous renewable energy sources which attract attention due to the decreasing fossil fuel reserves and environmental property impact
The first one uses classic algorithms such as hill-climbing (HC), perturbation and observation (P&O), and incremental conductance (IncCond). It is based on intelligent methods such as fuzzy logic, artificial neural network (ANN), and neurofuzzy, which is a combination between the two previous methods
The objective of the DC-DC boost converter is to help the power renewable energy voltage [13], which is in our work the solar and wind energies, to converge the reference value provided by the maximum power point tracking (MPPT) algorithm
Summary
Wind and solar energies present the most famous renewable energy sources which attract attention due to the decreasing fossil fuel reserves and environmental property impact. The idea to use the fuzzy logic controller is to control, respectively, the proportional-integral controller for wind turbines and the duty cycle (d) for solar energy to regularize successively the optimal rotor speed and the pulse-width modulation in the boost converter This algorithm does not require a specific detailed mathematical model or linearization, about an operating point, and it is independent from system parameter variations. To get the optimum performance and effective power of the wind-solar turbine at fixed atmospheric conditions, a second objective is studied, which is the implementation of both controllers This implementation is designed on Xilinx, which has the Xilinx System Generator (XSG) tools to facilitate the design. The results of a fuzzy logic controller implementation on FPGA are given in Section 5 before the conclusion which is the final part of this paper
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