Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm

The global trend on harvesting the green energies from solar cells gains more attention in recent years as compared to fossil fuel. The Photovoltaic (PV) system represents a clean, sustainable, and free renewable energy source, yet the efficiency of the PV cells is affected by the daily environmental effects on its non-linear current-voltage (I-V) and power-voltage (P-V) characteristics. Given these shortcomings, a maximum power point tracking (MPPT) algorithm is a viable part of tracking the optimum power point despite the fluctuation of temperature and irradiance. The MPPT algorithms imply the optimal duty ratio to drive the matching converter for optimal maximum power tracking. MPPT algorithms can be categorized into classical methods and artificial intelligence-based methods. Among the conventional techniques, perturb and observe (P&O) is the most common method due to its simplicity of operation and easiness of implementation. However, it increments and decrements the duty ratio in fixed step sizes which impose inherited drawbacks such as slow response time and continuous oscillation around the maximum power point (MPP). As a result, low efficiency ratio is obtained. The artificial intelligent MPPT techniques have the advantage of the adaptive nature to control the non-linear systems. Fuzzy logic controller (FLC), as adaptive MPPT method, adaptively modifies the duty ratio variations which lead to faster convergence time, low oscillation, and higher output power ratio. However, an FLC of an inaccurate design of input parameters like the error (E) and the error derivative (CE) contribute to high oscillation, slow response time towards the MPP, and less efficiency. This thesis proposes a FLC controller that calculates the E and the previous duty ratio variations (ΔDn-1) as input parameters to adaptively modify the output duty ratio (Δd). The controller aims to eliminate the drawbacks of both conventional (FLC, P&O) algorithms in term of response time, settling time, oscillation level, and maximum power ratio. MATLAB/SIMULINK environment is used to design and develop the PV module, DC-DC boost converter, and MPPT algorithms. The steady state test and dynamic tests were used to test the performance of the algorithms. The simulation results at steady state conditions show the proposed FLC has better performance than the conventional algorithms in term of response time, settling time, oscillation around the MPP, and maximum efficiency. A further test on dynamic conditions shows the proposed FLC has a better transient response at low irradiance conditions. The experimental results validated the performance of the MPPT algorithms at steady state conditions in term of response time, oscillation, and MPP ratio. In conclusion, the proposed FLC has fulfilled the objectives of the study by eliminating the drawbacks of the conventional algorithms and achieved more efficient PV system.

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