Research On The Photovoltaic MPPT Control System

Photovoltaic power generation is one of the ways using solar energy resources effectively. In recent years, it has gotten the world's attention and has been a rapid development. At present, one of the main problems faced by the photovoltaic power generation is the low conversion efficiency. One way to solve this problem is carrying out the maximum power point tracking in the photovoltaic power generation process.At present, many domestic and foreign literatures have proposed a variety of photovoltaic maximum power point tracking algorithm, and have made remarkable effect to improve the efficiency of photovoltaic power generation. Among them, the perturbation and observation method has been widely used because of its simple control idea, its algorithm is not complex and its low hardware requirements. However, the perturbation-step of the perturbation and observation method is difficult to be selected, leading it is hard to give consideration to improve both the dynamic responding speed and the steady-state tracking accuracy. According to this problem, the paper proposed a variable-step photovoltaic MPPT algorithm based on Adaptive Neuro-Fuzzy Inference.The main work and the achievements of this paper are as follows:1. Proposed a variable-step photovoltaic MPPT algorithm based on Adaptive Neuro-Fuzzy Inference after analyzeing the output characteristics of the photovoltaic cells and the basic principles of the various maximum power point tracking algorithms such as the perturbation and observation method. This algorithm uses the result of previous power difference divided by previous disturbance voltage difference, and then multiplied by a variable-step factor k as the next perturbation-step. Here, the variable-step factor k changes according to the Short-circuit current Isc, the relationship between them is trained by MATLAB's Adaptive Neuro-Fuzzy Inference System.2. Created the photovoltaic cells simulation model and the photovoltaic maximum power point tracking model in MATLAB, and then carried out the simulation and analysis. Verified the feasibility and effectiveness of the variable-step photovoltaic MPPT algorithm based on Adaptive Neuro-Fuzzy Inference.3. Designed a photovoltaic MPPT control system. Fulfilled the designation of the various hardware circuits such as the power circuit module and the control circuit module. Meanwhile, fulfilled the designation of the photovoltaic MPPT control system's software according to the system function requirement.4. Established the photovoltaic maximum power point tracking experiment platform and carried out experiments. Verified that the photovoltaic MPPT control system can work precisely and stablely and the variable-step photovoltaic MPPT algorithm based on Adaptive Neuro-Fuzzy Inference can track the maximum power point effectively.5. Finally, made a summary of the full text, and proposed some prospects for the further research.