A Maximum Power Point Tracking Technilogy For Fuel Cells/Photovoltaic Using Cloud Model Based Intelligent Controller

Due to the lack of environmental pollution and non-renewable energy sources,vigorously developing renewable energy has become a trend in today’s society.As a form of new energy,fuel cells and photovoltaic cells have demonstrated superior performance in large-scale clean power generation,automotive power,and military applications.Maximum Power Point Tracking(MPPT)is an effective means for improving the conversion efficiency of fuel cells/photovoltaic energy,and is a key technology that must be performed before it is put into use and connected to the grid.Aiming at the problem of tracking speed and accuracy in maximum power tracking,combined with the basic principle of disturbance observation method,this paper proposes a method of variable step MPPT based on cloud intelligent controller,using a control algorithm to achieve two kinds of objects(fuel cells And photovoltaic cells)MPPT control.Firstly,the power generation principles of fuel cell and photovoltaic cell were analyzed respectively,and the simulation model was constructed by Matlab/Simulink.Emphasis on the simulation analysis of their output characteristics,in-depth study of changes in the power-voltage curve caused by changes in the external environment and the maximum power point changes,laid the foundation for the follow-up maximum power tracking.Secondly,the Boost Chopper circuit is introduced to implement the MPPT technology.The impedance matching is performed by adjusting the duty cycle of the fully-controlled switching device in the boost chopper circuit.The equivalent circuit diagram of the circuit establishes a simulation model.The working principles of disturbance observation method and fuzzy control method are briefly introduced and verified by simulation.The advantages and disadvantages of the two methods are also illustrated.Finally,the artificial intelligence cloud model algorithm is introduced.It can realize qualitative and quantitative bidirectional conversion through cloud generator,aiming at combining randomness and fuzziness.Combining with cloud model theory,a variable-step intelligent MPPT tracking method is proposed.On the basis of formulating and implementing the MPPT cloud model rule base,cloud intelligent controllers for the fuel cell MPPT cloud intelligent controller and the photovoltaic cell MPPT were respectively established.This method effectively solves the problem of the misjudgment of disturbance observation in the external conditions and the difficulty of designing precise membership in fuzzy control.The feasibility of the method is verified by Matlab/Simulink simulation,and compared with disturbance observation and fuzzy control.The results show that this strategy can quickly and accurately track the maximum power point,with the advantages of fast convergence and good stability.