Research On Maximum Power Point Tracking Control Strategy For Wind-solar Hybrid Power Generation System

As the performance of the solar-wind hybrid power system is strongly impacted by altitude,wind speed,air humidity,light intensity and other environmental conditions,the power output is usually unstable.That is,when the surrounding environment changes,the power output of the solar-wind hybrid system changes thereby.Based on the output characteristics of wind-solar hybrid power generation system,The simultaneous tracking control strategy based on geometric mean and the time-sharing tracking control strategy based on BP neural network prediction are studied.These two control strategies can be achieved with a DC-DC circuit to track the control of wind power and solar power generation system output power,compared with the traditional independent control strategy,you can save a number of converters.Simplify the structure and reduce costs.First of all,this thesis introduce the topology structure as well as the main components of the wind power generation system,photovoltaic power generation system,solar-wind hybrid power system,and the DC-DC.Given the parameters of the inverter in the system,the simulation model of each system is then built and the output attributes are analyzed.Second of all,a fuzzy control method is applied to track the output power of wind and photovoltaic generation system.By collecting the output power and duty cycle of the adjacent time system,the voltage duty cycle at the next time point can be calculated.And then use the geometric mean to find the average of the two duty cycle,with this average to adjust the wind and solar power generation system output voltage,thus ensuring that the wind-solar power generation system works at the maximum power point.The control strategy is not ideal when the output power of a single power generation system changes,and the power loss is large.However,the power loss caused by the control strategy is small when the output power of the wind power and the photovoltaic power generation system changes at the same time.Additionally,the BP neutral network is used to predict the wind speed and light intensity.Based on the forecast value,the wind power generation system and the photovoltaic power generation system are tracked in real-time.If the predicted wind speed is about to change,then the system will start tracking the wind power system;similarly,if there are changes in light intensity,then the system will start tracking the photovoltaic power generation system.By analyzing the simulation results of windpower and photovoltaic power generation system,the minimum decision value of the tracking target of solar-wind hybrid power system is reached.What is achieved will reduce the frequency of the tracking system,and thus reduce power lose and ensure the stability of the system output.The control strategy is better when the output power of a single power generation system changes only.When the output power of the wind power and the photovoltaic power generation system changes at the same time,the power loss caused by the time-sharing tracking control strategy is larger.By comparing the advantages and disadvantages of the above two methods,a new maximum power tracking control strategy combine the above two strategies is given,which can change the control strategy or switch the tracking object under different weather conditions.Effectively improve the power generation efficiency,reduce power consumption.Finally,a Matlab / Simulink simulation model of solar-wind hybrid power system is established.Through the analysis of the simulation results,it can be seen that within the normal range of the change in wind speed and light intensity,the designed control strategy is able to make the wind-solar power generation system switch the tracking target accordingly,realizing the time-sharing and real-time tracking of wind power and photovoltaic power generation system.The satisfying result ensures that the solar-wind hybrid power system works at the maximum power point.