Research On The Maximum Power Point Tracking Strategy For Photovoltaic Power Generation Systems

With the introduction of the concept of sustainable development,the issue of traditional energy transformation has been widely focused on around the world.Among the many new energy systems,solar energy has become a key target for development as a renewable energy source with extensive reserves,green,safe and convenient.However,the low energy conversion rate of photovoltaic systems and the large upfront capital investment required limit the widespread diffusion of the industry.In order to maximise the output of the power generated by the PV system,a maximum power point tracking(MPPT)strategy has been introduced to reduce the loss of effective power.As the most important single component of a photovoltaic system,this paper begins with a study of the basic characteristics of photovoltaic cells.Simulation models of PV arrays with uniform illumination and partial shading were constructed,focusing on the extreme value point of the output characteristic curve and the variation of cell parameters in the dynamic environment;the common MPPT strategies corresponding to the two lighting situations are categorized and elaborated,and the problems of the original algorithmic strategies in the application process are pointed out;a hysteresis controlled variable step perturbation and observation(HP&O)algorithm is proposed for photovoltaic systems under uniform illumination,A hybrid algorithmic strategy of adaptive cuckoo search(ACS)and perturbation and observation(P&O)is proposed for the case of local shading.The proposed HP&O algorithm automatically adjusts the step size of the perturbation signal when the PV system is under uniform illumination,so that the tracking balances speed and stability;the introduction of hysteresis control to limit the operating point to the power hysteresis interval if the light intensity changes,avoiding shifts in the operating point due to misjudged conditions;the new inverse tangent function added to the variable step equation suppresses sudden increases in the amount of power change and stops spikes in the step size.The ACS-P&O hybrid algorithm is enabled to track the global maximum power point when local shading of the PV array occurs.The ACS algorithm is applied in the preliminary global search phase,and this improved algorithm adapts the switching probability in the cuckoo search algorithm with the step coefficients of Levy flight,and incorporates a boundary individual processing strategy to substantially improve the algorithm tracking speed and global performance;switching to a small-step P&O algorithm in the later stages of the local search prevents the presence of randomness in the intelligent algorithm from making the power output unstable in the convergence phase.Finally,to demonstrate that the proposed method has improved the MPPT efficiency of the PV power system,a simulation model of the PV power system is created in MATLAB/simulink software.The proposed algorithms are compared and validated in different external environments,the results show that the improved algorithm can successfully track to the maximum power point in any state and that the power generation efficiency of the PV system has been dramatically enhanced.