| Countries are working to stimulate the development of new energy sources and enhance the structure of old energy sources in an effort to lessen the harm that primary energy sources do to the environment as a result of the increasing depletion of fossil fuels and pollution.With the current rapid progress in technology and the increase in the number of smart devices,we now take electricity for granted in our daily lives.Solar energy is a clean,pollutant-free energy source that is renewable and has low-emission properties.Although photovoltaic power generation technology has advanced,there are still numerous problems to be resolved.the most crucial of which is maximizing power point tracking and solar cell power generating efficiency in complex environments is an important part of it.When there is some local shading conditions,the P-V curve of PV cells will show the characteristics of "multi-peak".When dealing with the multi-peak characteristic,it is difficult to follow the global maximum power point properly and fast,and it is simple to run into the local optimal problem,which ultimately results in the failure of tracking the maximum power point.At present,with some intelligent algorithms proposed,the performance in tracking the global maximum power has improved,avoiding the situation of falling into the local optimum,but their search speed is relatively slow,and the early output waveform fluctuates greatly so that it cannot play its proper effect.In this paper,We suggest a more effective whale-particle swarm hybrid method that will enhance system performance by more precisely tracking the maximum power point.The main work accomplished is as follows.Firstly,the PV cell model is built on MATLAB/Simulink simulation platform is applied,and its output characteristic curve is comprehensively analyzed,and it is concluded that the cell array is affected differently under different temperature and light intensity.In real life,it is very common for PV cells to be partially shaded in the process of use.By constructing a PV array model,controlling the variables through constant temperature and adjusting the light intensity to simulate the environmental conditions of partial shading,under partial external environment shading,we investigate the influence law of PV array performance as well as the multiple peaks of PV array output characteristics.After a comprehensive analysis of the control circuit,it was finally decided to select a Boost boost circuit for the DC-DC conversion unit.Second,the conventional MPPT control method is investigated,and the goal and guiding ideas of maximum power point tracking are briefly stated.,and straightforward introduces the traditional algorithm,and compares it with the simulation model of P&O and INC.The particle swarm optimization approach is presented and simulated for examination to address the issue of falling into local optimum and failing to track the global peak,and not tracking the global peak,and combined with the whale algorithm to propose an improved whale-particle swarm optimization hybrid algorithm(IWOA-PSO)by increasing the algorithm’s convergence factor and adding a random strategy factor,which optimizes the tracking performance and enables fast and stable tracking of the maximum power point.Last but not least,the management model is built on the MATLAB/Simulink simulation platform,and as a result,the simulation outcomes of the enhanced whale-particle swarm hybrid algorithmic program are evaluated in comparison to the whale algorithmic program and the particle swarm algorithmic program.MPPT adopts hybrid algorithm,which can effectively solve the problem that traditional methods are trapped in local optimal solution.The tracking speed and output power fluctuate little when reaching the maximum power point tracking.This improves the tracking speed and has good advantages compared with other algorithms. |
PDF Full Text Request