Design And Research Of The Cleaning Time Early Warning System For Photovoltaic Plant Based On Environmental Acquisition

Solar energy is considered to be one of the most promising clean energies owing to its advantages of being non-toxic,widespread and renewable.In the meantime,photovoltaic(PV)is becoming the most important form of solar power generation.This is mainly because the PV modules,a core component of PV system,have several unique advantages,such as simple structure,stable characteristics and good reliability.However,the module is easily affected by ambient dust during its operation,and the accumulation of dust on its surface will reduce its conversion efficiency and generation benefits,even causing serious safety accidents.Therefore,it can be seen that timely dust cleaning is very important for keeping PV plant safe and efficient.Literature research indicates that,current clean strategies may lead to a loss of generation benefits after dust cleaning instead of increasing,although it indeed improves the power generation.Hence in this theory,investigations are performed to develop a new clean strategy based on real-time acquisition of environmental data,and to design a smart early warning system using such strategy.In the first part of this theory,a forecasting model of power generation is obtained by studying the correlations between three pairs of variables,including the weather and the peak sun hours(PSH),the dust and the peak power,and the plant construction time and the system efficiency.Then an acquisition appliance is innovatively designed in order to collect data for the above mentioned environmental variables.This appliance has an environment sensor which is made of two small solar cells with identical characteristics to PV modules.One of the two cells is used to detect the surface dust,and the other one is used to detect the sun radiation.After data processing,the peak power of dust module can be obtained as well as the PSH for the specific duration.Based on above forecasting model and acquisition appliance,this theory proposes a novel algorithm for cleaning strategy.This algorithm can guarantee the generation benefits of PV plant after cleaning operation,and maximize the benefits for certain duration.At last,the algorithm is verified by an outdoor experiment which is carried out in Chengdu.The results show that the intelligent warning system developed in this theory is feasible and applicable.The results of this theory provide a theoretical basis for maximizing the economic benefits of PV plant after dust clean,and establish a technical reference for the realization of intelligent,unmanned and convenient cleaning decision process.In addition,this theory also provides a data resource for the PV plant maintenance,and it has great significance for the development of PV industry.