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Xi’an University of Architecture and Technology (2018)

Research on Dust-accumulation Detection and Output Power Prediction Model of Building Photovoltaic Modules

从光杰;

Titre : Research on Dust-accumulation Detection and Output Power Prediction Model of Building Photovoltaic Modules

Auteur : 从光杰;

Grade : Master’s Theses 2018

Université : Xi’an University of Architecture and Technology

Résumé
With the development of green building and zero-energy building as well as maturity of photovoltaic(PV)power generation technology,and the application of building PV power generation system is increasingly widespread.However,Long-term dust-accumulation can lead to a significant drop in the output power of the building PV power generation system,affecting its effective use.Because of the output power of the building PV power generation system have the volatility and randomness,and after grid connection,it will bring problems to the safe and stable operation of the power grid.Thus in order to decrease the effect,it needs to accurately forecast the output power of the PV system.Actually,a large number of prediction methods of PV output power mainly consider the influence of meteorological factors,neglecting the effect of dust-accumulation,which leads to a decrease in the output power prediction accuracy.Hence,the research of PV output power prediction method considering the effect of dust-accumulation has important value.This paper takes the building PV system as the research object,and studies the effect of dust-accumulation on its output characteristics.To puts forward the detection method of surface area ash of PV modules,establishes the evaluation model of dust-accumulation degree,and builds the PV output power attenuation model on this basis.Integrate the meteorological factors and the factors that affect ash deposition,establish a PV short-term output power prediction model to improve the prediction accuracy of PV output power.The content of the paper is as follows:At first,the experimental analysis and analysis of the physicochemical characteristics of PV modules surface area ash results in : The gray surface area ofbuilding PV modules mainly comes from the soil and road dust,and some of the accumulated dust may originate from haze.Development of the building PV module output characteristics monitoring system,collected the power generation parameters and meteorological data of the dust-accumulation assembly and the cleaning assembly,compared and analyzed the effect of dust-accumulation on the output characteristics of PV modules,and analyzed and found that the output power of PV modules with continuous accumulation of dust for 12 days decrease by 8.87% ;At the same time,at the initial stage of accumulation of accumulated dust,the output power of PV modules decays rapidly.As time passes,the output power decays gradually.Secondly,the surface area dust-accumulation detection method and the evaluation model of dust-accumulation degree of building PV modules were proposed.Through the filtering and enhancement of preprocessed infrared images of the dust-stacked PV modules,the improved Otsu segmentation algorithm was used to process the infrared images,and the gray surface area of the PV modules was well identified,and a satisfactory detection effect was achieved.Finally,combined with dust-accumulation factors and meteorological factors,the PV output power BP neural network and SVM regression prediction model were established respectively.Two prediction models are used to predict the PV output power under different weather types.The prediction results show that : for the cloudy overcast PV output prediction,the BP neural network prediction model has the best prediction effect.For the sunny days,the SVM regression prediction model has the best prediction effect and the prediction accuracy is the highest.In short,the study of the effect of dust-accumulation on building photovoltaic components and their detection techniques can provide technical support for the later clean-up maintenance.At the same time,accurately predicting the output power of building PV module is of great significance to the safe and stable operation of the power grid and the operation management and optimal dispatch of the power grid

Mots clés : building PV module; Influence of dust-accumulation; dust-accumulation detection; prediction model;

Présentation (CNKI)

Page publiée le 19 mai 2019