To study the effect of dust on performance of photovoltaic power generation

a laboratory bench was built to collect daily power generation data of clean and polluted photovoltaic strings while monitoring meteorological data to analyze the influence of dust accumulation and weather on power generation performance of photovoltaic modules. The results indicate that

the increase in PM2.5 mass concentration in winter and the frequent occurrence of sandstorms in spring lead to a significant accumulation of dust on surface of the photovoltaic modules

resulting in a rapid increase in cumulative power generation losses. However

in summer

due to increased precipitation

dust is difficult to accumulate on photovoltaic modules

resulting in a slow increase in cumulative power generation losses. In addition

the DTW algorithm is employed to find similar days. Firstly

the entropy method is used to calculate the weights of each meteorological parameter. Then

the DTW values corresponding to each meteorological parameter on each historical day are calculated in reverse chronological order

multiplied by their weights

and added together to obtain the comprehensive DTW value for each historical day. By comparing the comprehensive DTW values of each historical day

the meteorological similar day that is closest to the current day is selected. In order to avoid extreme weather conditions

a portion of the dataset is selected as the validation set

and the criteria for finding similar days are optimized. The data from 9:00 to 15:00each day is divided into three time periods for analysis

and the condition that the average solar irradiance is not less than 600 W/m~2 is set. After optimization

the evaluation index determination coefficient of the prediction model is 0.83

and the root mean square error is 0.22

indicating a significant improvement in prediction performance. Finally

the algorithm is used to develop a cleaning strategy for the photovoltaic power plant. After comparing the cumulative power generation loss with the cleaning cost

it is determined that the power plant should be cleaned every 28 days under long-term non rainfall conditions.