Method for intelligent cleaning strategy of photovoltaic module, and intelligent cleaning control system for photovoltaic module
A photovoltaic module and control system technology, applied in general control systems, control/regulation systems, photovoltaic modules, etc., can solve problems such as the influence of photovoltaic module power generation efficiency, lack of intelligent cleaning strategies, lack of combination of geographical environment, and seasonal changes
Active Publication Date: 2019-08-23
NANTONG UNIVERSITY
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[0004] However, most of the cleaning solutions currently used by photovoltaic cleaning robots are traditional regular cleaning, which cleans photovoltaic modules at regular intervals. This method does not combine geographical environment, seasonal changes, weather factors, etc., and lacks corresponding intelligent cleaning. Strategy, too much cleaning will cause unnecessary loss of energy, too little cleaning will affect the power generation efficiency of photovoltaic modules, so it is necessary to propose an intelligent cleaning strategy and arrange the best cleaning time reasonably
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[0151] The installed capacity of a photovoltaic power station in Jiangsu is about 5MW (1MW=1000kW). For model verification, two inverters (500kW) of an array in a photovoltaic power station are selected, and the data of a photovoltaic power station in Jiangsu from December 1, 2017 to July 31, 2018 are taken. As a training set, the photovoltaic on-grid electricity price during this period is 0.98 yuan / (kW h), and the improved BP neural network prediction model is used to predict the power generation of photovoltaic modules from August 1, 2018 to August 28, 2018. According to The weather forecast knows that there is no bad weather during this period, and the weather type is mainly sunny or cloudy, and then the best cleaning time is obtained according to the intelligent cleaning data model.
[0152] Table 2 Experimental data table
[0153]
[0154]
[0155] As shown in Table 2, P r is the predicted power generation value based on the improved BP neural network, P a is the...
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The invention provides a method for the intelligent cleaning strategy of a photovoltaic module, and an intelligent cleaning control system for the photovoltaic module. The control system comprises a server system and a Web system. The method for the cleaning strategy comprises the following steps that: S1: the server system obtains data from an external system through a data interface and judges whether a photovoltaic module detection starting condition is conformed or not; S2: a power generation amount is predicted; S3: calculating a loss power generation amount; S4: analyzing cleaning cost;and S5: an optimal cleaning time control instruction is obtained, or a cleaning device operation maintenance advice does not need to be constructed. The intelligent cleaning strategy of the photovoltaic module combines geographical environments, weather factors and the like, a power generation amount loss value caused by the soot formation of the photovoltaic module is quantitatively analyzed, theproblem that an existing photovoltaic power station is in shortage in a corresponding intelligent cleaning strategy can be effectively solved, the cleaning efficiency of the photovoltaic module is improved, cleaning cost is lowered, and the economic efficiency of the photovoltaic power station is improved.
Description
technical field [0001] The invention relates to the technical field of photovoltaic module intelligent cleaning, in particular to a method and a control system for a photovoltaic module intelligent cleaning strategy. Background technique [0002] With the continuous development of photovoltaic technology and the continuous increase of photovoltaic installed capacity in my country, the economic benefits of photovoltaic power plants are particularly important. However, since the photovoltaic modules used in photovoltaic power plants are usually installed outdoors, the photovoltaic modules are not only affected by internal factors such as equipment aging, but also affected by external factors such as dust during operation. Studies have shown that the power generation performance of photovoltaic modules and the amount of dust deposited There is a negative correlation change, and the power generation efficiency of photovoltaic modules decreases by 25.5% for every 1 micron increas...
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Login to View More IPC IPC(8): G05B13/04H02S40/10
CPCG05B13/042H02S40/10Y02E10/50
Inventor 李跃华江小静何雨泽王进
Owner NANTONG UNIVERSITY