Abstract
With the decrease of disposable energy and the increase of social demand for power resources, photovoltaic power generation technology has been rapidly developed. The photovoltaic modules exposed outdoors for a long time accumulate serious ash, and the photovoltaic power generation efficiency is affected, so the photovoltaic modules need to be cleaned. Since various factors affecting the power generation efficiency of photovoltaic modules are difficult to quantify and mostly rely on the experience judgment of operation and maintenance personnel, this paper uses the historical operation data of photovoltaic power stations, comprehensively considers various influencing factors, establishes an intelligent cleaning data model, and combines the cleaning cost analysis to provide a basis for intelligent control of photovoltaic module cleaning robots.
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