Photovoltaic assembly power gray scale prediction algorithm based on history power data

Abstract

The invention discloses a photovoltaic module power grayscale prediction algorithm based on historical power data, which includes the following steps in turn: step 1, select one or more groups of photovoltaic module arrays in the photovoltaic power station as the monitoring group; step 2, select the photovoltaic module in the monitoring group Set up a monitoring subsystem at the array to collect power generation data and ash accumulation data; step 3, establish a function model based on the power generation data and ash accumulation data, and obtain the functional relationship between power generation data and ash accumulation data; step 3, monitor through the monitoring subsystem Power generation data and ash accumulation data for a period of time and collect data; step 4, establish a comparison database for the relationship between ash accumulation data and power data; The dust accumulation data corresponding to the power data of the photovoltaic module array. It is convenient for managers to obtain dust accumulation data from power data, and avoid the influence of dust on the surface of photovoltaic modules on power generation efficiency.

Description

technical field [0001] The invention relates to a photovoltaic module, in particular to a power grayscale prediction algorithm of a photovoltaic module based on historical power data. Background technique [0002] The solar photovoltaic grid-connected power generation system converts solar energy into electrical energy, and directly sends the electrical energy to the grid through the grid-connected inverter without going through battery energy storage. Grid-connected solar power generation represents the development direction of solar power and is the most attractive energy utilization technology in the 21st century. Compared with the off-grid solar power generation system, the grid-connected power generation system has the following advantages: use clean, renewable natural energy solar energy to generate electricity, do not consume non-renewable, carbon-containing fossil energy with limited resources, and have no greenhouse gases and The discharge of pollutants is in harmo...

AI Technical Summary

Problems solved by technology

[0005] The invention solves the problem in the prior art that the amount of dust in the photovoltaic module array of a photovoltaic power station directly affects the power generation power of the photovoltaic module, and provides a grayscale prediction algorithm for the power of photovoltaic modules based on historical power data. The current power generation power of