METHOD FOR PREDICTING A FUTURE TIMING OF LOWERING OF CURRENT VALUE OR POWER GENERATION QUANTITY OF SOLAR POWER GENERATION SYSTEM

摘要

A method for predicting a future timing when the current value or power generation quantity of a module, string or power conditioner will have been lowered by a specific level from its present current value or power generation quantity. This method makes it possible to know an appropriate timing when a maintenance of the solar power generation system is to be performed, and attain a planned maintenance.

主权项

1. A method for predicting a future timing when the current value or power generation quantity of a solar cell module, solar cell string or power conditioner will have been lowered by a specific level from the current value or power generation quantity thereof at present, wherein the solar cell module, solar cell string or power conditioner is out of the entire modules, strings, and power conditioners in a solar power generation system including a plurality of power conditioners in each of which a plurality of solar cell strings each including a plurality of solar cell modules connected in series to each other are connected in parallel to each other, characterized in that the method includes:
gaining data on the current value or power generation quantity of the solar cell module, solar cell string or power conditioner, which is a prediction target; gaining data on the current value or power generation quantity of a different and comparative solar cell module, solar cell string or power conditioner having one or more specific relevancies with the prediction target about a physically positional adjacent relationship, a physically positional interval relationship, a similarity of past data values, and/or a structural similarity, wherein the different and comparative solar cell module, solar cell string or power conditioner is out of the entire modules, strings, and power conditioners in the solar power generation system; calculating an absolute degree of grey incidence from these gained data; using a digital grey predictive model to calculate, from the calculated absolute degree of grey incidence, the degree of incidence between data at present on the prediction target and data at present on the comparative target, and the degree of incidence between future data on the prediction target and future data on the comparative target; and indicating a future timing when the degree of incidence between the future data will have been lowered by a specific level from the degree of incidence between the data at present, in the prediction target compared with the comparative target.