Photovoltaic Power Generation Unit Life Prediction Based on Grey Forecast Model with Health Evaluation

In the photovoltaic power generation plant, health condition of each unit is regarded as a crucial index. Whether the life prediction is accurate or not determines the economic benefit of the plant. Among the current research and applications, either the designed system is too complex to be suitable for most of the cases, or lack of complete and scientific algorithm to support the analysis. In order to deal with the problems encountered, in this paper, a life prediction method for photovoltaic power plant based on GM(l,l) model is proposed. On the basis of PR calculation, the definition of Health with only four indicators for each unit is introduced, simplifying system calculation and improving the efficiency. According to the ' `Bathtub Curve' of the equipment, relate aging rate to Health. After calculating and transforming the collected data into sequence, the preparatory work for this method is completed. Further, take the aging rate sequence as the input and obtain the life prediction curves. This paper designs optimization for GM(l,l) grey forecast model, which makes the model self-correct the curves dynamically. This method is implemented with the data from a photovoltaic power plant. The results show that this method is well worth being adopted in reality.