Output power classification forecasting system suitable for full life circle of photovoltaic system

Abstract

The invention discloses an output power classification forecasting system suitable for full life circle of a photovoltaic system. The output power classification forecasting system comprises a basic information storage module, a database module, a prediction model judgment module, a prediction data preprocessing module and a prediction modeling module. The system selects different prediction models to carry out training and predication according to data types and operation time of the photovoltaic system, is a modularized and multi-type photovoltaic system output power prediction system, can be suitable for output power prediction requirements of a majority of photovoltaic systems at present, can carry out customization according to the scale of the photovoltaic system and user requirements and the like, can both meet economic requirement and reliability requirement, and has good adaptability and transplantability. Meanwhile, the prediction method can update automatically; the prediction system can carry out automatic operation management; and higher prediction precision and stability are achieved.

Description

technical field [0001] The invention relates to the field of photovoltaic technology, in particular to an output power classification prediction system suitable for the entire life cycle of a photovoltaic system. Background technique [0002] Since the beginning of the 21st century, the world's energy supply has continued to be tense, and the development and utilization of clean and efficient renewable energy is the main way to solve future energy problems. At present, solar photovoltaic power generation is the fastest-growing renewable energy power generation technology. It is predicted that solar photovoltaic power generation will occupy an important seat in the world's energy consumption in the 21st century. It will not only replace some conventional energy sources, but also become the main body of world energy supply. . However, solar photovoltaic power generation is different from traditional power generation units. The output power of photovoltaic system has the chara...

AI Technical Summary

Problems solved by technology

[0004] In order to improve the prediction accuracy of photovoltaic power, the above-mentioned model input data types should be obtained as much as possible, but due to the limitation of the scale and geographical location of the photovoltaic system, it is usually impossible to obtain complete input data types

Traditional photovoltaic power forecasting systems usually only target a single combination of input data types, so the adaptability of the forecasting system is poor. In addition, these forecasting systems usually need to use more input data types, regardless of the difficulty of data acquisition. For installation The power prediction of photovoltaic systems in remote areas and islands is difficult to apply multiple input data types as input prediction systems

In addition, the type of data that a photovoltaic system can obtain during its entire life cycle is not fixed, that is, the power prediction method from the planning stage of the photovoltaic system to the power prediction method in the later stage of operation should change according to the change of the input data type of the prediction model, while the traditional PV forecasting systems often do not take this into account

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