Performance prediction and fault alarm method for photovoltaic power station

Abstract

The invention discloses a performance prediction and fault alarm method for a photovoltaic power station. The method comprises the following steps of: a, setting the station of the power station; b, setting the operation mode of the power station; c, judging whether required real-time data or historical data exists or not; d, predicting the performance of the power station through an experience model if the state in the step a is that a new photovoltaic power station is required to be designed and the required real-time data or historical data in the step c does not exist, and predicting the performance of the power station through a data drive performance model if the required real-time data or historical data in the step c exists; e, predicting the performance of the power station through the data drive performance model or a polynomial regression model if the photovoltaic power station in the step a is operated and the required real-time data or historical data in the step c exists, and predicting the performance of the power station through the experience model if the required real-time data or historical data in the step c does not exist; f, comparing actual performance with the predicted performance, and performing fault alarm; and g, correcting the models on line by a Kalman filtering method and returning to the step c, and otherwise, directly returning to the step e. By the method, solar energy resources can be utilized to the maximum extent, and power utilization cost can be reduced; and the accuracy of performance prediction and fault diagnosis is improved.

Description

technical field [0001] The invention relates to a performance forecast and fault alarm method of a photovoltaic power station, which belongs to the technical field of solar photovoltaic power generation in advanced energy technologies. Background technique [0002] Due to the depletion of traditional energy resources and the improvement of power quality requirements in today's society, environmentally friendly and flexible photovoltaic power generation has been valued by countries all over the world. Solar photovoltaic power generation has become one of the most promising green energy utilization methods. However, the output of the photovoltaic power generation system is affected by factors such as solar radiation intensity, environment, operating conditions, and weather, and its power generation performance is a non-stationary random process. It is also very large. Compared with the large power grid, the photovoltaic power generation system will be an uncontrollable source,...

AI Technical Summary

Problems solved by technology

However, this invention can only predict the failure of the battery array, and cannot predict the failure of other photovoltaic devices such as inverters; and the accuracy of the data measured by the above method is limited, and the accuracy of the data is not high; finally, the invention needs Many devices such as voltage sensors and current sensors increase the system cost

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