Method and device for judging power generation state of photovoltaic power station based on neural network

The invention provides a photovoltaic power station power generation state discrimination method and device based on a neural network, and belongs to the technical field of new energy, and the method specifically comprises the steps: obtaining the real-time illumination intensity of a photovoltaic power station, and determining the maximum power point voltage of the photovoltaic power station; the working state of the photovoltaic power station is judged based on the difference value between the real-time grid-connected voltage and the maximum power point voltage; taking a difference value between the grid-connected voltage and the maximum power point voltage as a tracking error amount, and based on the real-time temperature data, the real-time humidity data, the tracking error amount and the grid-connected voltage waveform data, adopting a prediction model of a neural network algorithm to obtain a state value of the grid-connected equipment; based on temperature data, real-time illumination intensity and pho