Neural network prediction method for generated output of photovoltaic power station
A power generation and neural network technology, applied in forecasting, instrumentation, data processing applications, etc., to achieve great economic and social benefits, reduce adverse effects, and improve power generation efficiency
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[0025] Such as figure 1 shown, including steps,
[0026] 1) Establishment of prediction model
[0027] In the power generation prediction model, only the data of the day before the prediction day is used, 12 hours at night are removed, and the power generation per hour is used as an input variable, a total of 12 data, and the average power generation corresponding to each hour is obtained through calculation;
[0028] The output power of the photovoltaic array per unit area is P=nSI (1?0.005(t + 25)), where n is the conversion efficiency; S is the array area; I is the solar radiation intensity; t is the atmospheric temperature;
[0029] 2) Design of prediction model
[0030] The BP neural network is used to design the photovoltaic array power generation prediction model. The BP neural network is a multi-layer forward network with one-way propagation. The output of the input layer node is equal to its input, and wij is the connection between the input layer and the hidden lay...
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