Research on Automatic Prediction of New Energy Consumption in Distribution Networks Under Distributed Photovoltaic Access
The difficulty of predicting the consumption of new energy in the distribution network under distributed photovoltaic access has increased,and the current methods have relatively high deviations and low confidence in practical applications,which cannot achieve the expected prediction effect.Therefore,a study on automatic prediction of the consumption of new energy in the distribution network under distributed photovoltaic access is proposed.Select the factors affecting the consumption of new energy from two aspects:The power supply side and the power consumption side,and collect relevant data for normalization processing.Use a bidirectional long short-term memory network to learn and analyze the factors affecting the consumption amount,predict the consumption amount of new energy,and achieve automatic prediction of the consumption amount of new energy in the distribution grid under distributed photovoltaic access.Experimental results have shown that the design method predicts a relative deviation of no more than 1%and a confidence level of no less than 97%,which can achieve accurate and automated prediction of the consumption of new energy in the distribution network.
distributed photovoltaicdistribution networknew energyconsumptionautomatic predictionbidirectional long short-term memory network
NETL
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