METHOD FOR ANALYZING ELECTRIC POWER TRADING DATA STORED IN BLOCKCHAIN BASED ON NEURAL NETWORK

摘要

The present invention relates to a method for analyzing electric power trading data stored in a blockchain based on a neural network, which records trading between a power prosumer and a power consumer and analyzes and predicts a power trading time frequency by power prosumer household, a power demand amount by time slot of a household, and a power price through a neural network technology. According to the present invention, the method comprises the step of: allowing a power prosumer power sensor to collect power trading data; allowing a power prosumer to request the power prosumer power sensor to verify the collected power trading data to record power trading in a blockchain and allowing the power prosumer to perform agreement to record the power trading data in a power trading information blockchain; acquiring and storing power trading information corresponding to a power consumer in a power information analysis database; and analyzing and predicting power trade and a power price of the power consumer through the neural network technology based on the data stored in the power information analysis database. Accordingly, the present invention can cope with a behavior for forging/altering power trading, can record power trading verified through agreement among power consumers, and can realize systematic consumption through prediction of a power trading demand amount and power price.;COPYRIGHT KIPO 2019