Microgrid power big data transaction management system applying blockchain and artificial intelligence

Abstract

The invention discloses a microgrid power big data transaction management system applying a blockchain and artificial intelligence. The method comprises the following steps that an electricity purchasing receiving module organizes an electricity purchasing unit price of which transaction is completed according to previous electricity consumption data records of an electricity consumption side, andrecords the electric quantity required to be purchased at the power utilization side; an electricity price adjusting module uses the average value of the electricity purchasing unit prices which havecompleted the transaction as an initial electricity price and compares the total electricity generation amount of all the current electricity generation sides with the total electricity quantity which needs to be purchased by all the electricity utilization sides, and the intelligent matching module screens the electricity generation sides which can meet the electricity quantity which needs to bepurchased by the electricity utilization sides and selects the appropriate electricity generation sides for matching; according to the invention, on the basis of artificial intelligence, the blockchain technology is combined at the same time, so the intelligence and decentralization of the transaction management system and the non-tampering performance of data are enhanced.

Description

technical field [0001] The invention relates to power transaction management, in particular to a microgrid power big data transaction management system using blockchain and artificial intelligence. Background technique [0002] At present, power trading is concentrated on a small number of large platforms, and the degree of centralization is relatively serious. The control of the interests of the power generation side and the power consumption side is concentrated on these platforms. Therefore, power system failures are prone to occur, and the scope of influence also increases. Large; because the transaction between the power generation side and the power consumption side does not need to meet, the first thing to be solved is the key needs of all parties involved in the transaction, and strive for the accuracy and speed of the transaction. In this way, it seems that the traditional power transaction lacks personalized adjustments. Unrelated transactions can also be affected....

AI Technical Summary

Problems solved by technology

[0003] There are many power trading systems that allocate resources on the power generation side based on the matching of power supply and power consumption to achieve real-time and effective distribution of power resources. However, such methods do not comprehensively consider the geographical location of power distribution, power loss, and power consumption.

With the reduction of power participants, the emergence of productive consumers and the use of electricity by some flexible loads, the complexity of power trading is relatively high, and the simultaneous participation of all parties greatly increases the difficulty of power trading calculations. Occurs evenly, and the stability is poor

In terms of transaction matching, most systems will speculate on the transaction situation, but the existing prediction methods have shortcomings due to the volatility of historical data, strong time-varying characteristics, and nonlinearity. Causes large guessing errors, further affecting the generation and execution of transactions

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