Electric power spot service system fault prediction method and device, computer equipment and storage medium

Abstract

The invention discloses an electric power spot service system fault prediction method and device, computer equipment and a storage medium, and the method comprises the steps: receiving real-time equipment parameter time sequence data of hardware equipment in an electric power spot service system, inputting a first type of deep neural network to obtain the fault probability of the hardware equipment, wherein the first-class deep neural network is obtained through pre-construction, and comprises the steps of receiving equipment parameter time sequence data of hardware equipment in an electric power spot service system before a fault, and constructing an equipment parameter dictionary according to the equipment parameter time sequence data; performing vectorization processing on the equipment parameters by using the equipment parameter dictionary to obtain vectorized equipment parameter time sequence data and training data; and carrying out fine-tuning transfer learning on the training data by using the deep neural network to obtain the first-class deep neural network. According to the invention, safe operation and reliable operation of an electric power spot market and a business system are guaranteed.

Description

technical field [0001] The present application relates to the field of deep learning, in particular to a method, device, computer equipment and storage medium for fault prediction of a power spot business system. Background technique [0002] Since the British power industry revolution in the 1990s, the construction of power markets has gone through decades all over the world. At present, many countries in the world have established electricity markets, and the spot market is an extremely critical link. It has established a market organization form that is closely integrated with the operation of the power system in a short time sequence. The power spot market mainly includes the day-ahead, intra-day and real-time trading markets for ancillary services such as electric energy and backup. [0003] In order to ensure the normal operation of the power spot market business and the safe and stable operation of the power grid, the construction of the power spot business system ha...

AI Technical Summary

Problems solved by technology

However, due to the complexity of power grid equipment, the close correlation between equipment, the high frequency of transactions in the power spot market, the variety of transactions, the complexity of the trading system, an

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