Carbon emission price combination prediction method

Abstract

The invention discloses a carbon emission price combination prediction method. The method includes the steps that 1, an original carbon emission price sequence is decomposed into a series of intrinsic function components through a variation mode decomposition algorithm; 2, an output variable is given, the input variable of each IMF component is determined through statistical tools comprising a partial autocorrelation function and a corresponding partial autocorrelation diagram thereof; 3, each IMF component is predicted through a Spiking neural network; 4, prediction results of all the IMF components are superimposed to obtain a predicted value corresponding to an original carbon emission price. By means of the method, prediction precision is effectively improved, and carbon emission price prediction can be well achieved.

Description

technical field [0001] The invention relates to a carbon emission price combination forecasting method, for CO 2 Precise prediction of emission price belongs to the field of information analysis and prediction technology in power system technology. Background technique [0002] The global warming caused by the excessive consumption of fossil fuels has become a major challenge to the current social and economic development. It has become the consensus and goal of all countries in the world to achieve a clean, efficient and low-carbon energy system. In 2005, the "Kyoto Protocol" agreement came into effect, marking the beginning of the use of market mechanisms to reduce greenhouse gas emissions, and the carbon trading market has developed rapidly around the world. As one of the main sources of carbon dioxide emissions, the power industry has huge emission reduction potential and obvious room for optimization. At present, many researches on electricity in the market environmen...

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Problems solved by technology

[0004] Purpose of the invention: The present invention aims at the problem that the accuracy of prediction results in the existing carbon emission price prediction technology is not high, and provides a carbon emission price combination prediction method based on VMD and SNN (Spiking Neural Network, SNN)

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