Research On Grey Multivariate Prediction Model Driven By Characteristics Of Energy Economic System

Energy is the foundation for the stable operation and long-term development of the national economy,and the transformation of the energy economic system is crucial for achieving the goal of carbon peak and carbon neutrality.In the process of China’s economic development transitioning from high-speed growth to high-quality development,the transformation of the energy consumption structure and the problem of carbon emissions from fossil fuels in the energy economic system have become increasingly prominent.Around the issue of transformation of energy consumption structure in the energy economic system,quantifying the degree of competition and cooperation between different types of energy consumption and predicting the development trend of energy consumption structure can help analyze the change of energy consumption structure and the trend of energy consumption structure transformation;around the issue of carbon emission of fossil energy in the energy economic system,considering the non-linear and uncertain relationship between carbon emission and economic growth,the In order to provide a basis for energy planning and environmental policy formulation,we also forecast the trend of carbon emissions from fossil energy consumption in China.In order to better analyze the trend of energy consumption structure transformation and accurately forecast the trend of energy consumption and fossil energy carbon emission,the related work is as follows:To address the inherent complexity of the energy consumption system structure,this research proposes a nonlinear grey Lotka-Volterra model to evaluate the long-term competition and cooperation on the national energy consumption system and its development trend.The GLVM model is used to analyze the consumption structures of different types of energy in China,the United States and Germany,and to quantitatively analyze the intrinsic relationship between the energy consumption structures of the three representative countries.This model provides a method for researchers to study the structure of energy systems,and for decision-makers to quantitatively analyze the competition and cooperation between different energy sources to better guide decision-decisions.To reflect the interaction between carbon emissions from fossil energy consumption and economic growth in China,an equal-dimensional complementary optimized fractional order cumulative multivariate grey model EFMGM(1,2)is constructed to predict carbon emissions from fossil fuel consumption in China.The model is based on the IPCC accounting method for calculating carbon emissions from fossil fuel consumption in China,and the different characteristics of carbon emissions and economic growth in different periods.The time series are divided and modeled using multivariate grey model.The EFMGM(1,2)is constructed considering the new information priority principle,reducing the fitting error and prediction errors of the model,and optimizing fractional order and background value.The performance of the model is compared with other grey models to validate its effectiveness.The model can be used as an effective method to predict the development trend of carbon emissions from fossil fuel consumption in China,and combined with the prediction results,relevant countermeasures and suggestions are proposed for controlling carbon emissions.