Research On The Green Low-carbon Emission Reduction System Driven By The Collaboration And Interaction Of The Multi-agents

Climate change is one of the major challenges facing the world,which endangers human life,livelihood and development.As the main factor affecting climate change,how to effectively reduce carbon emissions to mitigate climate change has become a hot issue in the current global research.According to the nonlinear dynamic system theory,taking the green low-carbon behavior,carbon price,carbon emission,energy price,clean power and thermal power as the main variables and energy intensity,economic growth,climate change,industrial structure and energy production as the object variables,this dissertation builds a dynamic evolutionary model of the green lowcarbon emission reduction(GLCER)system based on China's national conditions,and a practical GLCER system is obtained by the means of the statistical data and the improved BP neural network method based on the theoretical analysis.The policy suggestions of the GLCER in line with China's actual situation are given,which provides theoretical and empirical reference for the policy makers to formulate scientific and reasonable carbon emission reduction policy.According to the causal conducting relationships among China's green low-carbon behavior,carbon price and carbon emissions,a three-dimensional GLCER system driven by multi-agent cooperation and interaction is constructed.Through the impact of the regulatory policy on system parameters,the evolutionary state of the system under different regulatory policies is explored,then the dynamic evolutionary path of the system under different regulatory policies and different regulatory efforts is analyzed.The results show that the steady-state level of the carbon emissions under the single control policy is lower than that under the combined control policy,and the combined control policy is better than the single control policy in improving the carbon price level and making it reach the steady-state time,but the steady-state levels of the carbon emissions show the same change trend under different control efforts of the single control policy.Meanwhile,the guiding role of the carbon emission reduction through the carbon trading market behavior has certain limitations in the immature stage of carbon trading market,that is,it can't fully tap the potential of the green low-carbon development,while the green low-carbon action through the government intervention behavior and social behavior has a more significant effect.On the basis of the GLCER system,the carbon quota system and carbon reduction subsidy policy are incorporated into the system as selection constraints,the selectiveconstrained GLCER system is established,and the evolutionary path of the system and its internalizing level is studied.The results show that the carbon quota system and carbon reduction subsidy policy can improve the level of the green low-carbon behavior and carbon price,and then reduce carbon emissions by restricting carbon emissions and encouraging low-carbon research and development.In addition,the promotion effect of the carbon quota on carbon price is stronger than that of carbon reduction subsidy on the carbon price,while the emission reduction mechanism of the carbon price under carbon quota and carbon emission reduction subsidy policy has not been fully played.Based on the three-dimensional GLCER system,the energy price is introduced to build a four-dimensional GLCER system with the energy price as the main variable,and the market-driven carbon emission reduction behavior is explored.The results show that both the energy market and carbon trading market can play the guiding role of the market economic behavior on carbon emission reduction under the premise of the effective energy price and carbon price mechanism,but the internalizing level of the green low-carbon behavior gradually declines with the increase of the market regulatory efforts.Meanwhile,there is asymmetry and reverse mechanism between the energy price and carbon price.The evolutionary system of the clean power is based on the complex nonlinear relationship between the green low-carbon behavior,carbon price,carbon emissions and clean power.The incorporation of the clean power into GLCER system makes the whole system present more complex evolutionary behavior.The results show that the development of the clean power is conducive to the improvement of the green lowcarbon development level,and improving the impact of the clean power on carbon price is conducive to the improvement of carbon price level in the early stage of the clean power.Meanwhile,the immature stage of the clean power has poor effect on carbon emission reduction,but the mature stage has good effect on carbon emission reduction.A GLCER system with the thermal power is built by incorporating the thermal power into the system based on the GLCER system,and the evolutionary state and influence mechanism of the thermal power on carbon emissions are explored.The research shows that carbon emissions can be effectively reduced through the control of the thermal power,but the carbon quota system enhances the driving force of the thermal power on carbon price,and increases the carbon price to reduce carbon emissions.While,the optimization level of the thermal power is to improve the green low-carbon development level to reduce carbon emissions,and the thermal power has a certain lag to reduce carbon emissions.At the same time,with the improvement of the thermal power carbon quota system and its optimization level,the total amount of carbon emission reduction is also larger.The innovation of this dissertation is mainly manifested in the application of complex system analysis and decision-making theory,system scientific analysis theory,neural network method and dynamic large-scale system modeling method in the research of GLCER dynamic system with Chinese characteristics,combined with the complex relationship of mutual promotion and restriction among market elements,resource elements,behavior elements and innovation elements,then a causal transmission relationship network between various entities has been constructed,a scientific and reasonable quantitative analysis model is established,and the research methods of combining quantitative analysis and qualitative research,theoretical analysis and empirical analysis are determined.Meanwhile,we deduce the evolutionary formula of the internalizing level among the multi-agents changing with the time from the GLCER system,analyze the evolutionary characteristics of the GLCER system in different situations,and present these evolutionary characteristics through the intuitive and visual graphics.Finally,some research results that are in line with China's actual development status are obtained by the qualitative and quantitative comparative analysis,and policy suggestions are provided for scientifically promoting the 2030 carbon emission peak target and the 2060 carbon neutral vision.