| Climate change has become the core challenge for human sustainable development.How to control the greenhouse gas emissions from human industrial activities has become a key issue that needs to be solved urgently.The carbon market,as a carbon emission reduction mechanism based on aggregate control and market transactions,has been widely used worldwide.The emergence of such a policy-based environmental market mechanism poses huge challenges to both carbon market managers and carbon market participants.Diversified trading behavior is one of the reasons for the complex and volatile state of the carbon market.The existing carbon trading behavior modeling methods are mainly divided into experimental economics methods and methods based on multiagents.The former is very limited in time,space and experimental participant selection,while the latter is difficult to simulate the participation due to the limitations of the agent model Therefore,more comprehensive methods are needed to analyze the trading behavior of carbon market participants.In addition,the carbon price mechanism is also a key content of the carbon market.A reasonable and effective target carbon price should be able to reflect the environmental damage caused by the greenhouse gas emissions of companies that control emissions from an economic level.This thesis is based on a hybrid simulation method that combines experimental economics and computer agent models proposed by our research team.Starting from the analysis of micro carbon trading behavior of power generation enterprises and the assessment of macro carbon prices in the carbon market,the main work further carried out is as follows.(1)Based on hybrid simulation application software for power system carbon trading,with Shanghai pilot carbon market as the background,through the carbon market environment parameter settings,emission control enterprise parameter settings,institutional investor parameter settings,and trade participant parameter settings,a hybrid dynamic carbon market simulation experiment involving electric power companies was constructed.The transaction behavior data of real participants in the simulation experiment was obtained to provide data support for subsequent behavior analysis.(2)Aiming at the analysis of real participants' trading behavior,a carbon trading behavior analysis method based on causal inference is proposed.Based on the data of real participants' trading behavior collected by hybrid simulation,a causal graph of carbon trading behavior decision-making was constructed.The front door of causal analysis is constructed by objective driving factors,subjective driving factors and final behavioral variables.The example analysis shows that the front door analysis path can effectively avoid the influence of confounding factors and identify the trading preferences of real participants.(3)Aiming at the assessment of target carbon prices in the construction of the carbon market,based on the integrated assessment model(IAM),the social cost of carbon(SCC)indicator is introduced.Through the socio-economic,climate change,loss assessment and result discounting modules,the environmentally difficult losses are converted into more intuitive economic losses.Finally,a trial calculation of SCC between 2020 and 2055 in China and the world level was conducted.The analysis results show that the SCC under different development models can provide a reference for carbon market target carbon price assessment. |
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