Research On The Dynamic Game Of Renewable Energy Electricity Market Under Uncertain Conditions

Although coal and other high-emission energy have always been in the dominant position in Chinese energy consumption structure,the clean energy consumption represented by the consumption of renewable energy electricity continues to increase.The goal of carbon peaking and carbon neutrality has promoted the transformation and upgrading of China’s energy structure.In order to ensure the high-quality and sustainable development of the energy market and social economy,China urgently needs to focus on the dynamic development of the renewable energy electricity market.Therefore,it is of theoretical value and practical significance to study the dynamic evolution and game of renewable energy power market under complex uncertain conditions.Under the background of the low-carbon economy development,this paper systematically reviews the complex system planning theory,evolutionary game theory,uncertain decision theory and low-carbon economy theory,on the basis of summarizing relevant domestic and foreign researches,studies the key scientific topics,such as the dynamic evolution of renewable energy electricity demand,the dynamic game involving the supply side,the dynamic evolution rule of supply and demand side as well as the specification of the dynamic game framework of supply and demand side under uncertain conditions.This paper mainly obtains the following innovative outcomes:(1)This paper builds a LEAP-REE model that is consistent with the characteristics of Chinese renewable energy market.Based on the spatio-temporal evolution characteristics and the key influential indicators of the demand side identified by spatial effect analysis,the dynamic evolution prediction of renewable energy electricity demand in 2022-2035 is conducted by scenario,industry and renewable energy variety.As shown by results,the spatiotemporal dynamic evolution of renewable energy electricity demand presents different spatial spillover characteristics: under the geographical proximity weight matrix,it shows an inverted “U” shaped feature;under the geographical economic comprehensive weight matrix,it approximats the “W” shaped evolution feature.In terms of sub sectors,heavy industry and light industry are the main sectors of electricity demand for renewable energy.In terms of scenarios,the CAS-IV scenario is the most desirable of the four clean alternative scenarios,with a stepwise increase in renewable electricity demand between2025 and 2030.In addition,the uncertainty of electricity demand from renewable sources increases over time.(2)Based on the EGT model,from the perspective of carbon trading,considering the uncertainty of the decision-making probability of participating entities,this paper constructs a tripartite dynamic game framework composed of renewable energy generators,thermal electricity generators and government-led carbon trading platform.According to the results,in the cooperative mode of(1,1,1),the three participants attend in an orderly manner under the framework of the dynamic game,form a cooperative partnership in the dynamic game,and obtain group benefits.Carbon tax,incentives and the price change of carbon emission quota are uncertain factors,which can affect the decision-making behavior of participants.Under the(1,1,1)model,the selling price of renewable energy power generations selling their carbon emission quotas to carbon trading platforms increases to over 48.6 yuan/t,which can promote the cooperation willingness of renewable energy power generations and exhibits a “semi shuttle” dynamic evolution feature.Under the(0,1,1)mode,zero excess carbon emission incentives and carbon taxes can reduce the emissions and production willingness of thermal power generation companies.However,until the expiration of evolution,the share of thermal power generation will continue increasing at a high probability,and thermal power generation still will be the main body of social power generation.(3)This paper constructs a quantile dynamic model that allowed the existence of nonlinearity,based on the price response,to discover the dynamic game mechanism between supply and demand in the renewable energy electricity market under uncertain conditions.As shown by results,the renewable energy electricity market exhibits a dynamic evolution pattern of “supplydemand dependence and game coexistence,with different paths of wind and solar impact”.The supply-side evolution model of the renewable energy electricity market has a dynamic superiority Effect,and the change of the demand side’s decision can exert a dynamic effect on the price fluctuation by affecting the supply-side behavior.(4)This paper constructs a “G-G-S-C” four-party dynamic game framework involving the supply and demand of the renewable energy electricity market,considering uncertainty conditions such as the probability of decision-making,the instability of output and demand,and the possibility of multiple development scenarios,designs the incentive mechanism for electricity generators and the demand compensation mechanism for electricity users.As shown by results,in a fully marketized environment,electricity users prefer thermal electricity with lower cost,and electricity generators tend to choose noncompliant carbon emission strategy and expand the share of thermal electricity generation.In addition,the differentiated incentive mechanism is valuable,and the positive incentive mechanism for the emission compliance decision is more effective.Finally,the demand compensation mechanism guids the decision-making of generators through demand preferences,internalizes the negative externalities with a lower cost than the incentive mechanisms,is the most effective normative mechanism by promoting the evolution of green electricity preference of power users and targeting to promote the emission reduction input of power generators.Based on the above conclusions,in order to achieve better development of renewable energy electricity market under uncertain conditions,this paper puts forward a series of policy recommendations.