Optimization And Risk Analysis Of Energy Transition Pathways Based On The CPSSE Framework

As climate change and extreme weather issues become increasingly severe,the clean and low-carbon transition of energy systems has become a consensus among countries.To support the formulation of energy transition strategies and plans,the optimization of energy transition goals and pathways,as well as the analysis of their uncertainties,has become one of the hottest research areas and has yielded significant results.However,energy transition is a typical crossdisciplinary and complex issue,involving not only natural sciences such as energy and climate but also social sciences such as energy economics and policy mechanisms.It requires comprehensive consideration of multidimensional coordination,including between physical systems and social systems,energy systems and environmental systems,power systems and non-power energy systems,optimization of transition goals and pathways,system planning and operation,and the interests of different stakeholders.Furthermore,due to insufficient information and understanding,energy transition research must address many uncertainty factors from physical,economic,and policy fields.Such a complex problem poses serious challenges to research paradigms.In recent years,Chinese scholars have pioneered the framework of Cyber-Physical-Social System in Energy(CPSSE),which comprehensively considers multidimensional elements such as information,energy,physics,and society.They have proposed using sandbox simulations to quantitatively study such complex problems.This paradigm includes multidomain simulation modeling,hybrid simulation,knowledge extraction(simulation trajectory),decision optimization,and uncertainty analysis.It has been widely applied to research on electricity markets,power system adequacy,carbon markets,electric vehicles,and other issues.This article is based on the CPSSE framework and focuses on researching how to achieve the low-carbon transition of energy systems.With the optimization of energy transition goals and pathways as the core,a simulation model for energy system transition is developed,quantifiable evaluation indicators for energy transition are constructed,and energy transition schemes are optimized based on the goal-pathway decoupling method.On this basis,uncertain factors such as scenario parameters and extreme weather disturbances are considered,and the research explores how to address the risks caused by uncertainty factors in energy transition,with the objective of minimizing total cost of risk.The main research content is as follows:(1)The method for quantitatively evaluating the goals and pathways of energy system transition was proposed.The paper developed an energy system transition simulation model based on the CPSSE framework,which includes elements from the physical,environmental,and economic domains.Subsequently,the paper put forward a simulation and quantitative evaluation method for the long-term transition of the energy system,including qualitative energy transition strategies or energy development plans into scenario parameters and energy transition pathways that can be quantitatively simulated.This involves extracting physical,environmental,and economic indicators such as energy structure,electricity structure,installed capacity structure,energy efficiency,carbon emissions,carbon intensity,and economic costs of energy transition from the simulation trajectories.The simulation and quantitative evaluation of energy transition were then conducted using national and regional levels as research cases.(2)Based on the iterative optimization method between the evolutionary pathways and planning goals,the coordinated optimization of energy transition goals and pathways is achieved.Leveraging the quantitative assessment capability provided by the established energy system transition simulation model in this paper,the optimization objective function is defined as the minimization of the sum of construction costs,operation and maintenance costs,grid system costs,fuel costs,scarcity value of fossil fuels,and social cost of carbon.Using a clustering approach,an infinite variety of transition goals and pathways are represented by binary tuples[Rf,n]where Rf represents the value of the feature of transition goal at the final year,and the time-series trajectory between the start and final years is described in power function form(n represents the power exponent of the function).Through a two-layer search of goal features and pathway parameters,the optimal transition goals and pathways are obtained based on the established energy transition model and quantitative evaluation method.Taking the national energy transition as a case study,the optimal goals and pathways for the transition of China’s primary energy structure before 2050 were analyzed under both with and without carbon emission constraints.The study also analyzed the impact of changes in parameters such as scarcity value of fossil fuels,grid system costs,and social cost of carbon on the optimization results.(3)Proposed a risk optimization method for addressing scenario uncertainty in energy transition pathways.Firstly,uncertain factors in the fields of technology,economy,policy,and environment involved in energy transition were reviewed.Secondly,key uncertain scenario parameters were selected,and an uncertainty scenario set was constructed by setting the values and probabilities of relevant scenario parameters.Then,based on risk thinking,the expected economic cost of the energy transition pathway under the given scenario set was used as the objective function to obtain a risk-optimal pathway that takes into account different parameter scenarios.Finally,the impact of scenario probability parameters on the optimization results was analyzed.(4)Proposed an optimization method for the development pathway of quasiretired coal-fired power plants,taking into account the risk of extreme weather disturbances during the low-carbon transition of the power sector.Firstly,the analysis focused on the electricity security risks during extreme weather disturbances,as coal-fired power gradually phases out and the proportion of renewable energy generation increases.This included an assessment of the operational costs of quasi-retired coal-fired power plants(i.e.,coal-fired power plants that have reached the end of their service life but are kept in a standby state without being dismantled)when serving as emergency capacity and the role for ensuring the power supply.The objective function was set as the sum of the operational costs of quasi-retired coal-fired power plants,the coal-fired power generation costs after extreme weather disturbances,and the remaining blackout risk,with the aim of minimizing this sum.Following a clustering approach,the years during which the installed capacity of coal-fired power plants is maintained in a quasi-retired state are taken as characteristic parameters for the development pathway of quasi-retired coal-fired power plants.Optimization of the quasiretired coal-fired power plant development pathway was achieved by searching for the optimal values of this parameter,aiming to minimize the risk cost and maximize the role of quasi-retired coal-fired power plants in ensuring power supply during extreme weather disturbances.Finally,the analysis focused on the impact of parameters such as the intensity,duration,and probability of weather disturbances on the optimization results.