Research On The Optimization Of Decarbonization Pathways For Power Sector And The Measurement Of Transition Costs Based On Scenario Simulation

The carbon neutrality goal has given a new and tough commission to China’s energy transition,with clean and low carbon energy becoming the key role of China’s medium to long-term energy development.Under the constraints of the carbon neutrality goal,it has become a consensus that the power sector needs to carry out a deeper decarbonization transition,due to the highest technical feasibility and easier to decarbonize than other industrial sectors.China’s transition towards a new power system based on renewable energy sources is progressing rapidly,China also announced a target of achieving 50%of non-fossil energy generation by 2030.The plan also includes a goal of reaching peak CO2 emissions by 2030 and achieving carbon neutrality by 2060.It is foreseeable that China will promote the large-scale development of renewable energy on both the supply and demand sides,and gradually change the coal-based energy structure.In this research,it concentrates on the optimization of decarbonization pathways for power sector and the measurement of transition costs based on scenario simulation.Firstly,this paper constructed an optimization model for power resource portfolio planning which consider technology learning and carbon pricing,then simulated eight different decarbonization pathways for China’s power sector.On this basis,this paper provided decision-making on the hourly dispatch of various types of power resources under operating simulation based on the screening curve model,on the coal power unit CCS retrofitting based on the sourcesink matching model,and on the stranded coal power assets based on the carbon locking curves model.The purpose of which was to measure the investment costs of power resource expansion,total system costs,CCS retrofitting costs of coal power unit and stranded costs of coal power unit under various power planning scenarios.It is expected that by calculating some of the economic account of carbon neutrality in the power sector,which would provide academic support and decision-making guidance for relevant departments and scholars to design a scientific and reasonable decarbonization pathway map for China’s power sector.The main research contents are as follows:(1)Constructed a power resource portfolio planning optimization model with carbon price and learning rate of key power technologies for the design of power decarbonization transition pathways and multi-scenario simulations.Firstly,this article forecasted China’s medium-to long-term power demand.Secondly.it analyzed the potential development of power supply resources and the carbon emissions budget of the power sector.Then,the LCOE(Levelized Cost of Energy)considering carbon price and learning rate of key power technologies is introduced into the power resource portfolio planning model and eight different scenarios are simulated for the decarbonization pathway of China’s power sector with the minimum net present value during the planning period.Finally,the key indicators of power transition effectiveness are obtained,it conducted sensitivity analysis of learning rate and carbon price on annual power generation costs.(2)Measured the total system cost under different power decarbonization pathways and analyzed the value of flexible dispatch generated by incorporating specific technologies into the power system,based on of various power resources under the screening curve model.Firstly,based on historical data,it constructed the annual 8760h load curve and new energy output profile with random characteristics.Secondly,considering the operating constraints and hourly dispatch rules of the power system,the screening curve and load duration curve are used to simulate the hourly dispatch of various power resource portfolio,and the results are presented for 2035 and 2060 under the B-C21200 scenario.Then,based on the simulation results of the hourly dispatch,it calculated total system costs,abandonment rate,and CO2 emissions of power generation.Finally,we added a certain capacity of coal power with CCS,energy storage,BECCS,etc.based on the original power mix,and calculated the total system costs to define the flexible value formed by specific technology.(3)Constructed a source-sink matching model considering CO2 avoidance cost.which was used for CO2 transport pipeline network layout optimization,for decision-making and cost measurement of coal power CCS retrofitting under different power planning scenarios.Firstly,based on the "bottom-up" perspective of coal power database,we sorted out the coal power information according to the commissioning status of planned units,after certain conditions are determined and screened,we obtained the candidate coal power plants as CO2 emission sources with higher potential for CCS retrofitting.Secondly.in the"top-down" power planning scenarios,we compiled the coal power CCS retrofitting capacity targets to meet CO2 emission reduction by 2060,also obtained the CO2 storage point information in China.Thirdly,we calculated CO2 avoidance cost of different coal power units,of which introduced into the source-sink matching model.Next,considering the benefits of CO2-EOR,we obtained the feasible source-sink layout results with the goal of minimizing cost.Then,according to the CO2 avoidance cost,the sequence of coal power CCS retrofitting was determined.Finally,the total cost of coal power CCS retrofitting is calculated according to CO2 emission reduction targets and pipeline layout under different power planning scenarios.(4)Constructed the coal power database based on the commissioning status of planned units,which is used to make a comprehensive evaluation.And analyzed the capacity and cost of stranded coal power assets based on carbon lock-in curves model,which compared the differences between coal power database and coal capacity targets under power planning scenarios.Firstly,we collected information on coal-fired power units and set up different development scenarios for planned coal power units.We conducted comprehensive evaluations of these units according to the available information and obtained a comprehensive score for each coal power unit.Then,we compared the capacity under all planned coal power units build scenario with the coal power capacity target under the power planning scenarios.Using the carbon lock-in curves model and an"up-down interaction" mode,we constructed a decommissioning algorithm to make decisions on which coal power units to early withdrawal from market.Finally,we used the cash flow method to calculate the stranded costs of each coal power unit.