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Wind-fire-storage Joint Multi-time Scale Optimal Scheduling Considering Flexible Resource

Posted on:2024-07-05Degree:MasterType:Thesis
Country:ChinaCandidate:Q CaiFull Text:PDF
GTID:2532307130461074Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
The carbon emissions of the power system account for 40% of the entire industry,and increasing the proportion of renewable energy in the power system is a critical way to promote the "dual carbon" goal.Wind power is widely concerned because of its low marginal cost,zero carbon emissions,and other characteristics;However,its inherent randomness and volatility lead to large-scale grid connection,leading to wind abandonment and exacerbating the peak shaving pressure of the power system.At the same time,an insufficient prediction level will lead to a deviation between the day ahead dispatching plan and the actual situation,which puts forward higher requirements for the flexibility of power system dispatching.Currently,wind power in China often operates in collaboration with thermal power,but it is the primary source of carbon dioxide emissions from the power system.Integrating carbon capture technology into conventional thermal power can reduce carbon emissions and provide more flexible regulation resources.In addition,demand response can effectively reduce system carbon emissions by its zero carbon emissions and flexible and controllable characteristics.Therefore,this paper takes the wind fire storage power system as the carrier and considers the coordinated operation of wind power and carbon capture power plants,supplemented by demand response resources,to achieve the low-carbon economic dispatching goal of the power system.This article first introduces the operating principle and structure of carbon capture power plants,analyzes the energy consumption characteristics of their flexible operating modes,and based on this,clarifies the scheduling advantages of a joint operation with wind power;Analyzes the low-carbon principle of load side demand response,and further analyze the complementary advantages of both sides of the source and load;Given the deviation between the day ahead scheduling plan and the actual situation in the day,a multi-time scale solution is proposed.A multi time scale scheduling method is proposed considering the flexible operation and demand response of carbon capture power plants.This method applies the comprehensive,flexible operation mode of carbon capture power plant and the flexible adjustment resources of demand response in the early stage to build a scheduling model with the goal of economic optimization;In the intra-day stage,considering the source load prediction error,model predictive control is used to revise the day ahead scheduling plan in real-time.The calculation example shows that the proposed scheduling method can increase the system’s wind power consumption by614.4MWh,reduce carbon emissions by 2500 tons,and reduce total costs by 20.1%by applying flexible resources on both sides the source and load rather than considering flexible resource regulation.Further considering the source load coordination problem,the equivalent load method is adopted to deal with the wind power output,and a multi time scale scheduling method considering the source load coordination optimization is proposed based on the multi time scale scheduling method considering the flexible operation and demand response of carbon capture power plants.This method further improved the system’s wind power consumption by 308 MWh,reduced carbon emissions by 317 tons,and reduced total costs by 7.3%.The research results show that the proposed scheduling model can solve the problem of deviation between the day ahead scheduling plan and the actual situation in the day while giving the low-carbon economy scheduling plan of the system.Provide a reference for the low-carbon development of the power system.
Keywords/Search Tags:Consumption of renewable energy, Carbon capture power plant, Demand response, Multiple time scales, Optimize scheduling, Model predictive control
PDF Full Text Request
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