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Capacity Configuration Of Independent Wind-photovoltaic-hydrogen-diesel Coupled Energy Supply System For Electrified Railway Of No-human Zone

Posted on:2023-07-22Degree:MasterType:Thesis
Country:ChinaCandidate:J H HuFull Text:PDF
GTID:2532307145965149Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
In response to global warming,China put forward the “Carbon peak and carbon neutralization” development goals.Under the background of “Double carbon” as a major energy consumer,the relevant departments have formulated a strategy for the integrated development of energy and transportation.As a member of the transportation in western China,the unmanned area electrified railway has developed rapidly in recent years.Traction power accounts for the highest proportion of electric iron power consumption,which is the key area of carbon emission reduction.The electric railway traction load has strong impact,random instability and high reliability requirements for power supply system,which increases the research difficulty of clean energy traction power supply theory.The structure of power grid in unmanned area is weak,and it is easy to be destroyed in extreme weather or wartime.It is of great significance to study the independent power generation system separated from the main grid.Based on the existing research,this paper preliminarily explores the relevant research contents,including:Firstly,considering the traction load characteristics of unmanned electrified railway,an independent wind-photovoltaic-hydrogen-diesel coupled energy supply system for unmanned electrified railway traction is proposed.The system structure and operation mode are designed,and the mathematical models of wind turbines,photovoltaic arrays,alkaline electrolyzers,high-voltage hydrogen storage tanks,proton exchange membrane fuel cells and diesel generators in the system are established,which provide a theoretical basis for the reliability evaluation and capacity optimization of the following system.Secondly,the state probability model of wind turbine,photovoltaic array and other main components is introduced,and the system reliability evaluation index redundancy capacity ratio PRC is given.Considering the power interaction of the system under different working conditions,combined with the system operation mode,the system operation control strategy under multi-operation mode is proposed.Based on the non-sequential Monte Carlo method,the proposed independent wind-photo-hydrogen-diesel coupled energy supply system is evaluated to verify the overall reliability of the proposed independent wind-photo-hydrogen-diesel coupled energy supply system.Finally,the capacity optimization allocation method of independent wind–photovoltaic–hydrogen-diesel coupled energy supply system considering wind-photovoltaic power consumption,system power supply reliability and economy is proposed,that is,the system capacity optimization allocation model is established with the minimum total system cost,load power shortage rate and wind curtailment rate as the objective function,and the system power balance,device rated capacity and hydrogen storage tank operation state as the constraint conditions.Combined with the climate and traction load data of a certain unmanned area in Northwest China within 720 h in a month,the NSGA-II algorithm is used to optimize the capacity configuration of the proposed independent wind-photovoltaic-hydrogen-diesel coupling energy supply system,and the capacity optimization calculation of the system after removing the diesel generator is carried out again under the same conditions.The capacity optimization results of the two systems are compared,and the output tracking of the two systems for the same traction load is compared to verify the effectiveness and applicability of the proposed system in dealing with the traction power supply of the electrified railway in the unmanned area.
Keywords/Search Tags:Electrified railway of no-human zone, Electric traction power supply, Independent wind-photovoltaic-hydrogen-diesel coupled system, Reliability assessment, Capacity optimization configuration
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