Research On Distributed Collaborative Operation Optimization Of Coupled Transportation-power System Considering Carbon Emission And Elastic Traffic Demand

With the global energy crisis and environmental pollution becoming more and more severe,countries around the world are striving for green,low-carbon,highquality development.As one of the main sources of fossil energy consumption and carbon emissions,the transportation system has become a future development direction under the current trend of global energy transformation.As an important driving force for this transformation,electric vehicles are gradually increasing in scale,making the coupling relationship between the urban distribution network and the transportation network increasingly close.In this case,whether the powertransportation coupling network can operate safely and economically becomes particularly important,and only economic optimization of a single network can no longer meet the needs of future social development.Based on this background,this thesis starts from the network coupling relationship and conducts further research on the collaborative optimization of the power-transportation coupling network.The main contents are as follows:Firstly,a traffic flow allocation model based on the static user balance criterion is established to obtain the operating state of the traffic system,and an optimal power flow model of the distribution network based on second-order cone relaxation is established to obtain the operating state of the power system.On this basis,considering that the information between the transportation department and the power grid department is not completely interoperable,the solution principle of the distributed algorithm used in this thesis is introduced to provide a foundation for subsequent research.Secondly,further considering the state of charge and mileage limit of electric vehicles,the carbon emission cost of the coupling system and the user’s flexible travel demand are comprehensively studied,and a traffic flow distribution model considering the queuing time and charging cost of electric vehicle charging stations is established.And the effective path generation algorithm is designed specifically.A numerical example is used to verify that the proposed model can effectively realize the economy and low carbon of the coupled system,and the influence of the elastic response coefficient and electric vehicle penetration rate on the coordinated operation of the power-transportation network is discussed.Finally,on the basis of the above research,the existing static power-traffic network collaborative optimization model is extended to multi-time crosssectional scales,and a multi-period coupled network distributed collaborative operation optimization model is constructed,considering the variable travel demand time and regular load demand response and the cost of carbon emissions.On the other hand,considering the scenario of gradually increasing the proportion of renewable energy in the future distribution network,the introduction of distributed photovoltaics to replace the traditional thermal power units in the distribution network is considered in the multi-period collaborative operation optimization model.It is verified by calculation examples that the proposed model can fully tap the potential of orderly charging of electric vehicles to realize peakshaving and valley-filling,maximize the economic and low-carbon benefits of the coupling system,and can effectively improve the consumption level of renewable energy.At the same time,it adapts to the optimization scenario of the future highproportion renewable energy power system.