Study On Electric Vehicles Group Scheduling Strategy Considering Wind Power Credit And Load Margin

The transportation sector consumes about half of China's oil resources and produces a large amount of greenhouse gases.In response to the increasingly severe resource and environmental problems,governments around the world are actively promoting electric vehicles.The energy of electric vehicles mainly comes from the power grid.Its large-scale development is inseparable from the support of the power system.The disordered charging behavior has the characteristics of strong randomness and high simultaneous rate,which will increase the load peak and valley difference of the distribution network.Challenges such as insufficient user satisfaction.In response to the above problems,this paper explores the problem of integrated optimal scheduling of electric vehicles considering new energy access.The main research contents include:First,the optimal dispatching and development status of charging and swapping power stations considering wind power access are studied,and then the optimal dispatching model of electric vehicles that incorporates credibility theory and user satisfaction of electric vehicles is analyzed.The method of uncertain factors provides theoretical support for the study of electric vehicle group scheduling strategy considering wind power access and load margin domain.Secondly,for the uncertain problems such as electric vehicle load,define load margin domain indicators,detect daily load changes,and load peaks and valleys for loads with large fluctuations to make them smooth and stable.On this basis,taking the obtained load margin domain as a constraint and considering the grid-connected wind farm integration with time-of-use electricity price,a "wind-network-station-vehicle" system optimization dispatch model was established to achieve the maximum economic benefit of the system At the same time,it plays an important role in reducing the wind curtailment rate of wind power.Integrate the credibility theory and fuzzy chance constraints,introduce credibility measure indexes,clarify the equivalent conditions of fuzzy chance constraints,and use particle swarm optimization algorithm with shrinkage factor to optimize the scheduling model and verify it by an example the rationality of the model and its strategy.Finally,in order to solve the large-scale real-time optimization scheduling problem of electric vehicles,on the basis of establishing the state matrix of electric vehicles,a new method of dividing electric vehicles into several state clusters is proposed.The power satisfaction and time satisfaction are defined,the weighted sum is the user satisfaction,and the real-time optimization scheduling model of the "wind-network-station-vehicle" system based on electric vehicle clustering is constructed with the goal of maximum economic benefits and satisfaction as the goal.Aiming at the problems of grid-connected wind farm output and electric vehicle load uncertainty,the fusion credibility theory and fuzzy chance constraint theory are also used.Then the particle swarm optimization algorithm with shrinkage factor considering the external penalty function method is used to optimize the scheduling model,and the superiority of the model and its scheduling strategy is verified by an example.