Optimized Control Of Vehicle To Grid And Distribution Transformer Extension Planning Considering Demand Response

Active and flexible demand-side response technology can further expand the breadth and depth of electricity substitution,and is an effective plan to optimize energy use,reduce energy use and reduce carbon emissions,which can effectively help China to achieve carbon peak and carbon neutral goals faster.With the characteristics of both elastic load and energy storage equipment,electric vehicles are a special and high-quality demand response resource with broad investment market,good response performance and great adjustable margin.In order to further tap the demand response potential of electric vehicles,this paper conducts research from the operational and planning levels.The main work contents are as follows:In this paper,the general modeling method of EV charging load and the principle of demand response are briefly described,and the mechanism of EV participating in demand response is introduced in detail,including the basic principles of coordinated charging and V2 G response modes.In coordinated charging control method,a strategy based on real-time residual controllable capacity is adopted,while in terms of V2 G optimization scheduling,a grid-side V2 G optimization model with minimum load fluctuation variance as the objective is established.Secondly,in view of the inadaptability of the existing three-phase unbalance evaluation index in the case of current reverse,this paper summarizes the necessary conditions for considering current reverse from the theoretical level,and further deduces the three-phase unbalance index,residual unbalance current,which is suitable for the case of current reverse.Then a dual objective optimization model is established to minimize the residual unbalanced current and load fluctuation variance at the low voltage side of the distribution transformer,and the corresponding business model is described to ensure the benefits of users.The simulation results show that the proposed optimization model can reduce the peak and valley load difference,and can optimize the three-phase power flow more effectively and reduce the distribution network imbalance in the V2 G scenario with reverse current。Finally,aiming at the insufficient distribution capacity and investment economy caused by cluster EV,to provide a good and strong support for the participation of electric vehicles in demand response,this paper performs cluster analysis on the typical basic load curve in residential areas and resident-commercial scenarios,and establish a detailed model of EV charging load.Considering the development trend of load,establish a natural growth model of the comprehensive load of the distribution transformer.Further,based on the complementary advantages of the coordinated charging and the newly-built distribution transformer,an extended planning method for distribution transformers that takes into account coordinated charging is proposed.Aiming to minimize the life cycle cost of the investment scheme,a combination decision optimization model under long time scale is established to determine the best combination form of coordinated charging and newly-built distribution transformer.The effectiveness and economy of the proposed method is verified in simulation examples.