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Research On The Regulation Strategy Of Electric Vehicle Aggregators Participating In Power Grid Ancillary Services

Posted on:2020-09-27Degree:MasterType:Thesis
Country:ChinaCandidate:Y J ZhaoFull Text:PDF
GTID:2392330578966639Subject:Engineering
Abstract/Summary:PDF Full Text Request
With the increasingly serious problems of environmental pollution and energy shortage,the development of green energy has received extensive attention.In recent years,China's renewable energy installed capacity has increased rapidly,and energy structure adjustment has accelerated significantly,but it has also exposed some problems.New energy generation such as wind power and photovoltaic power generation has strong intermittent and uncertainties,and lacks the mechanical inertia exhibited by traditional generator sets to the power grid.After a large number of power grids are connected to the power grid,it brings great challenges to the stable operation of the system.Due to the shortage of peaking capacity of the system,a large number of abandoned winds and abandoned light have appeared,and this problem has become the main constraint factor for the power system to accept new energy.In this context,the traditional grid-assisted service means can not fully meet the needs of system operation.Therefore,in order to increase the adjustable capacity of the power grid and improve the response speed,it is necessary to introduce a new ancillary frequency regulation and peak shaving means.Recently,the maturity of electric vehicle technology and the continuous decline of battery cost have greatly increased the market share of electric vehicles,creating opportunities for electric vehicles to participate in the interactive operation of the power grid.As a kind of high-quality resources with potential for interaction with the system,electric vehicles are widely distributed in various regional power grids.How to use the driving force of power market reform to aggregate a large number of fragmented electric vehicles,build a new type of commercial operation,and participate in the power grid.The ancillary services have become a new idea to promote the construction of smart grids,and have also attracted the attention of the majority of science and technology workers.This paper studies the aggregation management of electric vehicles and the control strategy of frequency regulation and peak shaving in the ancillary power grid.The main work contents and research results are as follows:1.Combined with the energy storage characteristics of electric vehicles and the development needs of new energy power systems,the concept of Electric Vehicle Aggregator(EVA)was proposed.The basic framework of EVA is designed,and its working principle is introduced.The regulation mode and operation mechanism of EVA are studied.2.Considering the customer's travel expectations and the state of charge of the power battery,the control strategy of electric vehicles participating in frequency regulation is established.Under the control strategy,the EVA can control the real-time charging and discharging power of the charging pile according to the frequency deviation,thereby achieving the purpose of responding to the grid frequency change.A simulation scenario is established for the travel rules of different users in reality,and the simulation scenario comparison shows that the proposed strategy can not only meet the customer's travel expectations,but also stabilize the system frequency well.3.Taking the minimum mean square error of the load curve as the objective function,the power grid peaking strategy with EVA participation is formulated.Elements such as electric vehicles and photovoltaic units were added to the IEEE-33 node system,and related parameters were set.Through simulation and analysis of the example,the results show that the proposed strategy can make the electric vehicle complete the peaking task of the power system without affecting the customer's travel.
Keywords/Search Tags:Electric vehicle aggregator, ancillary service, travel demand, frequency regulation, peak shaving
PDF Full Text Request
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