本文選題：電動汽車 + 充電負荷��； 參考：《華北電力大學(北京)》2017年碩士論文

【摘要】：隨著環(huán)境污染與能源緊缺的日益加重,以清潔的電能為動力能源的電動汽車必將得到迅速發(fā)展,規(guī)模化電動汽車充電對電網的影響以及如何對其進行有序控制已經成為國內外關注的熱點,因此,本文圍繞電動汽車充電對電網的影響以及智能充電控制策略展開了研究,主要研究內容如下:(1)分析了影響電動汽車充電負荷的主要因素,以美國交通部統(tǒng)計數(shù)據(jù)為基礎研究了電動汽車行駛規(guī)律分析模型,改進了基于統(tǒng)計模型與蒙特卡洛法的無序充電負荷計算方法,并給出了計算流程,為文章后續(xù)研究提供了基礎。(2)提出了一種獨立研究充電負荷和背景負荷,再根據(jù)滲透率建立電動汽車數(shù)量與電網的對應關系,從而綜合分析電動汽車充電對電網影響的解耦分析方法。研究了不同電動汽車規(guī)模和充電功率下EV充電負荷特性,包括平均值特性、偏移特性、波動特性以及區(qū)域不平衡特性,得到了充電負荷特性隨車輛規(guī)模和充電功率變化的基本規(guī)律,再在較大滲透率的場景下,分析了規(guī)�；疎V充電對我國城市各級電網影響的基本規(guī)律,確定了主要問題發(fā)生的可能性。(3)提出了一種基于峰谷分時電價的動態(tài)排序充電控制策略,確定了該策略的優(yōu)化目標與約束條件,提出了動態(tài)排序的智能充電控制算法,分為外層排序與內層排序,將有充電需求的電動汽車“擇優(yōu)”接入并實時更新,以實現(xiàn)電動汽車的有序充電,減小充電負荷對電網帶來的不利影響。(4)以380V居民住宅小區(qū)配電網模型為基礎,對基于峰谷分時電價的動態(tài)排序的智能充電控制策略進行了仿真驗證,分別研究了采用智能充電控制策略之后電動汽車充電對配電網負荷曲線、變壓器負載率、節(jié)點電壓偏移以及網絡損耗的影響,并與電動汽車無序充電進行對比,仿真結果表明,動態(tài)排序的智能充電控制策略起到了削峰填谷、平抑負荷曲線、降低網絡損耗的作用,減小了充電負荷對配電網的影響,提高了電網運行的經濟性。
[Abstract]:With the worsening of environmental pollution and energy shortage, electric vehicles with clean electric energy as the power source will be developed rapidly.The influence of large-scale electric vehicle charging on power grid and how to control it orderly has become a hot spot at home and abroad. Therefore, this paper focuses on the influence of electric vehicle charging on power grid and intelligent charging control strategy.The main research contents are as follows: (1) the main factors affecting the charging load of electric vehicles are analyzed. Based on the statistics of the United States Department of Transportation, the driving law analysis model of electric vehicles is studied.This paper improves the calculation method of disordered charging load based on statistical model and Monte Carlo method, and gives the calculation flow, which provides the basis for further research. (2) an independent study of charging load and background load is proposed.Then the corresponding relationship between the number of electric vehicles and the power grid is established according to the permeability, and the decoupling analysis method for the influence of electric vehicle charging on the power grid is analyzed synthetically.The characteristics of EV charging load under different electric vehicle size and charging power are studied, including average value characteristic, offset characteristic, fluctuation characteristic and regional imbalance characteristic.The basic law of charge load characteristics varying with vehicle size and charging power is obtained. Under the scenario of large permeability, the basic law of the influence of large-scale EV charging on all levels of urban power grid in China is analyzed.In this paper, the possibility of the main problems is determined. (3) A dynamic charging control strategy based on peak-valley time-sharing price is proposed. The optimization objectives and constraints of the strategy are determined, and an intelligent charging control algorithm for dynamic scheduling is proposed.Divided into outer sorting and inner sorting, the electric vehicle with charging demand will be connected and updated in real time in order to realize the orderly charging of electric vehicle.Based on the distribution network model of 380V residential district, the intelligent charging control strategy based on dynamic sequencing of peak and valley time-sharing price is simulated and verified.The effects of electric vehicle charging on distribution network load curve, transformer load ratio, node voltage offset and network loss after intelligent charging control strategy are studied, and compared with the disordered charging of electric vehicle, the simulation results show that.The intelligent charging control strategy of dynamic sequencing can cut the peak and fill the valley, stabilize the load curve, reduce the network loss, reduce the influence of charge load on the distribution network, and improve the economy of the network operation.
【學位授予單位】：華北電力大學(北京)
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM73

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本文編號：1761006