本文關(guān)鍵詞：規(guī)�；瘏^(qū)域電動乘用車負荷估算研究　出處：《北京交通大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 電動出租車 出行特性 充電特征 充電負荷 分段概率模型 優(yōu)化配置 排隊論

【摘要】：隨著電動汽車技術(shù)及其充電設(shè)施的不斷成熟,電動汽車將越來越廣泛地應(yīng)用于人們的日常生活之中,在電動汽車規(guī)�；l(fā)展之后,電動汽車龐大的充電負荷將成為電網(wǎng)負荷的重要組成部分。為了保證電網(wǎng)能夠較好地滿足規(guī)模化發(fā)展的電動汽車充電需求,同時避免和減小電動汽車充電對電網(wǎng)正常運行造成不良影響,有必要對區(qū)域電動乘用車的充電負荷估算方法進行研究,以滿足電動乘用車有序充電控制和能量管理相關(guān)研究的需要。電動汽車充電站是電動汽車產(chǎn)業(yè)的重要支撐系統(tǒng),雖然目前電動汽車還處于示范運營階段,但在其廣泛的應(yīng)用前景下,需要科學(xué)合理地對充電站進行規(guī)劃配置。 本文分析燃油出租車和燃油私家車的出行特征,假定電動汽車替代燃油車不會影響電動汽車用戶的出行特征,得到電動乘用車的充電特征,結(jié)果表明,電動私家車與電動出租車在充電開始時刻和行駛里程方面具有不同的分布規(guī)律。 針對電動出租車充電特征的隨機性,采用基于概率模型的統(tǒng)計學(xué)建模方法,建立電動出租車日充電負荷的分段概率估算模型,用蒙特卡羅仿真方法求得電動出租車的日充電負荷。根據(jù)南方某城市出租車的充電運營數(shù)據(jù),采用充電負荷的分段概率估算模型得到出租車日充電負荷并與實際負荷對比,結(jié)果表明,該建模方法具有可信性。 研究電動乘用車充電負荷估算方法,并根據(jù)南方某城市2015年和2020年電動乘用車發(fā)展?fàn)顩r估算規(guī)�；瘏^(qū)域電動乘用車的日充電負荷,結(jié)果表明,到2020年,電動乘用車充電負荷占南方某城市電網(wǎng)中負荷的比例不大。 在分析電動汽車充電行為的基礎(chǔ)上,基于排隊論理論建立充電設(shè)施服務(wù)系統(tǒng)排隊模型,以充電設(shè)施服務(wù)系統(tǒng)總費用最小為目標(biāo)函數(shù)建立充電設(shè)施費用最優(yōu)模型,得到最優(yōu)充電設(shè)施配置,并分析站內(nèi)充電設(shè)施配置對充電負荷的影響。
[Abstract]:With the development of electric vehicle technology and its charging facilities, electric vehicle will be more and more widely used in people's daily life, after the development of electric vehicle scale. The huge charge load of electric vehicle will become an important part of power grid load. In order to ensure that the power grid can meet the demand of large-scale development of electric vehicle charging. At the same time, to avoid and reduce the adverse impact of electric vehicle charging on the normal operation of the grid, it is necessary to study the charging load estimation method of regional electric passenger vehicle. Electric vehicle charging station is an important supporting system of electric vehicle industry, although the electric vehicle is still in the stage of demonstration operation. However, it is necessary to plan and dispose the charging station scientifically and reasonably under the prospect of its wide application. This paper analyzes the travel characteristics of fuel taxis and fuel private cars, assuming that the alternative fuel vehicles of electric vehicles will not affect the travel characteristics of electric vehicle users, and get the charging characteristics of electric passenger cars. The results show that. Electric private cars and electric taxis have different distribution at the beginning of charging and driving mileage. Aiming at the randomness of the charging characteristics of electric taxis, a piecewise probability estimation model of daily charging load of electric taxis is established by using the statistical modeling method based on probability model. The daily charging load of electric taxi is calculated by Monte Carlo simulation method. By using the piecewise probability estimation model of charging load, the daily charging load of taxi is obtained and compared with the actual load. The results show that the modeling method is credible. The charging load estimation method of electric passenger car is studied, and the daily charge load of electric passenger car in large-scale area is estimated according to the development of electric passenger car in a southern city on 2015 and 2020. By 2020, the charge load of electric passenger car is not much in a southern city power grid. Based on the analysis of charging behavior of electric vehicles, the queuing model of charging facility service system is established based on queuing theory. Taking the minimum total cost of charging facility service system as the objective function, the optimal model of charging facility cost is established, the optimal charging facility configuration is obtained, and the influence of charging facility configuration on charging load is analyzed.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM910.6;U469.72

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