本文選題：電動(dòng)汽車(chē) + V2G技術(shù)　； 參考：《湖南大學(xué)》2016年碩士論文

【摘要】：當(dāng)今環(huán)境日益污染、能源日益缺乏,電動(dòng)汽車(chē)(Electric Vehicles, EVs)作為一種清潔、環(huán)保的交通工具,對(duì)保護(hù)環(huán)境,緩解能源短缺,調(diào)整能源結(jié)構(gòu)具有重要作用。電動(dòng)汽車(chē)行業(yè)具有廣闊的發(fā)展前景,若大量電動(dòng)汽車(chē)涌入市場(chǎng),其充電負(fù)荷將對(duì)配電網(wǎng)的電能質(zhì)量、經(jīng)濟(jì)運(yùn)行等方面產(chǎn)生不可忽視的影響。因此,研究電動(dòng)汽車(chē)的規(guī)�；尤雽�(duì)配電網(wǎng)的影響,提出優(yōu)化方案對(duì)充電負(fù)荷進(jìn)行控制管理具有重要的現(xiàn)實(shí)意義。為使電動(dòng)汽車(chē)能更好的融入電力系統(tǒng),本論文對(duì)規(guī)�；碾妱�(dòng)汽車(chē)充放電控制進(jìn)行研究。首先研究了電動(dòng)汽車(chē)充電負(fù)荷的計(jì)算方法。在確定了充電負(fù)荷的主要影響因素后,建立了充電負(fù)荷模型,采用蒙特卡洛法對(duì)電動(dòng)汽車(chē)充電負(fù)荷進(jìn)行計(jì)算,并對(duì)電動(dòng)汽車(chē)充電行為進(jìn)行模擬。在此基礎(chǔ)上,分析了不同情景下電動(dòng)汽車(chē)充電負(fù)荷對(duì)配電網(wǎng)網(wǎng)損、電壓偏移的影響。仿真結(jié)果表明,大規(guī)模電動(dòng)汽車(chē)的隨機(jī)接入會(huì)造成負(fù)荷“峰上加峰”,并且隨著滲透率提高,配電網(wǎng)電壓偏移明顯變大。為了對(duì)電動(dòng)汽車(chē)實(shí)行較為有效的控制管理,提出了基于聚合商分層管理控制結(jié)構(gòu)的智能充電方法,以電網(wǎng)峰值負(fù)荷最小為優(yōu)化目標(biāo)建立了智能充電策略模型。研究了不同充電策略下評(píng)估電動(dòng)汽車(chē)充電對(duì)配電網(wǎng)影響的方法并給出具體步驟和算法流程,通過(guò)算例評(píng)估無(wú)序充電、分時(shí)電價(jià)充電和智能充電三種充電策略下電動(dòng)汽車(chē)接入后對(duì)電網(wǎng)的影響。仿真結(jié)果表明,智能充電策略更能有效降低負(fù)荷的峰荷,同時(shí)獲得更好的電壓分布和更低的電能損耗,有利于電網(wǎng)的安全經(jīng)濟(jì)運(yùn)行。在地區(qū)電網(wǎng)含有風(fēng)電和光伏機(jī)組出力的情形下,探討了電動(dòng)汽車(chē)平抑負(fù)荷波動(dòng)的充放電策略。提出了基于V2G模式情況下電動(dòng)汽車(chē)與可再生能源的多目標(biāo)協(xié)同調(diào)度模型,以合理安排電動(dòng)汽車(chē)的充放電行為。該模型以地區(qū)電網(wǎng)等效負(fù)荷波動(dòng)最小和用戶(hù)充電費(fèi)用最低為目標(biāo)函數(shù),兼顧了降低電網(wǎng)負(fù)荷峰谷差、促進(jìn)可再生能源吸納和提高電動(dòng)汽車(chē)用戶(hù)相應(yīng)積極性等方面的需求。通過(guò)對(duì)目標(biāo)函數(shù)的模糊處理,并應(yīng)用自適應(yīng)粒子群優(yōu)化算法進(jìn)行求解,得到最優(yōu)充放電策略。仿真結(jié)果驗(yàn)證了模型的有效性和求解方法的可行性。
[Abstract]:Nowadays, the environment is becoming increasingly polluted and energy is increasingly lacking. As a clean and environmentally friendly vehicle, electric vehicles (EVs) play an important role in protecting the environment, alleviating the energy shortage and adjusting the energy structure. The electric vehicle industry has a broad prospect of development. If a large number of electric vehicles pour into the market, its charging load will have a significant impact on the power quality and economic operation of the distribution network. Therefore, it is of great practical significance to study the influence of the large-scale access of electric vehicles on the distribution network and to put forward an optimized scheme to control and manage the charging load. In order to better integrate electric vehicle into power system, this paper studies the charge and discharge control of large-scale electric vehicle. Firstly, the calculation method of electric vehicle charging load is studied. After determining the main influencing factors of charging load, the charging load model is established, and the charging load of electric vehicle is calculated by Monte Carlo method, and the charging behavior of electric vehicle is simulated. On this basis, the influence of electric vehicle charging load on distribution network loss and voltage offset is analyzed. The simulation results show that the random access of large scale electric vehicles will result in the load "peak plus peak", and with the increase of permeability, the distribution network voltage offset is obviously increased. In order to implement more effective control management for electric vehicles, an intelligent charging method based on the hierarchical management control structure of aggregators is proposed. The intelligent charging strategy model is established with the minimum peak load as the optimization objective. The methods of evaluating the influence of electric vehicle charging on distribution network under different charging strategies are studied, and the concrete steps and algorithm flow are given, and the disordered charging is evaluated by an example. The influence of electric vehicle access on power grid under three charging strategies of time-sharing pricing and intelligent charging. The simulation results show that the intelligent charging strategy can effectively reduce the peak load and obtain better voltage distribution and lower power loss, which is beneficial to the safe and economical operation of the power grid. The charging and discharging strategies for suppressing load fluctuation of electric vehicles are discussed in the case of local power grid with wind power and photovoltaic unit output. A multi-objective cooperative scheduling model of electric vehicle and renewable energy based on V2G mode is proposed to reasonably arrange the charging and discharging behavior of electric vehicle. The model takes the minimum fluctuation of equivalent load and the lowest charge cost as the objective function to reduce the peak and valley difference of power grid load, to promote renewable energy absorption and to improve the enthusiasm of electric vehicle users. The optimal charging and discharging strategy is obtained by fuzzy processing of objective function and application of adaptive particle swarm optimization (APSO) algorithm. The simulation results verify the validity of the model and the feasibility of the solution method.
【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：TM73
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本文編號(hào)：1789409