本文選題：電動汽車 + 馬爾科夫鏈　； 參考：《工程科學與技術(shù)》2017年03期

【摘要】：考慮用戶出行習慣的復(fù)雜性、多樣性,對區(qū)域充電樁進行合理的配置以滿足充電需求。首先,通過馬爾科夫鏈模型描述電動汽車用戶一天出行過程中在行駛、充電、不充電也不行駛3種決策行為下,動力電池荷電狀態(tài)的變化情況。以此確定該過程中電動汽車用戶的實時充電行為,得出不同類型電動汽車的快充、慢充負荷需求。然后,考慮規(guī)劃區(qū)內(nèi)電動汽車的移動特性及其不同時段不同類型電動汽車輛數(shù),預(yù)測各區(qū)域各時段充電負荷的需求情況。最后,以投資、運維成本最小為目標建立區(qū)域充電樁優(yōu)化配置模型。該模型計及了電動汽車移動特性均衡等約束條件,并通過粒子群優(yōu)化算法求解。對33節(jié)點4區(qū)域系統(tǒng)電動汽車充電負荷需求預(yù)測及其充電樁配置進行仿真,仿真結(jié)果驗證了所提方法的有效性和可行性。
[Abstract]:Considering the complexity and diversity of the user's travel habits, the regional charging piles are reasonably configured to meet the charging demand. Firstly, Markov chain model is used to describe the change of charged state of electric vehicle under three kinds of decision behavior: driving, charging, charging and driving. The real-time charging behavior of electric vehicle users is determined, and the demands of different types of electric vehicles for fast charging and slow charging are obtained. Then, considering the moving characteristics of electric vehicles in the planning area and the number of different types of electric vehicles in different periods of time, the demand for charging load in different periods of time in each region is forecasted. Finally, the optimal configuration model of regional charging pile is established with the aim of minimum investment and operation cost. The model takes into account the equilibrium constraints of the moving characteristics of electric vehicles and is solved by particle swarm optimization (PSO). The demand forecast of charging load and charging pile configuration of 33-bus 4-region system electric vehicle are simulated. The simulation results show that the proposed method is effective and feasible.
【作者單位】： 四川大學電氣信息學院;國網(wǎng)福建省電力有限公司電力科學研究院;國網(wǎng)福建省電力有限公司廈門供電公司;
【基金】：國家自然科學基金資助項目(51377111) 四川省科技廳應(yīng)用基礎(chǔ)項目資助(2015JY0128) 四川大學引進人才科研啟動經(jīng)費資助項目(20822041A4161) 國家電網(wǎng)總部科技項目資助
【分類號】：TM715;U491.8

【相似文獻】

相關(guān)期刊論文 前4條

1 蔣t橁，

本文編號：1872263