電動汽車與電網(wǎng)互動技術的研究
發(fā)布時間：2018-07-17 17:02
【摘要】：隨著電動汽車數(shù)量的快速增加和充放電技術的成熟，一方面，電動汽車接入電網(wǎng)充電會對電網(wǎng)安全穩(wěn)定運行產(chǎn)生不可忽視的影響；另一方面，V2G（Vehicle-to-Grid）技術的發(fā)展又為智能電網(wǎng)的推廣帶來一些機遇。如何對電動汽車充放電行為進行合理地調(diào)度和控制，并對電網(wǎng)產(chǎn)生積極影響，，是一個值得研究的課題。本文根據(jù)電動汽車充放電行為特性，構建電動汽車充放電調(diào)度模型，探討了基于電網(wǎng)峰谷分時電價引導下的充放電行為對電網(wǎng)產(chǎn)生的影響。 本文首先對電動汽車發(fā)展對電網(wǎng)的影響進行了初步探討，包括大規(guī)模電動汽車入網(wǎng)對電網(wǎng)的不利影響和電動汽車作為儲能單元對電網(wǎng)的積極影響。介紹了V2G系統(tǒng)的發(fā)展過程及其組成部分，分析了V2G的運營和管理模式，本文采用集中V2G運營模式對電動汽車充放電行為進行管理和調(diào)度。根據(jù)國家對充電設施負荷等級的劃分及供電電源的要求，提出了三種具有V2G功能的電動汽車充電設施規(guī)劃方案。 其次，本文提出以對電網(wǎng)負荷進行削峰填谷為目標，重點針對小型私有電動汽車的功率需求，并考慮了電動汽車充放電功率、電池容量、電池荷電狀態(tài)等約束條件，建立了一天內(nèi)電動汽車參與電網(wǎng)調(diào)峰的模型，并用粒子群算法優(yōu)化調(diào)度策略，實現(xiàn)了電動汽車參與電網(wǎng)調(diào)峰的功能，通過實際算例，仿真驗證了電動汽車參與電網(wǎng)調(diào)峰的有效性。 最后，根據(jù)美國交通部門對美國私家車使用的研究結果，得出用戶日行駛里程和用戶充電時刻的概率模型，基于電網(wǎng)峰谷分時電價和相關假設的基礎上，建立了電動汽車無序充放電模型和峰谷電價引導后的充放電模型，考慮到峰谷電價響應程度，采用蒙特卡洛法模擬電動汽車充放電日負荷功率曲線，根據(jù)原始電網(wǎng)負荷，得出考慮電動汽車充放電影響的電網(wǎng)實際負荷。在上述基礎上，建立以電網(wǎng)負荷峰谷差最小為目標的電網(wǎng)峰谷電價時段優(yōu)化模型，并使用遺傳算法進行求解，通過實際算例驗證了模型的正確性。
[Abstract]:With the rapid increase of the number of electric vehicles and the maturity of the charge and discharge technology , on the one hand , the charging of the electric vehicle access network will have an unnegligible effect on the safe and stable operation of the power grid ;
On the other hand , the development of the V2G ( Vehicle - to - Grid ) technology has brought some opportunities for the popularization of the intelligent power grid . How to properly schedule and control the charging and discharging behavior of the electric vehicle is a subject worthy of study . According to the characteristics of the charging and discharging behavior of the electric automobile , the charging and discharging dispatching model of the electric automobile is constructed , and the influence of the charging and discharging behavior under the guidance of the power grid peak and valley time on the power grid is discussed .
This paper first discusses the influence of electric vehicle development on power grid , including the adverse effect of large - scale electric vehicle entering network on power grid and the positive influence of electric automobile as energy storage unit on power grid . The development process and its components of V2G system are introduced , and the operation and management mode of V2G is introduced . Three kinds of charging facilities planning schemes with V2G function are put forward according to the division of load rating of charging facilities and the requirement of power supply .
Secondly , this paper aims at the power demand of the small private electric vehicle , and takes into account the constraints of charging and discharging power , battery capacity and state of charge state of the electric automobile , and establishes the model of the electric automobile participating in the power grid peak regulation by using the particle swarm optimization algorithm .
In the end , according to the research results of the American transportation department to the private car in the United States , the probability model of daily driving mileage and user charging time is obtained . Based on the electricity price and related assumptions of the peak - valley electricity price of the electric vehicle , the electric vehicle random charge - discharge model and the peak - valley electricity price - guided charge - discharge model are established . Based on the above - mentioned foundation , the optimization model of the power grid peak - valley electricity price period is established taking the minimum of the peak - valley difference of the power grid as the target , and the genetic algorithm is used for solving the model , and the correctness of the model is verified by the practical example .
【學位授予單位】：天津理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U469.72;TM727
本文編號：2130317
[Abstract]:With the rapid increase of the number of electric vehicles and the maturity of the charge and discharge technology , on the one hand , the charging of the electric vehicle access network will have an unnegligible effect on the safe and stable operation of the power grid ;
On the other hand , the development of the V2G ( Vehicle - to - Grid ) technology has brought some opportunities for the popularization of the intelligent power grid . How to properly schedule and control the charging and discharging behavior of the electric vehicle is a subject worthy of study . According to the characteristics of the charging and discharging behavior of the electric automobile , the charging and discharging dispatching model of the electric automobile is constructed , and the influence of the charging and discharging behavior under the guidance of the power grid peak and valley time on the power grid is discussed .
This paper first discusses the influence of electric vehicle development on power grid , including the adverse effect of large - scale electric vehicle entering network on power grid and the positive influence of electric automobile as energy storage unit on power grid . The development process and its components of V2G system are introduced , and the operation and management mode of V2G is introduced . Three kinds of charging facilities planning schemes with V2G function are put forward according to the division of load rating of charging facilities and the requirement of power supply .
Secondly , this paper aims at the power demand of the small private electric vehicle , and takes into account the constraints of charging and discharging power , battery capacity and state of charge state of the electric automobile , and establishes the model of the electric automobile participating in the power grid peak regulation by using the particle swarm optimization algorithm .
In the end , according to the research results of the American transportation department to the private car in the United States , the probability model of daily driving mileage and user charging time is obtained . Based on the electricity price and related assumptions of the peak - valley electricity price of the electric vehicle , the electric vehicle random charge - discharge model and the peak - valley electricity price - guided charge - discharge model are established . Based on the above - mentioned foundation , the optimization model of the power grid peak - valley electricity price period is established taking the minimum of the peak - valley difference of the power grid as the target , and the genetic algorithm is used for solving the model , and the correctness of the model is verified by the practical example .
【學位授予單位】：天津理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U469.72;TM727
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