智能电网中考虑电动汽车储能特性的家庭用电策略研究
发布时间：2018-08-02 08:10
【摘要】：在智能电网环境下,从需求响应管理角度考虑将电动汽车引入住宅配电系统,一方面可以减轻环境污染,节约能源,另一方面电动汽车具有储能特性,可以作为储能设备为用户带来放电收益。但电动汽车是大功率充电负载,需要进行合理的充放电调度控制才能避免造成电网负载峰值增大,家庭用电开支增加的不良影响。为了解决这些问题,本文展开了以下研究:首先,为了解决引入电动汽车在住宅配电系统下进行用电后导致的电网过载和用户用电开支增加的问题,本文采用了注水原理算法(water-filling),并结合电动汽车储能特性和一个简单有效的价格预测机制,搭建了家庭用电成本模型。该算法将可调负载调整至可调时间段中电价最低时段进行用电;将电动汽车移至夜间用电需求和电价均相对较低时间进行充电;同时电动汽车闲置期间,利用蓄电池储能特性,为用电高峰期使用的不可调负载进行供电,从而缓解电网过载现象,减小用户家庭用电成本。其次,在注水原理算法的基础上,利用电动汽车储能特性进行充放电后,对蓄电池使用寿命造成影响。而电动汽车蓄电池的更换成本昂贵,若不对其放电特性加以合理利用,会造成蓄电池使用寿命减小,进而家庭用电成本大幅度增加。基于以上分析,本文提出了一种基于电动汽车蓄电池SOC状态的家庭用电算法。该算法结合电动汽车蓄电池SOC状态和蓄电池的使用寿命建立用电成本优化模型,获取了蓄电池放电门限值nSOC和最佳放电状态点lSOC。在电动汽车使用归来后,用户针对蓄电池已进行的放电次数选择合适的用电策略。合理有效的利用好电动汽车的充放电功能,在减小家庭用电成本的同时尽可能延长电动汽车蓄电池的使用寿命。然后,在针对单个家庭用电状况的基础上,本文提出了基于纳什均衡博弈论的需求响应分布式算法。该算法是对多用户用电策略进行优化,达到共同利益最大化。本文提出的策略基础是用户之间的交互。该策略下的分布式算法只需要用户试图最大化个人利益时,使用博弈论进行交互的信息,在不牺牲任何一个用户利益的前提下达到共同获益的目的。结合电动汽车的储能特性对用户们的用电策略进行协调控制,从而实现能耗成本和PAR最小化。
[Abstract]:In the environment of smart grid, considering the introduction of electric vehicle into residential distribution system from the point of view of demand response management, on the one hand, it can reduce environmental pollution and save energy, on the other hand, electric vehicle has the characteristics of energy storage. It can be used as energy storage equipment to bring customers discharge revenue. However, electric vehicle is a high-power charging load, so reasonable charge and discharge scheduling control is needed to avoid the adverse effects of the increase of load peak and the increase of household electricity consumption. In order to solve these problems, the following researches are carried out in this paper: firstly, in order to solve the problem of overload of power grid and increase of consumer power consumption caused by introducing electric vehicles under residential distribution system, In this paper, the water injection principle algorithm (water-filling) is adopted, combined with the energy storage characteristics of electric vehicles and a simple and effective price prediction mechanism, a household electricity cost model is built. The algorithm adjusts the adjustable load to the lowest electricity price period in the adjustable time period, moves the electric vehicle to the lower power demand and price at night, and uses the energy storage characteristics of the battery during the idle period of the electric vehicle. Power supply for the unadjustable load used in the peak period can alleviate the overload phenomenon of power grid and reduce the cost of household electricity consumption. Secondly, on the basis of the principle of water injection, the battery life is affected by charging and discharging using the energy storage characteristics of electric vehicle. However, the replacement cost of electric vehicle batteries is expensive. If the discharge characteristics of the batteries are not properly utilized, the battery life will be reduced, and the household electricity cost will be increased greatly. Based on the above analysis, this paper presents a household power consumption algorithm based on the SOC state of electric vehicle battery. Based on the SOC state of electric vehicle battery and the service life of battery, the optimization model of power consumption cost is established, and the discharge threshold nSOC and the optimal discharge state point lSOC are obtained. After the electric vehicle comes back from use, the user chooses the appropriate power strategy for the discharge times of the battery. Reasonable and effective use of the charge and discharge function of electric vehicles, while reducing the cost of household electricity, as much as possible to prolong the battery life of electric vehicles. Then, a distributed demand response algorithm based on Nash equilibrium game theory is proposed. The algorithm is to optimize the multi-user power consumption strategy to maximize the common benefits. The strategy proposed in this paper is based on the interaction between users. The distributed algorithm under this strategy only requires users to use game theory to interact with each other when they try to maximize their personal interests and to achieve the goal of mutual benefit without sacrificing the interests of any one of the users. Combined with the energy storage characteristics of electric vehicles, the power consumption strategies of users are coordinated and controlled, thus minimizing the energy consumption cost and PAR.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM73
，
本文编号：2158768
[Abstract]:In the environment of smart grid, considering the introduction of electric vehicle into residential distribution system from the point of view of demand response management, on the one hand, it can reduce environmental pollution and save energy, on the other hand, electric vehicle has the characteristics of energy storage. It can be used as energy storage equipment to bring customers discharge revenue. However, electric vehicle is a high-power charging load, so reasonable charge and discharge scheduling control is needed to avoid the adverse effects of the increase of load peak and the increase of household electricity consumption. In order to solve these problems, the following researches are carried out in this paper: firstly, in order to solve the problem of overload of power grid and increase of consumer power consumption caused by introducing electric vehicles under residential distribution system, In this paper, the water injection principle algorithm (water-filling) is adopted, combined with the energy storage characteristics of electric vehicles and a simple and effective price prediction mechanism, a household electricity cost model is built. The algorithm adjusts the adjustable load to the lowest electricity price period in the adjustable time period, moves the electric vehicle to the lower power demand and price at night, and uses the energy storage characteristics of the battery during the idle period of the electric vehicle. Power supply for the unadjustable load used in the peak period can alleviate the overload phenomenon of power grid and reduce the cost of household electricity consumption. Secondly, on the basis of the principle of water injection, the battery life is affected by charging and discharging using the energy storage characteristics of electric vehicle. However, the replacement cost of electric vehicle batteries is expensive. If the discharge characteristics of the batteries are not properly utilized, the battery life will be reduced, and the household electricity cost will be increased greatly. Based on the above analysis, this paper presents a household power consumption algorithm based on the SOC state of electric vehicle battery. Based on the SOC state of electric vehicle battery and the service life of battery, the optimization model of power consumption cost is established, and the discharge threshold nSOC and the optimal discharge state point lSOC are obtained. After the electric vehicle comes back from use, the user chooses the appropriate power strategy for the discharge times of the battery. Reasonable and effective use of the charge and discharge function of electric vehicles, while reducing the cost of household electricity, as much as possible to prolong the battery life of electric vehicles. Then, a distributed demand response algorithm based on Nash equilibrium game theory is proposed. The algorithm is to optimize the multi-user power consumption strategy to maximize the common benefits. The strategy proposed in this paper is based on the interaction between users. The distributed algorithm under this strategy only requires users to use game theory to interact with each other when they try to maximize their personal interests and to achieve the goal of mutual benefit without sacrificing the interests of any one of the users. Combined with the energy storage characteristics of electric vehicles, the power consumption strategies of users are coordinated and controlled, thus minimizing the energy consumption cost and PAR.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM73
，
本文编号：2158768
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