智能电网中大规模电动汽车充电的调度与优化策略

发布时间：2018-07-31 08:37

【摘要】：在环境污染和资源紧张的双重压力下,电动汽车作为一种新型交通工具,在缓解能源危机、减少环境污染等方面具有传统汽车不可比拟的优势。电动汽车的规模化应用受到世界范围的广泛关注,面向未来电动汽车灵活接入与电网互动、互利共赢,电动汽车充电优化控制方法成为研究的热点。本文分析了智能电网和电动汽车的现状及发展趋势,详细讨论了影响电动汽车充电负荷的因素,系统分析了电动汽车充电优化调度经典方法。研究了智能电网中利用电动汽车充电消纳分布式能源的可行性,提出了计及分布式能源接入的智能电网中大规模电动汽车充电的调度与优化策略。为消除大规模电动汽车无序充电给电力系统安全与经济运行带来的严重负面影响,,本文基于“电力系统调度中心—代理商—电动汽车”架构,提出了基于双层优化的电动汽车充电调度策略。在“电力系统调度中心—代理商”的上层模型中,通过优化各电动汽车中间代理商在各时段的调度计划,使系统在研究时间区间内总负荷水平的方差最小化,采用模拟退火算法求解了电力系统调度中心为各电动汽车中间代理商在各时段制定的调度计划,从而实现削峰填谷和消纳分布式能源的目的；在“代理商—电动汽车”的下层模型中,通过各电动汽车中间代理商对其所管辖的电动汽车充电功率的优化管理,以便与电力系统调度中心制定的调度计划尽可能一致,采用模拟退火算法求解了各中间代理商所管辖的电动汽车各时段的充电功率。所提的基于双层优化的电动汽车充电调度策略降低了电网负荷峰谷比,有效的消纳了分布式能源。
[Abstract]:Under the double pressure of environmental pollution and resource shortage, electric vehicle, as a new type of vehicle, has incomparable advantages in alleviating the energy crisis and reducing environmental pollution. The large-scale application of electric vehicles has attracted worldwide attention. The flexible access of electric vehicles to the future and grid interaction, mutual benefit and win-win, electric vehicle charging optimization control method has become a hot spot. This paper analyzes the current situation and development trend of smart grid and electric vehicle, discusses in detail the factors that affect the charging load of electric vehicle, and systematically analyzes the classical methods of charging optimization of electric vehicle. In this paper, the feasibility of using electric vehicle to charge and absorb distributed energy in smart grid is studied, and the scheduling and optimization strategy of large-scale electric vehicle charging in smart grid with distributed energy access is proposed. In order to eliminate the serious negative impact of disordered charging of large-scale electric vehicles on the safety and economic operation of power systems, this paper is based on the framework of "Power system dispatching Center-agents-Electric vehicles". A charging scheduling strategy for electric vehicles based on double-layer optimization is proposed. In the upper layer model of "power system dispatching center-agent", the variance of the total load level in the study time range is minimized by optimizing the scheduling plan of each electric vehicle intermediate agent in each time period. The simulated annealing algorithm is used to solve the scheduling plan of the power system dispatching center for the middle agents of each electric vehicle in each period, so as to realize the purpose of cutting the peak and filling the valley and eliminating the distributed energy. In the "agent-electric vehicle" model, the optimal management of the charging power of the electric vehicle under its jurisdiction by the middle agents of each electric vehicle is carried out in order to be as consistent as possible with the scheduling plan made by the power system dispatching center. The simulated annealing algorithm is used to calculate the charging power of electric vehicles under the jurisdiction of various intermediate agents. The proposed charging scheduling strategy for electric vehicles based on double-layer optimization reduces the peak-valley ratio of power grid load and effectively absorbs distributed energy.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM73

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