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Simulation and optimisation study of the integration of distributed generation and electric vehicles in smart residential district

机译:智能住宅区分布式发电与电动汽车融合的仿真与优化研究

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摘要

This paper presents an optimisation methodology for simulating the integration of distributed generation and electric vehicles (EVs) in a residential district. A model of a smart residential district is proposed. Different charging scenarios (CS) for private cars are considered for simulating different power demand distributions during the day. Four different case studies are investigated, namely the Base Case, in which no EVs are present in the district and three study cases with different CSs. A global optimisation method based on a genetic algorithm approach was applied on the model to find the total power from PV panels installed and co-generative micro gas turbines while minimising the annual energy cost in the district for the four different scenarios. In conclusion, the results showed that the use of EVs in the district introduces considerable savings with respect to the Base Case. Moreover, the impact of the chosen CS is nearly insignificant under a purely economic perspective even if it is relevant for grid management. Additionally, the optimum amounts of installed power vary in a limited range if the distance travelled by EVs, users’ departure and arrival time change broadly.
机译:本文提出了一种用于模拟居民区中的分布式发电和电动汽车(EV)集成的优化方法。提出了智能住宅小区的模型。考虑了用于私家车的不同充电方案(CS),以模拟白天的不同电力需求分配。调查了四个不同的案例研究,即基础案例(其中基础区域中没有电动汽车)和三个具有不同CS的研究案例。在模型上应用了基于遗传算法方法的全局优化方法,以从已安装的光伏面板和热电联产微型燃气轮机中查找总功率,同时最大程度地降低了四种情况下该地区的年度能源成本。总之,结果表明,与基本案例相比,在该地区使用电动汽车可节省大量资金。而且,从纯粹的经济角度来看,即使与电网管理相关,所选CS的影响也几乎是微不足道的。此外,如果电动汽车行驶的距离,用户的出发和到达时间发生较大变化,则最佳安装功率量将在有限的范围内变化。

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