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Generation of domestic hot water, space heating and driving pattern profiles for integration analysis of active loads in low voltage grids

机译:用于生成国内热水,空间加热和驱动图案型材,用于低压网格中有源负载的集成分析

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The changes in the Danish energy sector, consequence of political agreements, are expected to have direct impact in the actual power distribution systems. Large number of electric boiler, heat pumps and electric vehicles are planned and will cope large percentage of the future power consumption at household level. Despite of the well-known flexible service that this kind of loads can provide, their flexibility is highly dependent of the domestic hot water and space heating demand and the driving habits of each user. This paper presents two methodologies employed to randomly generate thermal power demand and electric vehicle driving profiles, to be used for power grid calculations. The generated thermal profiles relied on a statistical analysis made from real domestic hot water and space heating data from 25 households of a typical Danish residential area. The driving profiles instead were formed based on conclusions derived from previous analysis on Danish driving patterns and the driving cycles extracted from the European project ARTEMIS. The obtained random profiles will allow electrical networks in Denmark to be analyzed while maintaining the probability of the original data set.
机译:预计丹麦能源部门的变化,政治协议的后果将对实际配电系统产生直接影响。计划大量电动锅炉,热泵和电动车辆,并将在家庭水平上应对未来的未来功耗。尽管具有这种负荷可以提供的众所周知的灵活性服务,但它们的灵活性高度依赖于国内热水和空间加热需求以及每个用户的驾驶习惯。本文介绍了用于随机产生热电需求和电动车辆驾驶配置文件的两种方法,用于电网计算。产生的热型材依赖于由典型的丹麦住宅区25户的实际家庭热水和空间加热数据制成的统计分析。基于丹麦驾驶模式的先前分析和从欧洲项目artemis提取的驱动循环来形成驾驶配置文件。所获得的随机轮廓将允许在保持原始数据集的概率的同时分析丹麦中的电网。

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