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基于电动汽车负荷预测的台区变压器选型策略 被引量:4

Transformer selection strategy based on electric vehicle load forecasting
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摘要 电动汽车凭借其特殊的能源驱动方式,可以有效地降低污染排放和提高能源利用效率,但作为一种新型负荷在带来社会效益的同时,也给电网的运行带来了诸多挑战。电动汽车渗透率的提高将引起电力系统整体负荷的增长,进而推动配电网提前改造。因此在进行配电网的扩容与升级时,有必要充分考虑电动汽车的影响。首先分析了电动汽车发展对电力系统的影响以及工程实际中配电网扩容需要考虑的因素。然后分析了电动汽车充电负荷的影响因素,并建立相应的预测模型,基于分析过程选择既可以反映模型参数,又方便采集的可观测量,从而为实现区域内电动汽车的负荷预测提供方向。在此基础上,进一步建立区域的配电网经济模型,指导供电台区内的变压器选型和评价指标的调整,在满足供电可靠性的前提下,提高电网的适应性和经济性,进一步促进电动汽车与电网的协同发展。 With the special energy driving mode,electric ve?hicles can effectively reduce pollution emissions and improve ener?gy efficiency.But as a new type of load,it brings social benefits and many challenges to the operation of the power grid.With the gradual increase of electric vehicle penetration,the load of power system will increase significantly and promote the transformation of distribution network in advance.When expanding and upgrading the distribution network,it is necessary to fully consider the impact of electric vehicles and make reasonable planning.The influence of the development of electric vehicles on the power system and the factors that need to be considered in the process of expansion of distribution network are analyzed.Then the factors that affect the charging load of electric vehicles,and the corresponding prediction model is established.Based on the prediction model,the observ?able quantity which can reflect the model parameters and be easily collected is selected.Based on the results of load forecasting,the regional economic model of distribution network is established to guide the selection of transformers in the upgrade process.On the premise of satisfying the reliability,the adaptability and economy of power grid are improved,and the coordinated development of electric vehicles and power grid is further promoted.
作者 韩天轮 冉纯嘉 毛安家 阳昌旺 赵丽娜 HAN Tianlun;RAN Chunjia;MAO Anjia;YANG Changwang;ZHAO Lina(State Grid Tianjin Binhai Power Supply Company,Tianjin 300451,China;China Automobile Technology Research Center,Tianjin 300300,China;North China Electric Power University,Beijing 102206,China;State Grid Anhui Huangshan Power Supply Company,Huangshan 245000,China)
出处 《电力需求侧管理》 2019年第5期46-51,共6页 Power Demand Side Management
基金 国家自然科学基金(51207050) 国家电网公司科技项目(SGAHJY00GHJS1700156)
关键词 电动汽车 负荷预测 lingo优化模型 变压器选型 electric vehicle load forecasting lingo optimizationmodel transformerselection
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