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Modeling storage and demand management in power distribution grids

机译:建模配电网中的存储和需求管理

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Storage devices and demand control may constitute beneficial tools to optimize electricity generation with a large share of intermittent resources through inter-temporal substitution of load. This paper quantifies the related cost reductions in a simulation model of a simplified stylized medium-voltage grid (10 kV) under uncertain demand and wind output. Benders Decomposition Method is applied to create a two-stage stochastic optimization program. The model informs an optimal investment sizing decision as regards specific 'smart' applications such as storage facilities and meters enabling load control. Model results indicate that central storage facilities are a more promising option for generation cost reductions as compared to demand management. Grid extensions are not appropriate in any of the scenarios. A sensitivity analysis is applied with respect to the market penetration of uncoordinated Plug-In Electric Vehicles which are found to strongly encourage investment into load control equipment for 'smart' charging and slightly improve the case for central storage devices.
机译:存储设备和需求控制可能构成有益的工具,可以通过跨时间的负载替代来优化具有大量间歇资源的发电。本文在需求和风输出不确定的情况下,在简化的程式化中压电网(10 kV)的仿真模型中量化了相关的成本降低。应用Benders分解方法创建一个两阶段随机优化程序。该模型针对特定的“智能”应用(例如可实现负载控制的存储设施和仪表)提供了最佳的投资规模决策。模型结果表明,与需求管理相比,中央存储设施是降低发电成本的更有希望的选择。网格扩展不适用于任何情况。针对不协调的插电式电动汽车的市场渗透率进行了敏感性分析,这被发现极大地鼓励了对用于“智能”充电的负荷控制设备的投资,并略微改善了中央存储设备的外壳。

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