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Optimized Control of Price-Based Demand Response With Electric Storage Space Heating

机译:储热空间的基于价格的需求响应的最优控制

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The increased uncertainty of the electric grid due to the penetration of renewable energy sources and deregulation of the electric market is aimed to be alleviated by demand response (DR) in the future smart grid. The demand-side resources can be incentivized to alter their consumption patterns by varying their electricity price over time. A major residential energy demand contribution is from electric heating, which, when combined with smart energy storage using water heaters, could be utilized to defer consumption to more inexpensive periods without affecting the customer's thermal quality of service. The objective is to optimize the consumer electricity price of electric storage space heating customers, in order to maximize the profit of the retailer. This approach of varying the customer electricity prices leads to a game-theoretic scenario, where the procurement and consumption profiles of the retailer and consumer agents are based on the set electricity price. The optimization of the consumer electricity price is shown to offer lesser expense for the retailer. In addition, hourly load-following can be improved by offering further discounts for the consumers.
机译:旨在通过未来智能电网中的需求响应(DR)来缓解由于可再生能源的渗透和电力市场管制而导致的电网不确定性增加。可以激励需求侧资源通过随时间改变电价来改变其消费模式。住宅能源需求的主要来源是电加热,当与使用热水器的智能储能结合使用时,可将其推迟到更便宜的时段使用,而不会影响客户的热服务质量。目的是优化储热空间供暖客户的消费电价,以最大程度地提高零售商的利润。这种改变客户电价的方法导致了博弈论的场景,其中零售商和消费者代理商的采购和消费概况基于设定的电价。消费者电价的优化显示为零售商提供了更少的费用。另外,可以通过为消费者提供进一步的折扣来改善每小时的负荷跟踪。

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