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Simplified Algorithm for Dynamic Demand Response in Smart Homes Under Smart Grid Environment

机译:智能电网环境下智能家庭动态需求响应简化算法

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Under Smart Grid environment, the consumers may respond to incentive-based smart energy tariffs for a particular consumption pattern. Demand Response (DR) is a portfolio of signaling schemes from the utility to the consumers for load shifting/shedding with a given deadline. The signaling schemes include Time-of-Use (ToU) pricing, Maximum Demand Limit (MDL) signals etc. This paper proposes a DR algorithm which schedules the operation of home appliances/loads through a minimization problem. The category of loads and their operational timings in a day have been considered as the operational parameters of the system. These operational parameters determine the dynamic priority of a load, which is an intermediate step of this algorithm. The ToU pricing, MDL signals, and the dynamic priority of loads are the constraints in this formulated minimization problem, which yields an optimal schedule of operation for each participating load within the consumer provided duration. The objective is to flatten the daily load curve of a smart home by distributing the operation of its appliances in possible low-price intervals without violating the MDL constraint. This proposed algorithm is simulated in MATLAB environment against various test cases. The obtained results are plotted to depict significant monetary savings and flattened load curves.
机译:在智能电网环境下,消费者可能会响应特定消费模式的基于激励的智能能源关税。需求响应(DR)是来自消费者的公用事业的信令方案的投资组合,用于使用给定的截止日期加载转换/脱落。信令方案包括使用时间(tou)定价,最大需求限制(MDL)信号等。本文提出了一种DR算法,该算法调度通过最小化问题的家用电器/负载的操作。在一天中的负载类别及其运行定时已被视为系统的操作参数。这些操作参数确定负载的动态优先级,这是该算法的中间步骤。 TOU定价,MDL信号和负载的动态优先级是该配方的最小化问题中的约束,其为消费者提供的持续时间内的每个参与负载产生最佳操作计划。目的是通过在可能的低价格间隔的情况下通过在不违反MDL约束的情况下将其设备的操作进行平衡智能家庭的日常负载曲线。在Matlab环境中模拟了该算法,用于针对各种测试用例。绘制了所获得的结果,以描述重大的货币储蓄和扁平的载荷曲线。

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