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Demand response management using cloud enabled load optimization

机译:使用云启用负载优化需求响应管理

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Energy demand for users of residential, commercial, industrial and agriculture has been largely uncontrollable and inelastic in relation to power production. There is urgency in power sector to provide flexibility in energy use by various sectors so as to maintain the stability and efficiency of the electric system. At the same time it is important to maintain the minimum peak average ratio (PVR). DSM can smoothen the peak to-average ratio (PAR) of power usage in electricity supply. In this paper, the main aim is to encourage the consumers to use less energy during peak hours by sending message alerts to the particular consumer with the cost allocated for the unit usage and to maintain the maximum profit profile for generation companies. For this we simulated power generation and the distribution models with LabVIEW technology. From this simulated model we collect the data of the generation and the distribution systems for every interval. This is stored in the data base of the cloud platform. When the demand profile is more than the generation profile from the collected cloud data, peak load time is observed on that time and the collected data is compared by the optimized data which is taken by the maximum profit optimized solution. In this case sending the message alerts to the consumer and consumer also be a part of DSM of the electricity system.
机译:对住宅,商业,工业和农业用户的能源需求在很大程度上是与电力生产相关的不可控制和无弹性。电力部门的紧迫性在各个部门提供能源使用的灵活性,以保持电气系统的稳定性和效率。同时保持最小峰值平均值(PVR)是重要的。 DSM可以平滑电力供应中电源使用的峰值平均比率(PAR)。在本文中,主要目的是通过向特定消费者发送消息警报来鼓励消费者在高峰时段使用能量较少,以便为单位使用的成本分配,并维护一代公司的最大利润配置文件。为此,我们模拟了带LabVIEW技术的发电和分布模型。从这个模拟模型,我们为每个间隔收集生成和分发系统的数据。这存储在云平台的数据库中。当需求简档大于从所收集的云数据的生成轮廓,峰负荷时间对时间观察所收集的数据进行比较,通过该采取的是最大的利润优化的解决方案的最优化的数据。在这种情况下,向消费者和消费者发送消息警报也是电力系统DSM的一部分。

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