基于服务器的智能电表系统负载分析

S. Elakshumi, A. Ponraj
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引用次数: 11

摘要

随着人口的增长和家庭中不同电器的使用,电力需求也在增加。因此,消费者需要跟踪他们的日常使用情况并了解消费模式,以节省和控制这些资源。智能电表以及高级计量基础设施(AMI)是一种实用而有效的解决方案。早期使用单向通信收集仪表数据的程序被称为自动抄表系统(AMR)。本文旨在分析拟议的智能电表系统的性能、高效传输以及公用事业如何通过远程监控能源消耗来探索新的发展,以造福消费者和他们自己。分析结果所遵循的方法是电力线通信(PLC),这是一种将数据传递到用于将电力从高压输电线路传输到建筑物内使用的低压线路的电导体上的安排。这是通过使用PLC调制解调器对电能表进行远程监控来实现的。通过这种方式,我们可以减少人类需要的努力来概述仪表读数,到目前为止,这些读数是通过单独访问每个家庭来记录的。因此,对公用事业公司的消费模式进行了研究,并进行了负荷分析,从而有助于维护与能源管理相关的其他系统。为了研究和分析负载消耗模式,在MATLAB中进行了仿真。通过这种方法,可以对能源消耗进行估计,从而控制其使用。
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A server based load analysis of smart meter systems
The electricity demand is increasing with the growth of population and with the use of different appliances in the households. So, there is a need for consumers to track their daily usage and understand the consumption patterns to save and control these resources. Smart meter along with Advanced Metering Infrastructure(AMI) is a pragmatic and efficient solution for this. Earlier procedure which put to profitable use of one-way communications to gather meter data, were mentioned to as Automated Meter Reading (AMR)Systems. This paper aims at analysing the performance of the proposed smart meter systems, efficient transmission and how utilities explore new developments for the benefit of consumers as well as themselves by remotely monitoring energy consumption. The methodology followed to analyze the outcome is Power Line Communication(PLC), which is an arrangement to pass on data on an electrical conductor used for transmitting electric power from high voltage transmission lines to lower voltage lines used inside the buildings. This is achieved by using PLC modems for remote monitoring and control of energy meters. By this way we can bring down human efforts needed to outline meter readings which are till now recorded by visiting every home individually. As a result, the consumption patterns at the utilities are studies and load analysis is made so that this can help in maintaining other systems associated with energy management. To study and analyze the load consumption patterns, simulations were carried out in MATLAB. By this way an estimate on the energy consumption can be made and thus have a control on its usage.
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