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Renewable microgrid state estimation using the Internet of Things communication network

机译:使用物联网通信网络的可更新微电网状态估计

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Given the huge concerns all over the world regarding carbon emissions from fossil fuels, energy crisis and global warming, the renewable distributed energy resources (DERs) are going to be integrated in electricity grids, which will make the energy supply more reliable and decrease transmission losses. Regrettably, one of the main practical defies in smart grid planning, control and operation with DERs is the voltage regulation at the distribution field level. This problem motivates the deployment of sensors and actuators in electricity grids so that the voltage regulation can be controlled at the desired level. To do that the measurements from the renewable microgrid state information is transmitted to an energy management center via the internet of things (IoT) based communication network. In other words, the proposed IoT communication infrastructure provides an opportunity to address the voltage regulation challenge by offering the two-way communication links for microgrid state information collection and estimation. Based on this smart grid communication infrastructure, we propose a Kalman filter based state estimation method for voltage regulation of the microgrid. Finally, the effectiveness of the Kalman filter based state estimation method is illustrated using the linear state space model of a microgrid incorporating DERs.
机译:鉴于世界各地对化石燃料的碳排放,能源危机和全球变暖的担忧,可再生分布式能源(DERs)将被整合到电网中,这将使能源供应更加可靠并减少传输损耗。遗憾的是,使用DER进行智能电网计划,控制和运行的主要实践缺陷之一是配电领域的电压调节。该问题促使传感器和致动器在电网中的部署,从而可以将电压调节控制在期望的水平。为此,来自可再生微电网状态信息的测量值通过基于物联网(IoT)的通信网络传输到能源管理中心。换句话说,提出的物联网通信基础设施通过提供双向通信链路以用于微电网状态信息的收集和估计,提供了应对电压调节挑战的机会。基于这种智能电网通信基础设施,我们提出了一种基于卡尔曼滤波器的状态估计方法,用于微电网的电压调节。最后,使用结合了DER的微电网的线性状态空间模型,说明了基于卡尔曼滤波器的状态估计方法的有效性。

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