Resource-efficient Model-Predictive PV control data communication

Kai Robin Piontek, N. Dorsch, C. Wietfeld
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引用次数: 3

Abstract

For the control of decentralized energy resources (DERs), Virtual Power Plants (VPPs) have been introduced to match the volatile production with the demand of energy consumers. However, due to their fluctuating feed-in, renewable energy sources such as photovoltaic (PV) systems need to be closely monitored and controlled, which in turn results in considerable communication effort. Aiming at reducing the periodic, costly wide-area communication of monitoring data between the PVs and the VPP, we introduce and validate in this paper our approach of Model Predictive PV Control Communication (MPCC). Leveraging a dedicated Efficient PV Production (EPVP) model which synchronously estimates the PV production on both ends of the wide-area communication path, i.e. the DERs and the VPP, the amount of transmitted monitoring data can be reduced considerably (up to 100% depending on weather conditions and acceptable prediction error). The introduced EPVP model is validated with real-life data of various PV systems. Finally, the proper parametrization and efficiency of the proposed MPCC has been analysed for various weather conditions.
资源高效模型-预测光伏控制数据通信
为了控制分散的能源资源,引入了虚拟发电厂(vpp)来匹配不稳定的生产与能源消费者的需求。然而,由于其波动的馈入,可再生能源,如光伏(PV)系统需要密切监测和控制,这反过来又导致了相当大的通信工作。为了减少PV和VPP之间监测数据的周期性、高成本的广域通信,本文介绍并验证了模型预测PV控制通信(MPCC)方法。利用专用的高效光伏发电(EPVP)模型,该模型可以同步估计广域通信路径两端的光伏产量,即DERs和VPP,传输的监测数据量可以大大减少(根据天气条件和可接受的预测误差,最多可减少100%)。用实际的光伏系统数据验证了所引入的EPVP模型。最后,分析了不同天气条件下MPCC的参数化和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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