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辐照度监测用高性能无线传感器网络的设计与测试。

Design and Test of a High-Performance Wireless Sensor Network for Irradiance Monitoring.

机构信息

Research Group PAIDI-TIC-168, Computational Instrumentation and Industrial Electronics (ICEI), University of Cadiz, ETSI of Algeciras, Av. Ramonn Puyol S/N, Algeciras, 11202 Cadiz, Spain.

出版信息

Sensors (Basel). 2022 Apr 11;22(8):2928. doi: 10.3390/s22082928.

Abstract

Cloud-induced photovoltaic variability can affect grid stability and power quality, especially in electricity systems with high penetration levels. The availability of irradiance field forecasts in the scale of seconds and meters is fundamental for an adequate control of photovoltaic systems in order to minimize their impact on distribution networks. Irradiance sensor networks have proved to be efficient tools for supporting these forecasts, but the costs of monitoring systems with the required specifications are economically justified only for large plants and research purposes. This study deals with the design and test of a wireless irradiance sensor network as an adaptable operational solution for photovoltaic systems capable of meeting the measurement specifications necessary for capturing the clouds passage. The network was based on WiFi, comprised 16 pyranometers, and proved to be stable at sampling periods up to 25 ms, providing detailed spatial representations of the irradiance field and its evolution. As a result, the developed network was capable of achieving comparable specifications to research wired irradiance monitoring network with the advantages in costs and flexibility of the wireless technology, thus constituting a valuable tool for supporting nowcasting systems for photovoltaic management and control.

摘要

云致光伏变化会影响电网稳定性和电能质量,尤其是在高渗透率的电力系统中。在秒级和米级尺度上提供辐照度场预测,对于充分控制光伏系统至关重要,可将其对配电网的影响降至最低。辐照度传感器网络已被证明是支持这些预测的有效工具,但具有所需规格的监测系统的成本仅在大型工厂和研究目的方面具有经济合理性。本研究涉及设计和测试一种无线辐照度传感器网络,作为一种可适应的操作解决方案,用于光伏系统,能够满足捕捉云通过所需的测量规格。该网络基于 WiFi,由 16 个总辐射表组成,在采样周期长达 25 毫秒时表现稳定,提供了辐照度场及其演变的详细空间表示。结果表明,所开发的网络能够达到与研究有线辐照度监测网络相当的规格,具有无线技术在成本和灵活性方面的优势,因此是支持光伏管理和控制的临近预报系统的有价值工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab12/9031206/44908fee59b1/sensors-22-02928-g001.jpg

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