基于人工神经网络UPQC的并网光伏电网电能质量提升评估

IF 0.6 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Phani Kumar Chittala, E. Elanchezhian, S. Pragaspathy, S. Subramanian
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引用次数: 0

摘要

微电网是最近十年的术语,超越了与公共电网和公用事业电网相关的长期问题。在可再生能源中,太阳能光伏发电装置由于其巨大的可用性和技术上的轻松操作特点而获得了更大的重要性。相反,它提供无污染的电力,也许在大多数情况下可靠性是不稳定的。文献研究积累了上述挫折,并提出了无波动和可控的电力输出标准质量。本研究的目的是通过基于人工神经网络的UPQC对并网光伏(PV)网络的电能质量增强进行评估。这种提议的方法背后的新颖想法是UPQC组件,它故意调节和控制电力系统,以实现更高水平的电力质量,最终满足最近的IEEE标准。本研究通过用多层前馈型人工神经网络控制器取代传统的PI控制器来调节串联有源滤波器的电流,从而提高了UPQC在微网单元中的性能。此外,建立了神经网络控制器的训练算法,并在MATLAB/Simulink平台上进行了训练和仿真。提出了基于人工神经网络的UPQC,以缓解电压起伏、谐波失真、电压补偿所需时间和功率因数等电能质量挑战。因此,UPQC可以丰富各电力框架内共耦合点的电力传输标准。最后,通过仿真验证了基于人工神经网络的UPQC系统对并网光伏网络的运行效果。为了展示所提出的拓扑结构的丰富性能,与基于PI控制器的UPQC进行了比较分析,结果与理论讨论一致。此外,基于人工神经网络的方法在凹陷和膨胀条件下分别减少了恢复时间和THD。在本铰接式工作中,光伏发电系统网络采用DC-DC变换器和三相逆变器进行并网。峰值功率提取是通过采用增量电导算法的DC-DC变换器来保证的。通过MATLAB/Simulink平台对两种upqc进行了非恒定非线性负荷分析和实验,对上述指标进行了研究,并在工作区域内进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of Power Quality Enhancement in a Grid-Tied PV Network via ANN-based UPQC
Microgrid is the recent decade terminology that surpasses the long-run issues associated with the public and utility grids. Among the renewable energy sources, solar PV units have gained greater importance owing to their huge potential availability and laidback operating characteristics on technological grounds. Conversely, it offers pollution-free electricity and perhaps the dependability is volatile in most situations. The literature study accumulates the foresaid setback and presents the fluctuation-less and controlled standard quality of power outputs. The aim of this particular research is to propose an assessment of Power Quality enhancement in a Grid-tied photovoltaic (PV) network via ANN-based UPQC. The novel idea behind this proposed approach is the UPQC component which deliberately regulates and controls the power system to achieve higher levels of power quality, ultimately meeting the recent IEEE standards. This particular research enhances the performances of UPQC employed in the microgrid unit by replacing the traditional PI controller with a multi-layered feed-forward-type ANN controller for the current regulation of the series active filter. Additionally, a training algorithm for the ANN controller is built, trained and simulated via MATLAB/Simulink platform. The ANN-based UPQC is proposed to alleviate the power quality challenges like sag and swell in voltage, harmonic distortion, the time required for voltage compensation, and power factor. Therefore, UPQC is equipped to enrich the standard of power transfer at the point of common coupling inside the power frameworks, respectively. Finally, the simulation results are presented to validate the operation of the grid-tied PV network via an ANN-based UPQC system. To show the enriched performance of the proposed topology, a comparative analysis is made with PI controller-based UPQC, and outcomes infer to be in agreement with the theoretical discussions. Also, the ANN-based proposed approach reduces the restoration time and THD as well under both sag and swell conditions, respectively. In this articulated work, a PV power system network with a DC-DC converter and three-phase inverter is employed for grid integration. The peak power extraction is ensured via a DC-DC converter with an incremental conductance algorithm. Both UPQCs are analysed and experimented via MATLAB/Simulink platform with inconstant nonlinear loads to investigate the indices mentioned above and corroborate the same within the operating regions.
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来源期刊
Recent Advances in Electrical & Electronic Engineering
Recent Advances in Electrical & Electronic Engineering ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
1.70
自引率
16.70%
发文量
101
期刊介绍: Recent Advances in Electrical & Electronic Engineering publishes full-length/mini reviews and research articles, guest edited thematic issues on electrical and electronic engineering and applications. The journal also covers research in fast emerging applications of electrical power supply, electrical systems, power transmission, electromagnetism, motor control process and technologies involved and related to electrical and electronic engineering. The journal is essential reading for all researchers in electrical and electronic engineering science.
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