基于改进型 SVSF 的配电网络动态状态估计新方法(考虑光伏功率预测

IF 2.6 4区 工程技术 Q3 ENERGY & FUELS Frontiers in Energy Research Pub Date : 2024-08-06 DOI:10.3389/fenrg.2024.1421555
Huiqiang Zhi, Xiao Chang, Jinhao Wang, Rui Mao, Rui Fan, Tengxin Wang, Jinge Song, Guisheng Xiao
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引用次数: 0

摘要

可再生能源接入配电网带来的波动使得配电网动态过程的状态空间模型难以准确描述,而状态空间模型是卡尔曼滤波等现有动态状态估计方法的基础。不准确的状态空间模型直接导致了动态状态估计结果的误差。本文提出了一种新的动态状态估计方法,通过在建立配电网状态空间模型时考虑光伏功率预测,可以减轻可再生能源波动的影响。首先,本文提出的方法在建立配电网状态空间模型时考虑了光伏功率预测,从而减轻了可再生能源波动的影响。其次,引入 SVSF 滤波器以实现噪声下更精确的估计。基于 MATLAB 仿真进行了案例研究和评估。结果证明,与现有的卡尔曼滤波器相比,带有光伏功率预测的平滑变结构滤波器在配电网波动下具有更好的动态状态估计效果。
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A new dynamic state estimation method for distribution networks based on modified SVSF considering photovoltaic power prediction
The fluctuations brought by the renewable energy access to the distribution network make it difficult to accurately describe the state space model of the distribution network’s dynamic process, which is the basis of the existing dynamic state estimation methods such as the Kalman filter. The inaccurate state space model directly causes an error of dynamic state estimation results. This paper proposed a new dynamic state estimation method which can mitigates the impact of renewable energy fluctuation by considering PV power prediction in establishing distribution network state space model. Firstly, the proposed method mitigates the impact of renewable energy fluctuation by considering PV power prediction in establishing distribution network state space model. Secondly, SVSF filter is introduced to achieve more accurate estimation under noise. The case study and evaluations are carried out based on MATLAB simulation. The results prove that the smooth variable structure filter with photovoltaic power prediction has a better dynamic state estimation effect under the fluctuation of the distribution network compared with the existing Kalman filter.
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来源期刊
Frontiers in Energy Research
Frontiers in Energy Research Economics, Econometrics and Finance-Economics and Econometrics
CiteScore
3.90
自引率
11.80%
发文量
1727
审稿时长
12 weeks
期刊介绍: Frontiers in Energy Research makes use of the unique Frontiers platform for open-access publishing and research networking for scientists, which provides an equal opportunity to seek, share and create knowledge. The mission of Frontiers is to place publishing back in the hands of working scientists and to promote an interactive, fair, and efficient review process. Articles are peer-reviewed according to the Frontiers review guidelines, which evaluate manuscripts on objective editorial criteria
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