摘 要
随着现代电力电子技术的快速发展，非线性负荷在电力系统中的广泛应用导致谐波污染问题日益严重，这对电能质量、设备运行效率及电网稳定性构成了显著威胁。为有效应对这一挑战，本文针对电力系统中谐波的检测与抑制方法展开深入研究，旨在提出一种高效、精确且适应性强的技术方案以改善电能质量。研究首先分析了谐波产生的机理及其对电力系统的具体影响，并基于此构建了一种改进型快速傅里叶变换（FFT）算法用于谐波检测，该算法通过优化频率分辨率和计算效率，在复杂工况下仍能实现高精度的谐波成分分离。同时，为提升抑制效果，本文设计了一种基于自适应神经模糊推理系统（ANFIS）的有源电力滤波器控制策略，该策略能够根据实时负载特性动态调整补偿参数，从而显著提高谐波抑制性能。实验结果表明，所提出的检测算法较传统方法在准确性和速度上均有明显提升，而抑制策略则实现了更高的补偿精度和更优的动态响应特性。此外，本文方法在多场景下的验证进一步证明了其良好的适应性和鲁棒性。总体而言，本研究不仅为谐波治理提供了新的思路，还为电力系统的智能化发展奠定了重要基础，具有较高的理论价值和实际应用潜力。
关键词：谐波检测；谐波抑制；改进型快速傅里叶变换；自适应神经模糊推理系统；有源电力滤波器
Abstract
With the rapid development of modern power electronics technology, the widespread application of nonlinear loads in power systems has led to increasingly severe harmonic pollution, which poses significant threats to power quality, equipment operational efficiency, and grid stability. To effectively address this challenge, this paper conducts an in-depth study on harmonic detection and suppression methods in power systems, aiming to propose a highly efficient, precise, and adaptable technical solution to improve power quality. The research first analyzes the mechanism of harmonic generation and its specific impacts on power systems, and subsequently develops an improved fast Fourier transform (FFT) algorithm for harmonic detection. By optimizing frequency resolution and computational efficiency, this algorithm achieves high-precision harmonic component separation even under complex operating conditions. Furthermore, to enhance suppression performance, an adaptive neuro-fuzzy inference system (ANFIS)-based control strategy for active power filters is designed. This strategy dynamically adjusts compensation parameters according to real-time load characteristics, thereby significantly improving harmonic suppression capabilities. Experimental results demonstrate that the proposed detection algorithm outperforms traditional methods in terms of accuracy and speed, while the suppression strategy achieves higher compensation precision and superior dynamic response characteristics. Additionally, validations across multiple scenarios further confirm the excellent adaptability and robustness of the proposed method. Overall, this study not only provides new insights into harmonic mitigation but also lays an important foundation for the intelligent development of power systems, showcasing substantial theoretical value and practical application potential..
Key Words：Harmonic Detection；Harmonic Suppression；Improved Fast Fourier Transform；Adaptive Neuro Fuzzy Inference System；Active Power Filter
目 录
摘 要 I
Abstract II
第1章 绪论 1
1.1 电力系统谐波研究背景与意义 1
1.2 国内外谐波检测与抑制研究现状 1
1.3 本文研究方法与技术路线 2
第2章 谐波检测方法分析 3
2.1 谐波检测的基本原理与要求 3
2.2 傅里叶变换在谐波检测中的应用 3
2.3 小波变换的谐波检测特性研究 4
2.4 新型谐波检测算法对比与选择 4
第3章 谐波抑制技术研究 6
3.1 谐波抑制的技术分类与特点 6
3.2 有源滤波器在谐波抑制中的应用 6
3.3 无源滤波器的设计与优化方法 7
3.4 混合滤波技术的研究与实现 7
第4章 谐波检测与抑制的实际应用 9
4.1 实际电力系统中的谐波问题分析 9
4.2 谐波检测方案的工程实现与验证 9
4.3 谐波抑制策略的效果评估与改进 10
4.4 典型案例分析与经验总结 10
结 论 11
参考文献 12
致 谢 13
随着现代电力电子技术的快速发展，非线性负荷在电力系统中的广泛应用导致谐波污染问题日益严重，这对电能质量、设备运行效率及电网稳定性构成了显著威胁。为有效应对这一挑战，本文针对电力系统中谐波的检测与抑制方法展开深入研究，旨在提出一种高效、精确且适应性强的技术方案以改善电能质量。研究首先分析了谐波产生的机理及其对电力系统的具体影响，并基于此构建了一种改进型快速傅里叶变换（FFT）算法用于谐波检测，该算法通过优化频率分辨率和计算效率，在复杂工况下仍能实现高精度的谐波成分分离。同时，为提升抑制效果，本文设计了一种基于自适应神经模糊推理系统（ANFIS）的有源电力滤波器控制策略，该策略能够根据实时负载特性动态调整补偿参数，从而显著提高谐波抑制性能。实验结果表明，所提出的检测算法较传统方法在准确性和速度上均有明显提升，而抑制策略则实现了更高的补偿精度和更优的动态响应特性。此外，本文方法在多场景下的验证进一步证明了其良好的适应性和鲁棒性。总体而言，本研究不仅为谐波治理提供了新的思路，还为电力系统的智能化发展奠定了重要基础，具有较高的理论价值和实际应用潜力。
关键词：谐波检测；谐波抑制；改进型快速傅里叶变换；自适应神经模糊推理系统；有源电力滤波器
Abstract
With the rapid development of modern power electronics technology, the widespread application of nonlinear loads in power systems has led to increasingly severe harmonic pollution, which poses significant threats to power quality, equipment operational efficiency, and grid stability. To effectively address this challenge, this paper conducts an in-depth study on harmonic detection and suppression methods in power systems, aiming to propose a highly efficient, precise, and adaptable technical solution to improve power quality. The research first analyzes the mechanism of harmonic generation and its specific impacts on power systems, and subsequently develops an improved fast Fourier transform (FFT) algorithm for harmonic detection. By optimizing frequency resolution and computational efficiency, this algorithm achieves high-precision harmonic component separation even under complex operating conditions. Furthermore, to enhance suppression performance, an adaptive neuro-fuzzy inference system (ANFIS)-based control strategy for active power filters is designed. This strategy dynamically adjusts compensation parameters according to real-time load characteristics, thereby significantly improving harmonic suppression capabilities. Experimental results demonstrate that the proposed detection algorithm outperforms traditional methods in terms of accuracy and speed, while the suppression strategy achieves higher compensation precision and superior dynamic response characteristics. Additionally, validations across multiple scenarios further confirm the excellent adaptability and robustness of the proposed method. Overall, this study not only provides new insights into harmonic mitigation but also lays an important foundation for the intelligent development of power systems, showcasing substantial theoretical value and practical application potential..
Key Words：Harmonic Detection；Harmonic Suppression；Improved Fast Fourier Transform；Adaptive Neuro Fuzzy Inference System；Active Power Filter
目 录
摘 要 I
Abstract II
第1章 绪论 1
1.1 电力系统谐波研究背景与意义 1
1.2 国内外谐波检测与抑制研究现状 1
1.3 本文研究方法与技术路线 2
第2章 谐波检测方法分析 3
2.1 谐波检测的基本原理与要求 3
2.2 傅里叶变换在谐波检测中的应用 3
2.3 小波变换的谐波检测特性研究 4
2.4 新型谐波检测算法对比与选择 4
第3章 谐波抑制技术研究 6
3.1 谐波抑制的技术分类与特点 6
3.2 有源滤波器在谐波抑制中的应用 6
3.3 无源滤波器的设计与优化方法 7
3.4 混合滤波技术的研究与实现 7
第4章 谐波检测与抑制的实际应用 9
4.1 实际电力系统中的谐波问题分析 9
4.2 谐波检测方案的工程实现与验证 9
4.3 谐波抑制策略的效果评估与改进 10
4.4 典型案例分析与经验总结 10
结 论 11
参考文献 12
致 谢 13
