基于粒子群算法的变换器并网系统振荡初期交流信号幅频调制特征解调方法OA
Demodulation Method for Amplitude-Frequency Modulation Characteristics of AC Signals in Initial Stage of Converter Interfaced System Oscillation Based on Particle Swarm Optimization Algorithm
针对新能源并网比例不断提升导致的电力系统振荡问题,提出了一种基于粒子群算法的电力系统振荡信号幅频调制特征解调方法.首先,从交流电气量形成与演化的物理机制出发,明确了振荡信号在扰动下的约束关系,揭示了其幅值与频率随时间演化的调制规律.与传统基于傅里叶分解或小波分析的谐波叠加方法不同,振荡信号并非由静态谐波叠加而成,而是受系统动态闭环作用形成的连续调制过程,更具物理意义.在此基础上,设计了基于粒子群算法的幅频调制特征提取方法.以拟合波形与实际波形偏差为目标,提取决定振荡过程的幅频调制参数.仿真结果表明,该方法能够准确反映典型的变换器并网系统的振荡规律,拟合波形与原始信号高度一致,动模实验进一步验证了算法在实际系统中的适用性与有效性.
A particle swarm optimization algorithm based demodulation method for amplitude frequency modulation characteristics of power system oscillation signals is proposed to address the problem of power system oscillation caused by the continuous increase in the proportion of new energy grid connected.Firstly,starting from the physical mechanisms of formation and evolution of AC electri-cal quantities,the constraint relationships of oscillation signals under disturbances are clarified,revealing the modulation patterns of their amplitudes and frequencies over time.Unlike traditional harmonic superposition methods based on Fourier decomposition or wavelet analysis,this study emphasizes that oscillation signals are not formed by static harmonic superposition but rather result from a continuous modulation process shaped by the system's dynamic closed-loop action,which carries greater physical significance.On this basis,a PSO-based amplitude-frequency modulation feature extraction method is designed.By minimizing the deviation between the fitted waveform and the actual waveform,the amplitude-frequency modulation parameters that determine the oscillation process are extracted.Simulation results show that the proposed method can accurately reflect the oscillation patterns of typical converter-interfaced power systems,with the fitted waveforms highly consistent with the original signals.Dynamic model experiments further validate the applicability and effectiveness of the proposed algorithm in practical systems.
蔡百科;王思成;袁小明
华中科技大学电气与电子工程学院,武汉 430074华中科技大学电气与电子工程学院,武汉 430074华中科技大学电气与电子工程学院,武汉 430074
信息技术与安全科学
振荡过程幅频调制机制粒子群算法幅频调制特征
oscillation processamplitude-frequency modulation mechanismparticle swarm optimization algorithmamplitude-frequency modulation characteristics
《南方电网技术》 2026 (4)
65-74,95,11
国家自然科学基金资助项目(U23B600008)台达电力电子科教发展计划资助项目(DREN2024001). Supported by the National Natural Science Foundation of China(U23B600008)the Delta Power Electronics Science and Education Development Program of Delta Group(DREN2024001).
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