随着非线性负荷大量接入电力系统，电网信号严重畸变，畸变影响下电能准确计量已成为电能计量领域亟待解决的问题。针对非线性冲击负荷大量接入电网导致的电能计量问题，提出一种基于自适应小波基的脉冲畸变信号有功电能计量方法。首先，分析脉冲畸变信号的特征并建立其数学表达式。其次，基于信号分解到下一级子尺度空间最大化原则提出脉冲畸变下的小波基构造方法，结合粒子群优化（particle swarm optimization, PSO）算法构建了自适应小波基。然后，采用该自适应小波基对脉冲畸变信号进行分解与重构，实现有功电能分频带计量。最后，搭建电能计量实验平台，以电动汽车充电时的三种不同畸变工况为例，对算法进行仿真和实验对比。结果表明：该方法与通用小波基、快速傅里叶变换（fast Fourier transform, FFT）、短时傅里叶变换（short-time Fourier transform, STFT）、广义S变换相比具有显著的有效性与准确性，计量精度满足电能表计量1级误差要求，为新型电能表的设计提供了新的解决方案。

With the extensive integration of nonlinear loads into power systems, severe waveform distortion of grid signals has made accurate energy metering under distorted conditions a critical challenge in power measurement technology. To address the metering inaccuracies caused by large-scale integration of nonlinear impact loads, an active power energy metering method was proposed based on adaptive wavelet basis for pulse-distorted signals. Firstly, the characteristic analysis and mathematical modeling of pulse-distorted signals were conducted. Subsequently, a wavelet basis construction method was developed under pulse distortion by maximizing signal decomposition energy in the next-level subspace, combined with particle swarm optimization (PSO) algorithm to establish the adaptive wavelet basis. The proposed basis was then employed to decompose and reconstruct pulse-distorted signals, enabling frequency-band-specific active power measurement. Finally, an experimental metering platform was established to validate the algorithm through simulations and comparative tests under three typical distortion scenarios during electric vehicle charging. Results demonstrate that the proposed method significantly outperforms conventional wavelet bases, fast Fourier transform (FFT), short-time Fourier transform(STFT), and Generalized S-transform in both effectiveness and accuracy. The achieved measurement precision meets class 1 error requirements for electricity meters, providing a novel solution for next-generation meter design.