Accurate electricity data is the foundation for time-of-use pricing. However, for various reasons, some data may be incorrect or lost. To address this issue, this paper proposes a recovery algorithm based on differential Fourier transform to restore missing metering data. First, the total electricity consumption data is differentiated and up-sampled as the interpolation sequence. Next, a Fourier transform is performed on the interpolated sequence to convert it from the time domain to the frequency domain. Zero-padding is applied in the high-frequency regions to enhance time-domain resolution. Then, the sequence is converted back to the time domain through an inverse Fourier transform, yielding the missing power consumption sequence. Finally, a proportional scaling method is applied to satisfy the non-decreasing characteristic. Numerical experiments demonstrate that the method proposed in this paper exhibits high reliability and accuracy in restoring missing electricity data.