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Differential Fast Fourier Transform Based Recovery Algorithm for Electricity Metering Data
by
Kong, Xiangyong
, Duan, Yuwei
, Xu, Yukun
, Xu, Zihan
, Shi, Desheng
, Liu, Chang
in
Algorithms
/ Data recovery
/ Electricity consumption
/ Fast Fourier transformations
/ Fourier transform
/ missing metering data
/ proportional scaling method
/ Time domain analysis
/ Time of use electricity pricing
/ total electricity consumption data
/ Zero-padding
2024
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Differential Fast Fourier Transform Based Recovery Algorithm for Electricity Metering Data
by
Kong, Xiangyong
, Duan, Yuwei
, Xu, Yukun
, Xu, Zihan
, Shi, Desheng
, Liu, Chang
in
Algorithms
/ Data recovery
/ Electricity consumption
/ Fast Fourier transformations
/ Fourier transform
/ missing metering data
/ proportional scaling method
/ Time domain analysis
/ Time of use electricity pricing
/ total electricity consumption data
/ Zero-padding
2024
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Do you wish to request the book?
Differential Fast Fourier Transform Based Recovery Algorithm for Electricity Metering Data
by
Kong, Xiangyong
, Duan, Yuwei
, Xu, Yukun
, Xu, Zihan
, Shi, Desheng
, Liu, Chang
in
Algorithms
/ Data recovery
/ Electricity consumption
/ Fast Fourier transformations
/ Fourier transform
/ missing metering data
/ proportional scaling method
/ Time domain analysis
/ Time of use electricity pricing
/ total electricity consumption data
/ Zero-padding
2024
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Differential Fast Fourier Transform Based Recovery Algorithm for Electricity Metering Data
Journal Article
Differential Fast Fourier Transform Based Recovery Algorithm for Electricity Metering Data
2024
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Overview
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.
Publisher
IOP Publishing
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