Golomb-Rice Compression for High-Resolution Interval Meter Data
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Solution Overview
Problem
Current smart metering systems face challenges in efficiently compressing electric power consumption data, limiting their ability to support more meters, more frequent readings, or higher resolution data without significant increases in data throughput.
Innovation Solution
A data compression method utilizing Golomb-Rice coding with pre-conditioning and variable parameter encoding, tailored to the exponential probability distribution of energy consumption data, to achieve efficient data transmission while minimizing computational complexity and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If data compression is applied to energy consumption data, then the amount of data to be transmitted is reduced, but the computational complexity increases
Solution Approach 1:
The patent applies Golomb-Rice coding with a specifically optimized parameter (k=3) that balances compression efficiency with computational simplicity. This parameter change allows the system to achieve significant data reduction while maintaining manageable computational requirements for encoding and decoding operations.
Solution Approach 2:
The patent segments the energy consumption data into fixed-size blocks (e.g., 16 or 32 values per block) before applying compression. This segmentation enables efficient processing of large datasets by breaking them into manageable units, reducing the computational burden on individual encoding operations while maintaining overall compression effectiveness.
2Quantity of substance
If more meters are supported in the AMI system, then the data capacity increases, but the power consumption increases
Solution Approach 1:
By optimizing the Golomb-Rice parameter and implementing efficient encoding algorithms, the patent reduces the bits required per data value, directly lowering the power consumption for transmitting data from multiple meters across the AMI network.
Solution Approach 2:
The patent performs pre-conditioning of data (such as differential encoding or prediction) before applying Golomb-Rice coding. This preliminary processing step improves compression efficiency, thereby reducing the total power consumption required to transmit data from expanded numbers of meters.
3Measurement precision
If higher resolution interval data is transmitted, then the measurement precision increases, but the data transmission volume increases
Solution Approach 1:
The patent maintains high measurement precision by applying Golomb-Rice coding that is particularly effective for the statistical distribution of energy consumption data. The coding parameter is optimized to preserve fine-grained resolution information while achieving maximum compression, allowing high-resolution data to be transmitted with reduced volume.
4Productivity
If more frequent readings are taken, then the productivity increases, but the data transmission volume increases
Solution Approach 1:
The patent optimizes the Golomb-Rice coding parameter to efficiently compress the increased volume of data generated by more frequent readings. The parameter selection and pre-conditioning techniques maintain compression effectiveness even as reading frequency increases, allowing higher productivity without proportional increases in transmission volume.
Data Source
AI summary
A method of data compression for use in a data communication's system for an electrical utility or the like to affect the most efficient transfer of data. The data is first formed into a forming a block (B). A parameter (M) is selected from among a group of parameters. Each data value in the block is divided by the selected parameter to produce, for each data value, a quotient (q=└n/M┘) and a remainder (r=n−qM). The quotient of each data value is encoded using unary coding in which the value for the quotient is encoded by transmitting an appropriate number of zeroes followed by a one. The remainder of each data value is encoded using binary encoding, and the resultant encoded block of data is then transmitted. The data values comprising the block of data are positive integer values and the encoding employs a Golomb-Rice code defined by a positive integer parameter.