Abstract: Wind power and photovoltaic power generation have become important sources of clean energy in the world. However, the massive amount of strong fluctuation and high noise power time series data generated by them brings a huge burden to the data storage and communication transmission of smart distribution network. This paper proposes an efficient time series data compression method for time series data generated by wind power and photovoltaic power generation, including timestamp compression algorithm, floating point quantization algorithm and floating point lossy compression algorithm. Finally, through the comparison experiment with the traditional compression algorithms on the public data set, it is verified that the proposed method can effectively compress the power time series data. Compared with the traditional algorithm, the performance indicators such as compression ratio and mean square error have been improved.