Smart Grid Data Compression of Power Quality Events using Wavelet Transform

Smart grids typically incorporate a communication networking layer onto the electric power grid to exchange the data and the information between the intelligent electronic devices and the supervisory control and data acquisition (SCADA). The smart grid monitoring and control requires the acquisition and the transmission of a large volume of data over such communication networks. This process sets new requirements for the existing data communication networks within the smart grid regarding the network transmission capacity and the data storage. Data compression is an effective mean to compress the power quality (PQ) data and hence saving the cost of data storage while meeting the communication network transmission capacity limits. The previous work on PQ data compression uses wavelets multiresolution signal decomposition into various decomposition levels. Thresholding is then applied on each wavelet decomposition level to capture the features needed for signal reconstruction. The goodness of compression is significantly affected by the choice of the wavelet basic function as well as the choice of the number of decomposition levels. This paper looks into identifying the most suitable wavelet basic function and the suitable number of wavelet decomposition level to achieve high compression of PQ disturbances. The study considered 80 wavelets and 4 categories of PQ disturbances such as sag, swell, interruption and notches. The results have been presented and the conclusions were drawn.