Typical scenario clustering method and application of oilfield microenergy grid

The data curve in typical oil field scenarios is the most representative and the basis for system optimization scheduling. Therefore, a typical scene selection method of load-PV based on ordered clustering and load-wind speed based on K-means clustering is proposed in the paper. In view of the strong time sequence of electric load and PV intensity, the ordered clustering method is used to cluster electric load and light samples. Aiming at the randomness of load and wind speed, K-means method is adopted to cluster. The cluster scenarios of different data are combined, and the typical scenarios of oilfield micro-energy grid system including load, wind speed and PV data are obtained.