Construction of Operation Portraits Based on a Cloud Model for Power Distribution Networks

Abstract

With the high proportion of new energy access in power distribution networks, the operation of distribution networks becomes more uncertain and complex. The mechanism on how to extract features that embody the full perspective of the distribution network from the diverse and varying conditions is of great significance to master the operating property of distribution networks under the high proportion of new energy. This study investigates the portrait construction of power distributions. A data-driven method of portrait construction for a distribution network based on a cloud model is proposed. First, the indexes describing the operation of the medium voltage distribution network (MVDN) and low-voltage station area (LVSA) are established. By means of statistics, fuzzy label templates are provided for the indexes. Then, based on the daily monitoring power grid data, the operation index is calculated to form the collected samples, and the reverse cloud generator is used as the data-driven method to process the samples, and the fuzzy model of cloud parameter representation is obtained. Finally, the fuzzy distance between the obtained fuzzy model and the label template is calculated, and the scores of operation indexes are obtained, thus forming a portrait method of distribution network operation behavior. Taking the IEEE 33 distribution network and real distribution network as examples and taking the LVSA as an example, it is verified that this method can effectively construct the distribution network operation portrait.