Affiliations: [a] School of Materials Science and Engineering, Inner Mongolia University of Technology, Hohhot 010051, China | [b] Inner Mongolia Electric Power Research Institute, Hohhot 010020, China | [c] Inner Mongolia Regional Key Laboratory of Electrical Power Conversion, Transmission and Control, Hohhot 010081, China
Abstract: In this new round of power network development, the concept of coordinated and optimized operation of power network interconnection and smart grid “source network load” has gradually attracted attention. Based on the analysis of the impact of the flexible DC distribution network on the complex energy system with multiple data sources and large data volume under the big data platform, the coordinated dispatching of the source and load of the big data flexible DC distribution network is studied. Therefore, a source-load matching index that can evaluate the impact of different types of loads on the stability of the flexible DC grid is constructed and incorporated into the load recovery optimization model. First, use the scene reduction method to process all generated scenes; next, take the reduction technology and the scene generation method into account of the uncertainty caused by the prediction error and incorporate them into the multi-objective function optimization model; finally, the membership function of fuzzy numbers is used to model uncertainty. So as to construct a load recovery model that can coordinate the load recovery amount, importance and system dynamic response. The actual meaning of the matching index is explained through model solving and actual case analysis.
Keywords: Distribution network, source-load coordination, big data, flexible response, fuzzy model
