2 results about "Ultra dense" patented technology

The application provides a 5G base station virtual power plant feasible region aggregation method based on coupling degree clustering, belongs to the flexible resource aggregation field, and comprises the following steps: a super-dense heterogeneous 5G base station network model containing macro base stations and micro base stations is constructed, and base station positions, user distribution, channel parameters and service quality constraints are obtained; the base station coupling degree concept is proposed; the coupling degree is used as the similarity measurement, the greedy clustering idea is adopted, the k-means++ optimization initial value is used as the initial clustering center, the remaining base stations are sequentially grouped into the cluster with the maximum coupling degree, the clustering is iterated, and the dynamic grouping is realized according to the flow prediction change; for each base station cluster, the base station communication energy consumption and energy storage resources that can be reduced are combined, the multi-objective optimization is used to solve the adjustable power internal distribution feasibility, and the cluster-level feasible region is obtained. The application significantly improves the accuracy and efficiency of the 5G base station virtual power plant feasible region aggregation, and provides key technical support for the large-scale participation of 5G base stations in the power system auxiliary service market.

The present application relates to the field of space exploration technology, and more particularly to a method, apparatus, electronic device, and medium for correcting gravity wave drag at the mesosphere. The method comprises: obtaining an ultradense gravity wave momentum flux (MF) of a target step length; fitting the ultradense MF of the target step length to obtain the gravity wave drag and residual at the mesosphere, estimating a first error of the gravity wave drag and a confidence interval of the residual under a target confidence level; removing outliers from the ultradense MF based on the confidence interval of the residual, fitting the ultradense MF after removing the outliers to obtain a corrected gravity wave drag at the mesosphere, estimating a second error of the gravity wave drag under a target confidence level, and calculating an error reduction rate based on the first error and the second error. This method solves the problem that gravity wave drag obtained based on meteor radar observations often has systematically large values ​​and, under the same confidence level, its error interval is also more divergent.