A Data-Upload Strategy of Measurements for Lean Management in Distribution Network Under Certain Communication Cost

Distribution system lean management (DSLM) is becoming an essential element of many distribution applications, the distribution network measurements are serving as the core data foundation of numerous DSLM. Considering the communication cost, the most valuable measurement data should be selected and uploaded. This paper proposes a data-upload strategy (DUS) based on distribution system state estimation (DSSE), which considers both the network observability and the mesurements' contribution. The measurements are first sorted, and then the most valuable data set is selected by using a particle swarm optimization (PSO) and a greedy algorithm. The method is tested on IEEE 4 node test feeder, different data sets are studied under several given communication cost constraints, its results are always in the top 5% group, and the DUS' result is also used on a period of time containing multipy time points, and is shown to have good stability. The proposed method is also applied to a IEEE 123 test system and works well.