US 12,284,585 B2
Cyber-physical integrated restoration method and system for distribution systems based on emergency mobile communications
Chen Chen, Xi'an (CN); Ruihuan Liu, Xiantao (CN); Zhigang Ye, Nanjing (CN); Fei Liu, Daqing (CN); and Zhaohong Bie, Xi'an (CN)
Assigned to Xi'an Jiaotong University, Xi'an (CN)
Filed by Xi'an Jiaotong University, Xi'an (CN)
Filed on Oct. 24, 2022, as Appl. No. 17/972,198.
Claims priority of application No. 202111258594.2 (CN), filed on Oct. 27, 2021.
Prior Publication US 2023/0130719 A1, Apr. 27, 2023
Int. Cl. H04W 4/90 (2018.01); H04W 4/40 (2018.01)
CPC H04W 4/90 (2018.02) [H04W 4/40 (2018.02)] 7 Claims
OG exemplary drawing
 
1. A cooperative cyber-physical distribution system restoration method based on emergency mobile communications, comprising:
S1, obtaining data of damaged and faulted lines of a distribution system, and determining locations of line switches and locations of working sites for mobile communication vehicles;
S2, modeling an optimal path for the mobile communication vehicles based on the determined locations of the working sites for the mobile communication vehicles obtained by S1, and obtaining a routing model of the mobile communication vehicles; wherein the routing model of the mobile communication vehicles comprises: moving path constraints and moving time constraints of the mobile communication vehicles, and each of the mobile communication vehicles is represented by a communication agent (CA);
S3, modeling repair crews dispatch to repair fault components based on the data obtained by S1, and obtaining a dispatch model of the repair crews; wherein the dispatch model of the repair crews comprises: travel path constraints and travel time constraints of the repair crews, and the repair crews are represented by a repair agent (RA);
S4, modeling a distribution system load restoration based on a topology of the distribution system and the determined locations of the line switches obtained by S1, introducing a concept of an electric agent (EA) and establishing a relationship between a path optimization problem of the electric agent and a distribution system restoration problem through routing tables and arrival time vectors, and obtaining a restoration model of the distribution system; wherein the restoration model of the distribution system comprises: electrical path constraints and electrical time constraints of the distribution system, and an energy flow path of the distribution system is represented by the electric agent (EA);
S5, determining dependency relationships among repair crew scheduling, mobile communication vehicle scheduling and distribution system sequence restoration, based on the moving path constraints in S2, the moving time constraints in S2, the travel path constraints in S3, the travel time constraints in S3, the electrical path constraints in S4 and the electrical time constraints in S4; wherein the dependency relationships comprise: interdependence constraints between the repair crew scheduling and the distribution system sequence restoration, and interdependence constraints between the mobile communication vehicle scheduling and the distribution system sequence restoration;
S6, considering components and system operation constraints for the distribution system, regarding minimizing a total weighted unserved energy, a total repair time and a use time cost of the mobile communication vehicles as a goal, building a comprehensive optimization model of coordination between distribution system restoration and emergency mobile communication based on a variable time step method, according to the moving path constraints in S2, the moving time constraints in S2, the travel path constraints in S3, the travel time constraints in S3, the electrical path constraints in S4, the electrical time constraints in S4, the interdependence constraints between the repair crew scheduling and the distribution system sequence restoration in S5, and the interdependence constraints between the mobile communication vehicle scheduling and the distribution system sequence restoration in S5; and solving the comprehensive optimization model to obtain results of cooperative cyber-physical distribution system restoration; and
S7, restoring communication paths and loads of the distribution system after disasters based on the results.