A monitoring scheme for Beidou integrated smart grid based on improved genetic algorithm

Beidou-Satellite integrated smart grids can transmit monitoring data from sensor nodes to satellite communication nodes, enabling real-time, long-distance, and unattended critical target security assurance for the power grid. The k-coverage and m- connectivity problem for multi-sensor nodes often can be solved using heuristic algorithms. To avoid the problem of high computational overhead in large-scale optimization that traditional genetic algorithms often encounter, an improved genetic algorithm (XGA) is proposed. A k-dimensional tree (KDT) is pre-built for electric towers and sensor nodes, and the KDF results are reused in the initialization stage of chromosomes. Chromosomes are guided by the proximity of sensor nodes around electric towers for initialization, allowing chromosomes to be closer to the optimal solution and accelerating the convergence of the algorithm. Simulation experiments show that the XGA algorithm has higher performance than traditional GA algorithms in both fixed and mobile scenarios in Satellite integrated smart grid.