智能配电网双模通信节点优化部署方案OA

Dual-mode communication technology,which integrates Power Line Communication(PLC)and micro-power wireless communication,has garnered significant attention for its ability to effec-tively mitigate communication interruptions caused by power line interference in smart distribution grids.To address the high deployment costs associated with micro-power wireless communication modules during the large-scale application of dual-mode communication technologies,this paper pro-poses an optimal deployment method for dual-mode communication nodes under constrained costs.First,a dual-tree network topology for smart distribution grids is constructed,and an optimal deploy-ment scheme for dual-mode nodes is designed.Then,an optimization problem is formulated with the objective of minimizing the weighted sum of the signal attenuation rate and deployment costs.Finally,to solve this multi-constrained mixed-integer programming problem,it is decomposed into two sce-narios for separate resolution:one with a fixed number of deployed dual-mode devices,the Deep De-terministic Policy Gradient(DDPG)algorithm is employed to optimize the deployment locations of the wireless communication modules.For the scenario with an unfixed optimal cost,a Dynamic Program-ming(DP)algorithm is adopted to optimize both the quantity and specific deployment locations of the dual-mode modules.Research results indicate that when the number of deployed dual-mode nodes is fixed,system performance degrades as the distance from ordinary and relay nodes to the concentrator increases.However,the DDPG-based deployment scheme consistently outperforms baseline strate-gies,including random deployment,prioritizing nodes with poor PLC performance,and prioritizing nodes with superior wireless performance.Furthermore,compared to the random deployment and re-lay node-first schemes,the DP-based scheme reduces the objective function value by 6.8％and 3.8％,respectively,demonstrating the effectiveness of the proposed approach in balancing deploy-ment costs and system performance.