引用本文: | 熊小萍,刘 瑞,蔡义明.计及节点重要度协同知识模型的电力通信QoS路由策略[J].电力系统保护与控制,2023,51(6):45-53.[点击复制] |
XIONG Xiaoping,LIU Rui,CAI Yiming.Power communication QoS routing strategy considering node importance degree and knowledge model[J].Power System Protection and Control,2023,51(6):45-53[点击复制] |
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摘要: |
“双碳规划”下电网面临形态和功能的集约升级,区域内节点化、模块化特征愈加突出,亟需研究一种计及节点特性的路由算法,来保障通信网支撑能力。首先,依托节点的电网影响度和拓扑关系定义了重要度参数。其次,从状态转移、自适应搜索收敛控制等方面将重要度嵌入策略模型,引导路由优化方向。然后,引进参数知识模型挖掘优化问题的相关知识,协同重要度指导后续优化过程,降低了蚁群系统的参数敏感性。最后,通过仿真证明在满足服务质量(quality of service, QoS)前提下,策略模型计及节点重要度的知识型路由能快速收敛,并提供了良好而稳定的主备用路由性能。 |
关键词: 电力通信网 节点重要度 QoS路由策略 知识模型 群智能优化 |
DOI:10.19783/j.cnki.pspc.220995 |
投稿时间:2022-06-29修订日期:2022-10-26 |
基金项目:国家自然科学基金项目资助(51867004);广西自治区重点研发计划项目资助(桂科AB22035033) |
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Power communication QoS routing strategy considering node importance degree and knowledge model |
XIONG Xiaoping,LIU Rui,CAI Yiming |
(School of Electrical Engineering, Guangxi University, Nanning 530004, China) |
Abstract: |
Under the "carbon peaking and carbon neutrality goals", the power grid faces intensive upgrades in form and function. The characteristics of nodalization and modularization are more prominent. It is urgent to determine a routing algorithm taking into account the characteristics of nodes to ensure the supporting capacity of the communication network. First, this paper defines importance degree based on the nodes’ power grid influence degree and topology relationship. Then the importance degree is embedded into the policy model from the state transition and adaptive search convergence control, so as to guide the route optimization direction. Then a parameter knowledge model is introduced to mine the relevant knowledge of the problem and cooperate with the importance degree to guide the optimization. This reduces the parameter sensitivity of the ant colony algorithm. Finally, the simulation results show that, in needing to meet the quality of service (QoS), the knowledge-based routing policy considering the importance of nodes can converge quickly, and provide favorable and stable performance in primary and standby routing. |
Key words: power communication node importance degree QoS routing strategy knowledge model swarm intelligence optimization |