考虑优先级的智能电网业务调度与资源分配方案  

Service Scheduling and Resource Allocation Scheme of Smart Grid Considering Priority

作　　者：王素红 唐煜星 郭文豪 熊泽凯 祝长鸿 闫明 胡永乐 覃团发[1,2] WANG Suhong;TANG Yuxing;GUO Wenhao;XIONG Zekai;ZHU Changhong;YAN Ming;HU Yongle;QIN Tuanfa(School of Computer and Electronic Information,Guangxi University,Nanning 530004,China;Guangxi Key Laboratory of Multimedia Communications and Network Technology,Guangxi University,Nanning 530004,China;School of Electrical Engineering,Guangxi University,Nanning 530004,China;Runjian Co.,Ltd.,Nanning 530007,China)

机构地区：[1]广西大学计算机与电子信息学院,南宁530004 [2]广西大学广西多媒体通信与网络技术重点实验室,南宁530004 [3]广西大学电气工程学院,南宁530004 [4]润建股份有限公司,南宁530007

出　　处：《南方电网技术》2024年第4期59-70,79,共13页Southern Power System Technology

基　　金：国家自然科学基金资助项目(61761007);广西重点研发计划资助项目(桂科AB23026037,2023AB01190);2020年度南宁市创新创业领军人才(团队)“邕江计划”项目(2020006)。

摘　　要：随着智能电网和5G通信技术的融合发展,越来越多的智能终端应用到智能电网系统。针对海量电力业务的分流处理问题,提出了一种考虑电力业务优先级的业务调度和资源分配方案。首先介绍了面向智能电网的基于软件定义网络的边缘计算处理架构,建立了业务处理模型。其次阐述了基于强占型优先级排队的业务调度机制,建立了业务卸载收益和卸载开销的数学模型,该模型以系统整体收益最大化为目标函数,并基于电力业务的卸载有效性得到每一种优先级业务在边缘服务器的资源分配阈值,并以资源分配阈值为约束条件。再次,利用改进的遗传算法(improved genetic algorithm,IGA)求解最优的卸载和资源分配决策。最后通过实验仿真验证了IGA在收敛速度和个体选择方面均优于其他对比算法,对比其他方法所提方案在业务平均处理时间、功耗、高优先级业务平均处理时间等方面分别降低了69.2%、67.7%、73%,在系统收益方面提升了119%。With the integration and development of smart grid and 5G communication technology,more and more intelligent terminals are applied to the smart grid system.Aiming at the problem of diversion processing of massive power services,a service scheduling and resource allocation scheme considering the priority of power service is proposed.Firstly,the edge computing processing architecture based on software defined network for smart grid is introduced,and the service processing models are established.Secondly,the service scheduling mechanism based on preemptive priority queuing is elaborated,the mathematical models of service offloading revenue and offloading cost are established with overall system revenue maximization as the objective function.Based on the offloading effectiveness of power service,the resource allocation threshold of each priority service in the mobile edge computing(MEC) server is obtained and taken as the constraint condition.Thirdly,the improved genetic algorithm(IGA) is used to solve the optimal offloading and resource allocation decisions.Finally,the simulation results demonstrate that IGA outperforms other comparative algorithms in terms of convergence speed and individual selection,and the proposed scheme reduced the average processing time,energy consumption,and average processing time of high priority services by 69.2%,67.7%,and 73% compared to other methods,respectively.The system revenue is improved by 119% compared to other methods.

关 键 词：智能电网 软件定义网络 强占型优先级 排队模型 业务调度 系统收益 

分 类 号：TM73[电气工程—电力系统及自动化]