摘要
由于目前电力行业负荷量的增加,电力管理就越来越被人们所看重。并且由于现在智能电网的开发和利用,会产生大量的数据,这些数据的存放和管理都需要云计算来处理。所以本文提出了基于云网协同的智能电网能源管理系统。它可以根据消费者的要求来动态的运行和管理。因此,被称为数据驱动的智能电网管理系统。雾计算作为云计算的扩展,有助于减轻云数据中心的负载。并且本文还提出了一种基于云计算和雾计算兼容的系统模型,以减少来自终端设备向雾数据中心进行请求的响应时间和处理时间。并且在虚拟机上合理分配优化响应时间和处理时间。使用新的服务代理策略(NSBP)来管理数据中心。本文采用的负载均衡算法是粒子群优化和模拟退火(PSO-SA)的混合体,用于在数据中心的虚拟机上分配请求。实现了两个方案来评估服务代理策略和负载平衡算法的性能。
Due to the increase of power industry load,power management is more and more valued by people.In addition,due to the development and utilization of smart grid,a large amount of data will be generated,and the storage and management of these data need to be processed by cloud computing.Therefore,this paper proposes a smart grid energy management system based on cloud network coordination.It can be run and managed dynamically according to the requirements of consumers.Therefore,it is called data driven smart grid management system.As an extension of cloud computing,fog computing helps lighten the load on cloud data centers.And this paper also proposes a system model based on cloud computing and fog computing compatibility to reduce the response time and processing time of requests from terminal devices to fog data center.Optimize response time and processing time on the virtual machine.Use the new service broker policy(NSBP)to manage the data center.The load balancing algorithm used in this paper is a hybrid of particle swarm optimization and simulated annealing(PSOSA)to distribute requests on virtual machines in data centers.Two schemes are implemented to evaluate the performance of service broker policies and load balancing algorithms.
作者
潘磊
沈雪晴
黄文雯
韩璐
贾明
PAN Lei;SHEN Xueqing;HUANG Wenwen;HAN Lu;JIA Ming(State Grid Information&Telecommunication Co.,Ltd,Beijing 100761,China;School of e-commerceand logistics,Beijing Technology and Business University,Beijing 100080,China)
出处
《中国测试》
CAS
北大核心
2022年第S01期211-217,共7页
China Measurement & Test
基金
国家电网有限公司信息通信分公司资助预研项目(CN2021XT-01)
关键词
智能电网
云计算:雾计算
粒子群优化
虚拟机
Smart grid
Cloud computing:fog computing
Particle swarm optimization
Virtual machine
