基于虚拟MAC的电力线载波与无线融合及业务分配策略研究
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摘要
随着配电物联网营配贯通、IP化等需求的提出,单一电力线载波、无线等通信技术的性能已难以满足应用需求。两种技术的深度融合和协同可实现优势互补,解决单一技术业务承载能力差等问题。为此该研究基于虚拟MAC的电力线载波与无线融合技术,提出一种链路选择与业务分配策略。基于排队论对虚拟MAC层在单跳网络与多跳网络中的业务分配方案进行建模分析,以减小时延为优化目标,根据网络参数,确定各链路业务分配比例。数值分析表明,所提出的业务分配策略能够减小通信系统的时延。
To meet the increasing demands of marketing and distribution fusion and IP distribution in internet of things, it is difficult for a single power line or wireless communication technology to meet all the services requirements. The cooperation of power line and wireless communication can complement each other, and thus to solve the problems of poor supporting capability of a single technology. Consequently, we studied the power line and wireless network fusion based on virtual MAC, and proposed a link selection and traffic allocation strategy. Based on the queuing theory, the traffic allocation scheme of the virtual MAC layer both in single-hop network and multi-hop network were modeled and analyzed,where the delay is taken as the optimization target, and the traffic allocation proportion of each link is determined according to the network parameters. Numerical analysis shows that the proposed traffic allocation strategy can reduce the communication delay.
To meet the increasing demands of marketing and distribution fusion and IP distribution in internet of things, it is difficult for a single power line or wireless communication technology to meet all the services requirements. The cooperation of power line and wireless communication can complement each other, and thus to solve the problems of poor supporting capability of a single technology. Consequently, we studied the power line and wireless network fusion based on virtual MAC, and proposed a link selection and traffic allocation strategy. Based on the queuing theory, the traffic allocation scheme of the virtual MAC layer both in single-hop network and multi-hop network were modeled and analyzed,where the delay is taken as the optimization target, and the traffic allocation proportion of each link is determined according to the network parameters. Numerical analysis shows that the proposed traffic allocation strategy can reduce the communication delay.
引文
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[19]崔杨,杨志文,张节潭,等.计及综合成本的风电-光伏-光热联合出力调度策略[J].高电压技术,2019,45(1):269-275.CUI Yang,YANG Zhiwen,ZHANG Jietan,et al.Wind power-photovoltaic-photothermal combined output dispatching strategy considering comprehensive cost[J].High Voltage Engineering,2019,45(1):269-275.
[20]陶琼,王德顺,叶季蕾,等.考虑储能配置模式的多数据源融合分布式光伏发电并网接纳分析方法[J].高电压技术,2018,44(4):1093-1098.TAO Qiong,WANG Deshun,YE Jilei,et al.Multi-data source fusion distributed photovoltaic power generation grid-connected acceptance analysis method considering energy storage configuration mode[J].High Voltage Engineering,,2018,44(4):1093-1098.
[21]孙莹,于琳,李可军,等.配电变压器更换优先级模型[J].高电压技术,2017,43(7):2370-2377.SUN Ying,YU Lin,LI Kejun,et al.Priority model of distribution transformer replacement[J].High Voltage Engineering,2017,43(7):2370-2377.
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[23]电力用户用电信息采集系统通信协议第4部分:基于微功率无线通信的数据传输协议:Q/GDW11016-2013[S],2013.Power user electric energy data acquisition system communication protocol part 4:micro-power wireless data transmission protocol:Q/GDW11016-2013[S],2013.
[2]吕军,栾文鹏,刘日亮,等.基于全面感知和软件定义的配电物联网体系架构[J].电网技术,2018,42(10):3108-3115.LüJun,LUAN Wenpeng,LIU Riliang,et al.Architecture of distribution internet of things based on widespread sensing&software defined technology[J].Power System Technology,2018,42(10):3108-3115.
[3]李松浓,胡晓锐,郑可,等.低压电力线载波通信信道衰减特性测量与分析[J].电力系统保护与控制,2018,46(4):99-106.LI Songnong,HU Xiaorui,ZHENG Ke,et al.Measurement and analysis of attenuation characteristics of low voltage power line carrier communication channel[J].Power System Protection and Control,2018,46(4):99-106.
[4]刘伟麟,李建岐,陆阳,等.跨频带认知电力线载波通信:核心思想、关键技术与应用[J].南方电网技术,2016,10(5):123-133.LIU Weilin,LI Jianqi,LU Yang,et al.Cross-band cognitive power line communication:core concepts,key technologies and applications[J].Southern Power System Technology,2016,10(5)123-133.
[5]李建岐,陆阳,高鸿坚.基于信道认知在线可定义的电力线载波通信方法[J].中国电机工程学报,2015,35(20):5235-5243.LI Jianqi,LU Yang,GAO Hongjian.On(power-)line defined power line communication solution based on channel sensing[J].Proceedings of the CSEE,2015,35(20):5235-5243.
[6]杨培宏,刘连光,刘春明,等.地磁暴引起电网电压波动抑制策略[J].高电压技术,2017,43(5):1707-1714.YANG Peihong,LIU Lianguang,LIU Chunming,et al.The suppression strategy of grid voltage fluctuation caused by geomagnetic storm[J].High Voltage Engineering,2017,43(5):1707-1714.
[7]袁越.无线通信技术在智能配电网中的运用[J].中国新技术新产品,2018,381(23):46-47.YUAN Yue.Application of wireless communication technology in smart distribution network[J].China New Technology and New Products,2018,381(23):46-47.
[8]IEEE standard for a convergent digital home network for heterogeneous technologies amendment 1:support of new MAC/PHYs and enhancements:IEEE Std 1905.1a-2014(amendment to IEEE Std1905.1-2013)[S],2013.
[9]IEEE standard for information technology-specific requirments-part3:carrier sense multiple access with collision detection(CSMA/CD)access method and physical layer specifications:IEEE Std802.3TM-2008[S],2008.
[10]IEEE standard for information technology-telecommunications and information exchange between systems-local and metropolitan area networks-specific requirements-part 11:wireless LAN medium access control(MAC)and physical layer(PHY)specifications:IEEE Std802.11TM-2012[S],2012.
[11]IEEE standard for broadband over power line networks:medium access control and physical layer specifications:IEEE Std1901TM-2010[S],2010.
[12]Multimedia over coax alliance:MoCA,MAC/PHY specification v1.1:MoCA-M/P-SPEC-V1.1-06272011[S],2011.
[13]刘柱,欧清海.面向智能配电网的电力线与无线融合通信研究[J].电力信息与通信技术,2016,14(2):1-6.LIU Zhu,OU Qinghai.Research on power line and wireless fusion communication for intelligent distribution network[J].Power Information and Communications Technology,2016,14(2):1-6.
[14]王立城,霍超,刘雨峰,等.电力线载波与无线融合通信链路感知组网算法[C]∥2018电力行业信息化年会.银川:[出版地不详],2018:4.WANG Licheng,HUO Chao,LIU Yufeng,et al.Power line carrier and wireless fusion communication link sensing networking algorithm[C]∥2018 Power Industry Informatization Annual Conference.Yinchuan,China:[s.n.],2018:4.
[15]王贤辉,王立城,宋彦斌,等.基于信噪比优选的电力线载波和无线通信物理层融合方法[J].电力信息与通信技术,2018,16(9):14-20.WANG Xianhui,WANG Licheng,SONG Yanbin,et al.Power line carrier and wireless communication physical layer fusion method based on signal to noise ratio optimization[J].Electric Power Information and Communication Technology,2018,16(9):14-20.
[16]许楠,郝学坤,许众.MF-TDMA卫星通信系统信道分配时间优化方法[J].无线电通信技术,2012,38(2):24-26.XU Nan,HAO Xuekun,XU Zhong.Channel allocation time optimization method for MF-TDMA satellite communication system[J].Radio Communications Technology,2012,38(2):24-26.
[17]潘轲.面向新能源微网的电力线与无线异构通信技术研究[D].北京:华北电力大学,2018.PAN Ke.Research on power line and wireless heterogeneous communication technology for new energy microgrid[D].Beijing,China:North China Electric Power University,2018.
[18]SUN L,TIAN H,SUN Q Y,et al.Traffic allocation scheme with cooperation of WWAN and WPAN[J].IEEE Communications Letters,2010,14(6):551-553.
[19]崔杨,杨志文,张节潭,等.计及综合成本的风电-光伏-光热联合出力调度策略[J].高电压技术,2019,45(1):269-275.CUI Yang,YANG Zhiwen,ZHANG Jietan,et al.Wind power-photovoltaic-photothermal combined output dispatching strategy considering comprehensive cost[J].High Voltage Engineering,2019,45(1):269-275.
[20]陶琼,王德顺,叶季蕾,等.考虑储能配置模式的多数据源融合分布式光伏发电并网接纳分析方法[J].高电压技术,2018,44(4):1093-1098.TAO Qiong,WANG Deshun,YE Jilei,et al.Multi-data source fusion distributed photovoltaic power generation grid-connected acceptance analysis method considering energy storage configuration mode[J].High Voltage Engineering,,2018,44(4):1093-1098.
[21]孙莹,于琳,李可军,等.配电变压器更换优先级模型[J].高电压技术,2017,43(7):2370-2377.SUN Ying,YU Lin,LI Kejun,et al.Priority model of distribution transformer replacement[J].High Voltage Engineering,2017,43(7):2370-2377.
[22]低压电力线宽带载波通信互联互通技术规范:Q/GDW11612-2016[S],2016.Low voltage power line broadband communication interoperability technical specification:Q/GDW11612-2016[S],2016.
[23]电力用户用电信息采集系统通信协议第4部分:基于微功率无线通信的数据传输协议:Q/GDW11016-2013[S],2013.Power user electric energy data acquisition system communication protocol part 4:micro-power wireless data transmission protocol:Q/GDW11016-2013[S],2013.