摘要
“煤改电”背景下大量电采暖设备的无序接入,极易造成尖峰负荷、引起电压波动甚至越限,影响电能质量与用电安全。针对这一问题,提出了基于共享介质争用访问机制的电采暖设备自适应控制方法。通过刻画电采暖功率变化与区域内电压分布关系函数,分析了各节点电压波动的关键影响因素。以此为基础,构建了以家庭为最小控制单元的电采暖设备自适应控制方法实施架构:采用自组织映射(SOM)神经网络得到家庭近期活跃的电采暖设备数量,进而借鉴通信网络中信道访问与数据传输冲突监测机制,使电采暖设备通过实时采集本地环境信息和电气信息进行自主控制和冲突规避,实现了无需通信的自适应控制。仿真结果验证了所提控制方法在减小用电尖峰负荷、平抑负荷曲线及抑制电压越限方面的有效性以及在实时控制方面的优越性。
On the background of “coal-to-electricity”,the disorderly connection of a large number of electric heating equipment can easily cause peak load,voltage fluctuation or even limit violation,which aggravates the quality and safety of power supply.Aiming at this problem,this paper proposes a self-adaptive control method for electric heating equipment based on the shared media contention access mechanism.The key influencing factors of node voltage fluctuations are analyzed by depicting the relationship function between the electric heating power variation and the regional voltage distribution.On this basis,an implementation architecture of self-adaptive control method for the electric heating equipment with the family as the smallest control unit is constructed.In the architecture,the self-organizing map(SOM) neural network is used to obtain the number of recently active electric heating equipment in the family.Then,referring to the channel access and conflict monitoring mechanism on data transfer in the communication network,the electric heating equipment is enabled to carry out autonomous control and conflict avoidance through real-time collections of local environmental and electrical information,realizing the self-adaptive control without communication.Simulation results verify the effectiveness of the proposed control method in reducing the peak load of power consumption,smoothing the load curve and restraining the voltage from exceeding the limit.The superiority of the self-adaptive control in the real-time response is also verified.
作者
石富岭
祁琪
冮若嘉
刘学忠
赵海龙
祁兵
SHI Fuling;QI Qi;GANG Ruojia;LIU Xuezhong;ZHAO Hailong;QI Bing(School of Electrical and Electronic Engineering,North China Electric Power University,Beijing 102206,China;State Grid Liaoning Electric Power Co.,Ltd.,Shenyang 110006,China;State Grid Beijing Electric Power Company,Beijing 101300,China)
出处
《电力系统自动化》
EI
CSCD
北大核心
2023年第16期76-84,共9页
Automation of Electric Power Systems
基金
中央高校基本科研业务费专项资金资助项目(2022MS002)。
关键词
智能用电
电采暖
共享介质争用访问
负荷平抑
自适应控制
退避算法
自组织映射
神经网络
smart power utilization
shared media contenthon alless mechanism
electric heating
load balancing
self-adaptive control
backoff algorithm
self-organizing map(SOM)
neural network
