摘要
针对目前低碳园区具有规模较大、信息分散、数据采集成本较高的问题,本文提出了一种智能感知系统的多目标优化配置方法。基于提出的智能感知系统结构,以传感网络节点覆盖率最高为目标进行节点选址;同时以投资成本、故障损失成本和运维成本最小为目标,建立数据采集设备优化配置模型。采用量子遗传算法求解多目标优化模型,结合工程实际,以获得传感网络覆盖率和经济效益最大化的配置方案。最后通过算例分析验证所提出的基于量子遗传算法的智能感知系统多目标优化配置方法的有效性。
Directing at the problems of large scale,scattered information and high cost of data collection in low-carbon parks,this paper proposes a multi-objective optimization configuration method of intelligent sensing system.Based on the proposed structure of the intelligent sensing system,node selection is carried out with the target of the highest node coverage of the sensor network.Meanwhile,aiming at the minimum investment cost,failure loss cost and operation maintenance cost,the optimal configuration model of data acquisition equipment is established.In this paper,quantum genetic algorithm is used to solve the multi-objective optimization model,combined with the engineering practice,in order to obtain the configuration scheme of the sensor network coverage and economic benefit maximization.Finally,an example is given to verify the effectiveness of the proposed multi-objective optimal configuration method for intelligent sensing system based on quantum genetic algorithm.
作者
孙哲宇
王琦
尹曜华
柯吉
段晨东
邢学树
SUN Zheyu;WANG Qi;YIN Yaohua;KE Ji;DUAN Chendong;XING Xueshu(School of Energy and Electrical Engineering,Chang’an University,Xi’an 710064,China;Power China Guiyang Engineering Co.,Ltd.,Guiyang 550081,China)
出处
《现代建筑电气》
2024年第4期8-15,共8页
Modern Architecture Electric
基金
陕西省重点研发计划(2023-YBSF-285)
贵州省科技计划项目(黔科合支撑[2023]一般409)
中国电建集团贵阳勘测设计研究院有限公司项目(YJ2022-12)
中国电力建设集团有限公司资助项目(XNZ/2020/KK-1-5)。
关键词
智能感知系统
传感网络
数据采集设备
优化配置
量子遗传算法
intelligent sensing device
sensor network
data acquisition equipment
optimize configuration
quantum genetic algorithm
