面向物联网的泵站站内优化调度系统研究

Research on the optimization scheduling systemof pump station based on Internet of Things

针对泵站站内优化调度问题进行了研究,引入物联网技术建立了面向物联网的泵站站内优化调度系统。系统的感应层通过各种传感器和网络摄像头采集数据,网络层采用Zigbee技术和5G技术传输数据,应用层实现用户的交互、数据的存储、方案的制定与实施。系统从功能角度分为人机交互界面、监测子系统、决策支持子系统和调度执行子系统4个部分。其中,决策支持子系统采用改进编码方式的动态惩罚函数遗传算法对泵站站内优化调度模型求解,并以江都三站为例,得到了较好的优化结果。

The optimization scheduling problem in the pump station was researched,and the Internet of Things technology was introduced to establish an optimization scheduling system in the pump station.The sensor layer of the system collected data through various sensors and webcams,the network layer used Zigbee technology and 5G technology to transmit data,and the application layer realized user interaction,data storage,plan formulation and implementation.From the perspective of function,the system is divided into four parts:human-machine interaction interface,monitoring subsystem,decision support subsystem and scheduling and execution subsystem.Among them,the decision support subsystem used an improved coding method of the dynamic penalty function genetic algorithm to solve the optimal scheduling model in the pumping station.Taking Jiangdu No.3 Station as an example,a better optimization result was obtained.