输电网中储能电站的智能预测系统设计  

Design of Intelligent Prediction System for Energy Storage Plant in Transmission Grid

作　　者：朱明[1] ZHU Ming(Guo Dian Nanjing Automation Co.,Ltd.,Nanjing 210000,China)

机构地区：[1]国电南京自动化股份有限公司,江苏南京210000

出　　处：《自动化仪表》2024年第6期63-67,共5页Process Automation Instrumentation

摘　　要：针对输电网中风电场与储能电站的容量配置问题,设计了一种输电网中储能电站的智能预测系统。采用直流系统、站用电低压系统、监控系统、微机保护装置、测控装置、计量装置、人工智能、5G移动通信以及综合自动化设备,创建智能预测系统。通过基于混合蛙跳算法(SFLA)的人工智能,实现储能电站容量的计算、研究、预测,同时对储能电站进行优化配置。将外连接口与卡线器进行对接。通过传感设备采集检测单元需要的硬件信息、运行状态、设备情况和额定负载等数据,并对数据进行优化。试验结果表明,该系统在储能电站的预测精准度高达90%以上。该系统对解决电能浪费问题具有较强的实用性,也符合储能电站的特性。An intelligent prediction system for energy storage plant in transmission grid is designed to address the problem of capacity allocation of wind farms and energy storage plant in transmission grid.The direct current(DC)system,station low voltage system,monitoring system,microcomputer protection device,measurement and control device,metering device,artificial intelligence,5G mobile communication,and integrated automation equipment are used to create the intelligent prediction system.Calculation,research,and prediction of the capacity of the energy storage plant are achieved through artificial intelligence based on the shuffled frog leaping algorithm(SFLA),as well as the optimized configuration of the energy storage plant.Docking the outer connection port to the snap wire.The data such as hardware information,operation status,equipment condition and rated load needed by the detection unit are collected by sensing equipment and the data is optimized.The test results show that the system has a prediction accuracy of more than 90%in the energy storage plant.The system is highly practical for solving the problem of power waste and is also in line with the characteristics of energy storage plant.

关 键 词：智能预测系统 混合蛙跳算法 测控装置 5G移动通信 人工智能 

分 类 号：TH-39[机械工程]