节能型矿井动能能耗预测系统

发布时间：2018-04-12 12:32

本文选题：节能 + 能耗　；参考：《青岛科技大学》2016年硕士论文

【摘要】：节能降耗政策已经深入到全国各行各业,无论是政府还是企业领导层都很重视。国内煤矿企业是高能耗产业,从煤矿的生产、运输等环节都需要消耗大量的电能、水能以及压缩空气。节能主要从生产工艺、生产设备和生产管理三个方面着手。本课题针对生产管理节能,研发了一套自动采集动能能耗数据并进行能耗预测的动能能耗预测系统。该系统可以实现用电量、用水量、压缩空气压力、供水压力的实时监测,组态软件提供数据曲线分析、报警窗口、报表打印等。通过这些功能可以分析设备故障原因,了解能耗约束指标的完成情况。另外工作人员根据采集的数据,经过人工智能预测模型的计算,预测出今后一段时间的动能能耗情况,可以实现能源的合理调度和分配。文章先是结合能源使用情况以及煤矿企业发展现状提出了研究本课题的必要性,介绍了能耗预测的国内外研究现状,然后利用自动化采集技术、组态软件及人工智能技术对系统进行了整体设计。文章从系统的总体结构框架及通信方式、软硬件设计、一直到能耗预测模型的研究,完整且详细的介绍了系统的设计过程。在硬件设计部分,课题对可编程控制器、智能电表、传感器、变频器进行了选型和电气设计,并且还对系统变频调压原理以及电气设计中使用的抗干扰技术做了深入的研究。在软件设计部分,课题完成了智能电表Modbus通信协议、设备启动与保护、组态画面切换的PLC程序编写,还对分站嵌入版触摸屏和远程上位机进行组态软件设计,文章结尾对动能能耗预测模型的构建和改进做了详细的研究,最后采用了一种灰色算法与BP神经网络组合的预测模型,实现了对矿井动能能耗的仿真预测。
[Abstract]:Energy-saving and consumption reduction policy has penetrated into various industries, both the government and enterprise leadership are very important.Domestic coal mining enterprise is a high energy consumption industry, from the coal mine production, transportation and other links need to consume a lot of electricity, water energy and compressed air.Energy-saving mainly from the production process, production equipment and production management three aspects.Aiming at energy saving in production management, a kinetic energy consumption prediction system is developed, which can automatically collect kinetic energy data and predict energy consumption.The system can realize real-time monitoring of electricity consumption, water consumption, compressed air pressure, water supply pressure, configuration software to provide data curve analysis, alarm window, report printing and so on.Through these functions, equipment failure can be analyzed to understand the completion of energy constraints.In addition, according to the collected data and the calculation of artificial intelligence prediction model, the energy consumption of kinetic energy can be predicted for a period of time in the future, which can realize the rational scheduling and distribution of energy.In this paper, the necessity of studying this subject is put forward according to the situation of energy use and the development of coal mine enterprises, and the research status of energy consumption prediction at home and abroad is introduced, and then the automatic acquisition technology is used.Configuration software and artificial intelligence technology for the overall design of the system.In this paper, the design process of the system is introduced in detail, from the overall structure and communication mode, the design of hardware and software, to the research of energy consumption prediction model.In the part of hardware design, the selection and electrical design of programmable controller, intelligent meter, sensor and frequency converter are discussed, and the principle of frequency conversion and voltage regulation of the system and the anti-interference technology used in electrical design are also deeply studied.In the part of software design, the PLC program of intelligent meter Modbus communication protocol, equipment startup and protection, configuration screen switching is completed, and configuration software is designed for embedded touch screen and remote host computer.At the end of the paper, the construction and improvement of kinetic energy consumption prediction model are studied in detail. Finally, a prediction model combining grey algorithm and BP neural network is used to realize the simulation prediction of kinetic energy consumption in mines.
【学位授予单位】：青岛科技大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TD82

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