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电力燃煤海运运力预测系统设计与实现
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摘要
本论文选题,源自作者参加的大连海事大学与神华集团某电力公司签约的实际项目,该项目自2010年春开始研发,年底在北京通过了专家验收。
     公司的业务部门——燃料管理中心,负责统一为电厂调配发电用的燃煤。为了确保各电厂燃煤库存安全、经济与合理,需要研发一套“电力燃煤海运运力预测系统”,以替代手工调度的操作模式,为燃煤的海运调度决策,提供有力的信息支持。
     本文阐述了燃料管理中心电力燃煤海运运力预测系统的开发过程。该系统实现的功能是存储和分析燃煤库存和海运运力的相关数据,预测库存和海运运力,根据预测结果,制定电力燃煤海上运输计划,合理安排运力,以最低的成本满足电厂燃煤供应,对现状和历史数据进行统计和查询,辅助管理者进行科学决策。
     首先,对电力燃煤海运运力预测系统进行需求分析,根据燃料管理中心的业务流程的特点,将系统划分为两个子系统,运力预测子系统和运力查询子系统,详细阐述了子系统的功能,随后介绍了系统设计与实现中所使用的UML和Struts框架和Hibernate持久化等相关技术;然后,给出了系统的总体结构图,其中,运力预测子系统为本系统的核心。之后给出了系统主要模块的详细设计,数据库设计和界面设计。以添加信息模块为例,讲述了系统分层的实现机制,具体讲述了库存预测等模块的实现;最后,论文给出系统试运行效果,并在此基础上总结了课题研究成果,指出了本课题更深层次的研究方向。
     电力燃煤海运运力预测系统,已经上线运行,彻底取代了原有的业务人员手工操作,避免了Excel数据存储分散性,运力查询角度的单一性等弊端,太大提高了企业业务人员的工作效率,为企业带来了良好效益。
This paper is from an actual project which was developed by Dalian Maritime University and the Shenhua Group together. The author took part in it. The project began in the spring of 2010, and got the acceptance of experts in Beijing in the end of the year.
     The company's fuel management center is responsible for the deployment of power coal among. In order to ensure that the power coal storage is of security, economic and reasonable, the center need to develop a system for prediction of power coal shipping to replace the manual operation and provide strong information support to make decisions for the coal shipping.
     In this paper, the author designs and implements the Prediction System for Power Coal Shipping. The system is used to predict, store and analysis of shipping and storage data, and according to forecast, to arrange shipping of coal-fired to meet the coal-fired supply with the lowest cost. And the statistical data of coal shipping, supply, storage and shipping information helps leaders to make right decisions.
     First, the author analyses the requirement of the system and introduces the UML and Struts framework and Hibernate persistence technology. Then, the author presents the overall structure of the system which is divided into subsystems include prediction subsystem and query subsystem, and displays the system's functional design, including the core of the system prediction subsystem, then introduces the database design and GUI design of the system. The author takes the module of adding information for example to introduce the implementation mechanism of the system, followed by the implementation of the prediction module for inventory. Finally, the author provides the system running results, and on this basis summarizes the research and looks into deeper research in the future.
     The system has been running online, completely replaced the original manual operation, avoiding the dispersion of Excel data storage and the unity of query angle for statistics, greatly improved the work efficiency of business operations staff, and brought good benefit for enterprises.
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