基于嵌入式系统的配电网络重构实验装置开发
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摘要
配电网络重构是配电网络自动化研究中的一个热点问题,它主要通过改变分段开关、联络开关的组合状态,来达到改善网络运行结构、降低网络损耗、提高网络可靠性的目的。因此,搭建一个可用于实验配电网络重构算法以及模拟演示整个配电网络重构过程的实验平台,对于配电网络自动化的研究具有十分重要的意义。
     实验装置采用模块化结构,整个装置的设计被划分为四个功能模块:模拟配电网络模块、嵌入式系统模块、数据采集模块以及重构执行模块。其中嵌入式系统模块以ARM+Linux的嵌入式系统为核心,主要用于接收网络潮流参数、运行配网重构算法以及发出重构指令;模拟配电网络模块是以IEEE配电网可靠性测试系统为模板制作的一个低压网络模型,用于模拟实际的配电网络;数据采集模块则以一块STC的单片机为中央处理器,用于采集网络潮流数据并将其提供给重构算法作为参数;重构执行模块的处理器则是一块Altera的FPGA,用于接收嵌入式系统模块输出的重构指令并执行。论文对各个模块的功能、原理及其具体实现方法进行了分析介绍,并就以故障停电用户数最少为目标函数的配电网络重构算法进行了研究实验。
     最后,论文展示了实验结论,并就该系统未来需改进和发展的方向进行了展望。
Distribution Network Reconfiguration (DNR) is a hot topic in the research on distribution network automation system which can improve the network running structure, reduce active loss, and increase network reliability by changing the combination states of section switches and contact switches. Consequently, it is meaningful to design a DNR experiment device on which we can practise the DNR algorithm research and simulate the whole process of reconfiguration.
     The test bench is composed of four function modules: distribution network circuit simulation module, embedded system module, data acquisition module, and reconfiguration execution module. Among these modules the embedded system module, which is composed of S3C2410X microprocessor based on ARM920T core and Linux embedded operating system, is the center control module. Its main function is to receive the parameters from data acquisition module, run the DNR algorithm, and then output its operation result. The distribution network circuit simulation module is a low voltage distribution network based on IEEE-RBTS Bus2 and Bus 4.The data acquisition module centers about a STC MCU, and its main function is to get the parameters from the distribution network circuit simulation module and then send these parameters to the embedded system module. The reconfiguration execution module chooses a ALTERA FPGA as its processor to implement the order of reconfiguration. Then this paper introduces and analyzes the four function modules about their principle, function, the keys and difficulties about their design, and also develops a DNR algorithm and successfully realizes it on this test bench.
     Finally, this paper shows the results of the experiment and the points to be improved and developed.
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