摘要
近年来,随着社会经济的快速发展,互联电网的规模变得越来越大,大区电网的互联在提高电力系统运行经济性的同时使整个互联系统的动态特性变得更为复杂,用电负荷的不断增加也给电力传输带来前所未有的挑战。在此电力行业发展背景下,作为电力系统稳定与控制理论研究中热点问题之一的电力系统低频振荡就越发显得重要。电力系统低频振荡的出现会限制区域电网间的功率支援和电量交换,在严重情况下甚至会造成系统解列、大面积停电等事故。
由于电力系统低频振荡问题的重要性,因此学术界和工业界对它给予了很多的关注,出现了众多的不同方法对其进行研究分析。按照低频振荡分析数据源的不同可将低频振荡的分析方法划分为基于模型数据的分析方法和基于量测数据的分析方法等两类。第一种方法需要建立电力系统的数学模型并在确定的运行方式下进行分析,这在大电网互联的形势下由于电网复杂、运行状况不确定性增强而变得困难。实际上,发生低频振荡时电力系统的运行变量直接包含着振荡信息,因此第二种方法即利用实测数据进行分析的方法目前得到了广泛的应用。
广域测量系统(Wide Area Measurement System,WAMS)由相量测量单元(Phasor Measurement Unit, PMU)同步采集广域电网的实时运行参数,借助高速通信网络传输至数据处理中心站,得到同一时间坐标下电网全局的动态信息。电力广域频率监控网络(Wide Area Frequency Monitoring Network, FNET)是一种使用配电网电力插座作为驱动源和测量源的新型广域测量系统,具有低成本、易安装、高精度等优点,目前已经在北美电网得到广泛的部署。
在使用FNET实际测量数据对美国东部互联电网低频振荡进行模态分析时,出现了一系列影响算法分析性能与结果的问题,包括:考虑系统非线性条件下的输入信号的合适数据段选取、输入信号的采样频率选择、输入信号的时间长度设置、不同信号信噪比的多输入信号对多信号算法的影响、算法本身对于输入信号在不同信噪比条件下的参数设置等。本文即是从这些实际问题出发,进行了一系列的理论研究和创新,从而改进算法、给出算法的参数设置指导、给出算法应用指导、给出了输入信号参数设置的最优范围、采用时频分析技术选取合适数据段、多输入信号条件下的筛选方法以及由以上功能模块所组成的总体方案。仿真和实际案例分析结果表明,改进后的用于实际广域测量系统低频振荡模态分析的总体方案要明显优于现有的方法,因此本文的研究工作具有一定的理论价值和较高的实际意义。最后,基于本文提出的总体方案对2009年至2010年美国东部电网的实际低频振荡案例进行了统计分析,给出了不同分类的低频振荡出现在不同年、月份的比例和数量,对于随机选取的18个美国东部电网低频振荡实例则进行了详细的模态分析,给出了相应的振荡频率、阻尼比和模式形态分布等信息。
Recently, with the rapid development of society and economy the scale of intercon-nected power grid becomes greater and greater. The dynamic property of entire interconnec-tion has been changed to be more complicated with more interconnection of power grid which also could improve the economy for power system operation. Besides, the power load rising also brings the significant challenge of electric power transmission. Under this back-ground of electric power industry, power system low frequency oscillations which is one of the hot research topics in the area of power system stability and control becomes more and more important. Power system low frequency oscillations can limit the backup of power in different areas and exchange of electric power. What is more, in severe cases it will result in the interconnection breakup, blackout and other accidents.
Because of the importance of issue on power system low frequency oscillations, the in-dustry and academia has paid a lot of attention on it and a lot of different methods on ana-lyzing low frequency oscillations can be obtained. According to the varied data source for analyzing low frequency oscillations, methods on low frequency oscillations can be classi-fied into two types:the method based on system model and the method based on measure-ment. The first method relys on the accurate model of power system and determinate opera-tion mode which is rather difficult to acquire resulting from the complexity of power grid and uncertainty of operation mode in the case of large interconnected power grid. Actually, at the time of oscillations power system operation data contain rich oscillations information directly. Thus, the method for analyzing power system low frequency oscillations by utiliz-ing the field measurement data has been widely applied.
Wide area measurement system (WAMS) can obtain real time operation parameters of power grid from synchronized sampling by phasor measurement unit (PMU) deployed in wide geography area of power grid. Then operation parameters are transmitted to data center via the high speed communication network and the global dynamic information of entire power grid can be obtained accordingly. Wide Area Frequency Monitoring Network (FNET) is a novel WAMS by using the distribution power outlet as its power source and data source. It have characteristics of low cost, easy installation and high accuracy. Nowadays, it has been widely deployed in the North American power grid.
A lot of problems occurred when the field measurement data recorded by FNET was applied into analysis of low frequency oscillations. The problems introduced above are as follows:selection of proper data frame of input signal considering the effects of non-linearity of power system, selection of sampling frequency of input signal, time length setting of input signal, effects of varied signal-to-noise ratio (SNR) of multiple input signal on multiple signal modal analysis algorithm, presetting processing parameters of algorithms corresponding to different SNR of input signal. Based on those problems this paper obtains following significant achievements by theoretical research and innovation:improving Prony algortihm, introducing rules of presetting processing parameter of algorithms, presenting the guideline of algorithms application, acquiring the optimal range for parameter setting of in-put signal, appling time frequency technology for choosing the proper data frame of input signal, providing a filtering scheme in the case of multiple input signal with varied SNR, and a whole scheme including all the module above for analyzing the low frequency oscillations from field measurement data. The result of simulated case and practical case shows that the proposed whole scheme is obviously much better than existing methods. Therefore, the re-search of this paper has a certain theoretical value and practical significance. Finally, a sta-tistical analysis for low frequency oscillations from 2009 to 2010 occurred in American eastern interconnection is made by applying the proposed scheme. At the same time, random selected cases of eighteen are analyzed in detail and corresponding modal information in-cluding mode frequency, damping ratio and mode shape are also introduced.
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