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Control-oriented modeling and simulation of a three-phase gravity separator and its level loop process dynamics identification.

机译:三相重力分离器的面向控制的建模和仿真及其液位回路过程动力学识别。

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摘要

A three-phase gravity separator system is one of the most important facilities in the oil and gas industry. The main function of the separator is to separate the three phase inflow of water, oil, and gas into the outlets of the separator. Three phase separators have rich and complex dynamics. Many research activities have been conducted in order to model the behavior of the separator, mostly involving Computational Fluid Dynamics (CFD). Furthermore, few studies also have been conducted from the point of view of flow dynamics and mass balance differential equations.;Control of the three-phase separator processes includes water level, oil level, and the outlet gas pressure. Control of each process is based on the mass balance equations and may correlate with other processes which may affect the overall dynamics of the separator. This issue makes the modeling of the separator a challenging task. A proper model is required in order to control the processes of the separator. The modeling part is done using the mathematical equation of flow dynamics and mass balance of the phases, where each process loop is realized. The model takes into account the tank dimension, the flow rate, the fluid physical properties, and the droplet size distribution. The initial condition is set based on the available data. A simple PI controller is introduced for each process.;The second part in this thesis work will focus on the identification of the dynamics of the level process in the separator. Process dynamics identification is an important problem in the industrial control area. In oil and gas facilities, processes such as level, pressure, flow, and temperature comprise complex unknown dynamics and very often are not easy to control to provide satisfactory performance. To ensure high performance of the designed control, dynamics of such processes needs to be precisely modeled. Process dynamics identification usually consists of selection of an adequate model structure and finding parameters of the selected model. Model structure is selected on the basis of fundamental laws (first principles) used for process description, while model parameters are computed through matching of the actual process and the model responses to certain test signals. The most common type of the test signal is the step input.;It is shown in the present research that the use of the modified relay feedback test (MRFT) as a test allowing one to evaluate dynamics of the process is beneficial to the accuracy of identification. This benefit comes from the fact that identification is done through excitation of frequencies of test oscillations that are most informative and important to the system stability and performance. Data that are measured from MRFT are the frequency and the amplitude of the test oscillations, which makes realization of the test and automatic data measurement easy by means of DCS or PLC. Measurements are done in a few points of the process frequency response (Nyquist plot), and matching of the model response to the actual process response is done through optimization of a certain cost function that characterizes closeness of the measured response and response of the model. The describing function method is used to obtain the frequency response analysis of the MRF oscillations. Another method using the so-called locus of perturbed relay system (LPRS) is also presented in order to perform an exact frequency-domain analysis of the oscillations.;The proposed approach is demonstrated on a liquid level process laboratory setup. The process dynamics is modeled as first-order-plus-dead-time-plus-integrator transfer function. MRFT tests were conducted on the level process laboratory setup having unknown parameters to obtain experimental data. The unknown parameters of the process are found using conventional optimization technique. Simulation and optimization are performed using Matlab/Simulink. The results showed good accuracy of the process identification. A PI controller was then designed based on the process model to verify efficiency of the approach. It is shown that the modified relay feedback test can be successfully used for process identification, with providing a number of advantages over other identification methods.
机译:三相重力分离器系统是石油和天然气工业中最重要的设施之一。分离器的主要功能是将水,油和气的三相流入分离到分离器的出口。三相分离器具有丰富而复杂的动力学。为了对分离器的行为进行建模,已经进行了许多研究活动,其中主要涉及计算流体动力学(CFD)。此外,从流动动力学和质量平衡微分方程的观点来看,也很少进行研究。三相分离器过程的控制包括水位,油位和出口气体压力。每个过程的控制均基于质量平衡方程式,并且可能与其他过程相关,这可能会影响分离器的整体动力学。这个问题使分隔器的建模成为一项艰巨的任务。为了控制分离器的过程,需要一个合适的模型。使用流动动力学和各相质量平衡的数学方程式完成建模部分,从而实现每个过程循环。该模型考虑了储罐尺寸,流量,流体物理特性和液滴尺寸分布。初始条件是根据可用数据设置的。为每个过程引入了一个简单的PI控制器。;本论文的第二部分将集中于分离器中液位过程的动力学识别。过程动力学识别是工业控制领域的重要问题。在石油和天然气设施中,液位,压力,流量和温度等过程包含复杂的未知动力学,并且通常不容易控制以提供令人满意的性能。为了确保所设计控件的高性能,需要对此类过程的动力学进行精确建模。过程动力学识别通常包括选择适当的模型结构并查找所选模型的参数。根据用于过程描述的基本定律(第一原则)选择模型结构,同时通过匹配实际过程和模型对某些测试信号的响应来计算模型参数。测试信号最常见的类型是阶跃输入。在本研究中表明,使用改进的继电器反馈测试(MRFT)作为允许人们评估过程动力学的测试有助于提高信号的准确性。识别。该优点来自于这样的事实,即通过激发对系统稳定性和性能最有用和最重要的测试振荡频率进行识别。从MRFT测量的数据是测试振荡的频率和幅度,这使得通过DCS或PLC轻松实现测试和自动数据测量成为可能。在过程频率响应的几个点上进行测量(奈奎斯特图),并通过优化某些成本函数来完成模型响应与实际过程响应的匹配,该函数表征了所测响应和模型响应的紧密度。描述函数方法用于获得MRF振荡的频率响应分析。还提出了使用所谓的扰动中继系统(LPRS)轨迹的另一种方法,以便对振荡进行精确的频域分析。;在液位过程实验室设置上演示了该方法。过程动力学建模为一阶加死时间加积分器传递函数。在具有未知参数的水平过程实验室设置上进行了MRFT测试,以获得实验数据。使用常规优化技术可以找到过程的未知参数。使用Matlab / Simulink进行仿真和优化。结果表明过程识别具有良好的准确性。然后根据过程模型设计PI控制器,以验证该方法的效率。结果表明,改进的继电器反馈测试可以成功地用于过程识别,与其他识别方法相比,具有许多优势。

著录项

  • 作者

    Haekal, Muhammad.;

  • 作者单位

    The Petroleum Institute (United Arab Emirates).;

  • 授予单位 The Petroleum Institute (United Arab Emirates).;
  • 学科 Electrical engineering.
  • 学位 M.S.
  • 年度 2014
  • 页码 138 p.
  • 总页数 138
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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