Process and process control design using dynamic flowsheet simulation

Garner, K. C. ; Moreton, C. N. ; Peberdy, N. J.
Organization: Society for Mining, Metallurgy & Exploration
Pages: 5
Publication Date: Jan 1, 1987
Introduction During the past decade a major objective of the process industry has been to use digital computer technology to improve plant operating efficiencies. This objective implied some form of optimization, a concept that has various interpretations depending on the view of the prospective user. For the purpose of this paper, optimization of a process plant is defined as the establishment and setting of plant operating conditions that maximize some mathematical yield function, i.e. maximum profit, minimum residue, etc. Analysis of these objectives and the available design and implementation techniques led to the conclusion that digital computer and optimization techniques are not the stumbling blocks, but rather the development and derivation of the mathematical models of the unit operations and process plants to be optimized. Such models should not only describe the optimized (steady-state) objective, but also how one steers to this state (control algorithm). Due to the multidisciplinary nature of the skills associated with the design and operation of process plants, the development of suitable models by a single discipline, such as the process control engineer, was found to be not only difficult but often impossible, due to budget and human resource limitations. To over-come these limitations, a computer aided design (CAD) tool has been developed. It aims to provide a productivity tool to the various disciplines, at the same time coordinating the technical input from each. The system described is but the starting point in an evolutionary development of a tool that, with use, is becoming more efficient and cost effective to use. Development has become an application engineering activity rather than the preserve of the computer specialist. Project phasing The development of a mathematical description of a process plant requires coordination of information from conceptual design to operation management. The activities required to build and operate a process plant are divided into four basic chronological activities or phases. These activities are often undertaken by different organizations and disciplines. As a result, continuity is often lost with the resultant loss of critical design data. The major activities are considered to be: conceptual and flowsheeting; detailing around the P & ID; building and commissioning; and plant operation. The CAD system described provides a design tool to be used for each of these activities, as well as providing continuity between the activities and the disciplines involved. The heart of the system is the dynamic simulation of the flowsheet. Each of the activities will be discussed, leading to two simple examples that demonstrate the use of the simulator. Figure 1 shows a schematic format of the various activities and the path followed by the dynamic flowsheet simulator in the life of a project. Flowsheet development The prime requirements in the design and develop¬ment of a process flowsheet are • selection of the correct unit operations to achieve the most economic (capital and operating) beneficiation of the specified reserve ; • the sizing of the unit operations to achieve the desired results, as a function of the projected feed rates etc., to handle the time related (dynamics) of the process; and • the production of a set of engineering documents showing the drawn and labeled flowsheet with an equipment list and process specification for each of the unit operations. The question may well be asked at this stage why dynamic flowsheet simulation should be considered when steady state modeling has been found to be adequate to date. With the increases encountered in the cost of capital, one often cannot afford the luxury of designing around the compounding worst case technique. Further, a more accurate design of the control surges can be achieved. No information is lost in that the steady state solution is in fact a subset of the dynamic model. In generalized state space modeling, the differential equations describing the process dynamics are illustrated in the following matrix notation: XDOT=A.X+B.U(1) Y =C.X+D.U(2) where XDOT describes the set of first order derivatives of the system state Vector, and X- is the system state Vector; A - is the system matrix operator which in the general nonlinear case is both a function of X and time ; U- is the process input vector; B - is the input mapping matrix; Y - is the set of observations; C - is the output mapping matrix which maps X - onto Y; and D- maps the input onto the observations. Thus, by time integration of the system dynamic equations, described in (1), the dynamic trajectory away from any set of initial conditions can be deter¬mined. Further, by finding the conditions at which XDOT = 0, the steady state solution can be determined.
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