OPC based distributed real time simulation of complex continuous processes

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Abstract

This paper presents a methodology for the development of distributed process simulation using OPC (OLE for Process Control). The distributed components operate as OPC servers enclosing continuous simulations developed with the simulation language EcosimPro. The paper presents the problems related to data interchange and synchronisation in real time and the solutions adopted and gives results about the performance of OPC in this kind of applications. The methodology has been applied to a large process simulator of a beet sugar factory used for control room operator training. This includes a process simulation operating in a network of six computers, a SCADA system for operation on the process, an instructor console and the corresponding software for real time communication and synchronisation. The main advantages of this approach are: (i) independence of the development of the simulation from the communication mechanisms, (ii) access to the simulations by a wide range of applications, due to the standard provided by OPC, (iii) use of low cost conventional equipment and (iv) support for large scale simulations.

Introduction

There are an increasing number of simulation applications which size exceed the computational capacities of conventional computers, mainly if real time execution of the simulated models is required. One solution for this problem that is been adopted in an increased number of applications is based on distributing the computational load among a set of interconnected computers. Instead of running a big size simulation in a single computer, the simulation is divided in several modules, each of them suitable for running in a computer at the desired speed. In this way the simulation is performed in parallel in a computer network gaining benefit of the increased computational power.

Key elements in distributed simulation are the partitioning of the simulation among the different modules, the interchange of data between them along the simulation time and the synchronisation of the execution of the modules.

Criteria that can be used for the division of a simulation in modules are quite wide, ranging from selecting modules that correspond to physical elements such as process units, to looking for minimum number of interconnections among the modules, or for interconnections involving variables that present the smoothest changes.

For the distributed execution of simulations there are several software environments that provide data interchange and synchronisation services, among them, for instance, HLA and CAPE-OPEN. The High Level Architecture (HLA) [15] is a standard of the Defense Modeling and Simulation Office [8] of the Department of Defense of USA (DoD) [7], that have their own communication and synchronisation libraries called Runtime Infrastructure (RTI). On the other hand, CAPE-OPEN (Computer Aided Process Engineering Open Simulation Environment) [5], [6] is the result of an European Union joint project and instead of providing libraries for communication, it specify the component interfaces for two middlewares, OMG CORBA [13], [16] and Microsoft DCOM [11], [12]. In both cases, the common idea is the development of a set of specifications on the modules or components so that they can be developed and re-used easily.

In this paper we approach the topic of distributed simulation from the perspective of the requirements imposed by the development of simulators for control-room operators training in the process industries. These simulators combine a real-time simulation of the process, usually the whole factory, with a SCADA (Supervisor Control And Data Adquisition System) that acts as human interface and an instructor module for supervision and problem generation. The process simulation has been developed in the simulation environment EcosimPro [9]. It disposes of a modern object oriented modelling language named EcosimPro Language (EL) that supports both, continuous and discrete event systems, and incorporates state of the art integration algorithms for solving (sparse) DAE models. Two important characteristics are: first, that the computational causality of the mathematical models is not predetermined, so that these can be re-used in different contexts, and second, that the simulation models is generated as a C++ class that can be integrated in any C++ application.

Typical process models involve several thousand DAE equations so that for real time operation with today’s PC’s the simulation has to be distributed among several computers. Besides the HLA and CAPE-OPEN mentioned before, it is possible to take advantage of the generated C++ code and develop directly software components as DCOM y CORBA, but, taking into account the context in which these simulators are used, an attractive alternative is to use OPC (OLE for Process Control) [1], [10], [14] an emerging technology based on DCOM that has gained wide acceptance and became a “de facto” standard in the process industry for communications among devices. Adding a OPC layer to the simulation code allows a simulation not only to interchange data with other simulations in a distributed environment, but to be accessed by a wide range of applications and control equipment, including distributed control systems (DCS), SCADAs, PLCs, etc., opening the door to other applications such as hardware-in-the loop test, etc.

This paper study the problem of implementation of OPC interfaces in distributed continuous simulations and gives results of its application in a plant wide simulator of a sugar factory. The simulation language considered is EcosimPro but the methodologies and results are valid independently of the simulation environment.

The paper is organised as follows: After the introduction, Section 2 gives an overview of EcosimPro and Section 3 introduces OPC. The methodology for the development of distributed simulation applications is given in Section 4, while Section 5 describes the structure of the OPC server. The distributed simulation based on OPC servers is considered in Section 6 as well as some tools developed for the automation of the proposed methodology and, finally, Section 7 describes its application to a practical industrial case of a sugar factory. The paper ends with some conclusions and bibliography.

Section snippets

EcosimPro

EcosimPro belongs to the family of the simulation tools that support the so called object oriented modelling languages (OOML, whose main exponent is Modelica), such as gPROMS, Abacus, Dymola, MathCore, etc. in the sense that they support non-causal models able to be modified automatically according to the context in which they are used. This means that the user can specify different boundary conditions without modifying the model code, and EcosimPro will manipulate symbolically the equations to

OLE for Process Control (OPC)

OPC consists of a standard set of interfaces, properties and methods that can be used for device communication in process control and manufacturing applications. OPC is based on Microsoft DCOM (Distributed Component Object Model) technology. It is managed by the OPC Foundation, supported by the majority of the companies that operate in the process control sector.

Its main objective is providing an uniform access to data in industrial applications, in such a way that several clients can access

A methodology for the development of distributed simulations with EcosimPro

In this section the different steps in the construction of a distributed simulation will be described. These include, for each node of the network, generating the EcosimPro code and developing of the corresponding OPC server, as displayed in Fig. 2. It will be followed by the distribution of the simulations and the management of the environment. As a reference, we will consider the specific case of a simulator for operator training in process factories. This includes, not only a distributed

Generation and structure of the OPC server

Each distributed simulation module, besides the simulation code, has two main parts: the thread that handles the advance of the simulation, and the OPC server, which includes the access to the simulation (Fig. 8).

The OPC servers will be executed in a Windows NT or upper environment. Windows NT is a multitasking operating system, but not a real-time system. If desired it is possible to use a real-time patch, but this it not the case. In the servers, in order to advance the simulation

Simulation granularity

When an OPC server operates in a distributed real time environment, there are, at least, two important problems to be taken into account: Timing of the simulation and consistence of the integration of the distributed modules.

In order to obtain a real time progress of the simulation we synchronize it at given time intervals. This is obtained advancing the simulation as-fast-as-possible until the next time interval, and then, if the time used in this computation is less than the time interval,

A practical application in a sugar factory

The proposed methodology and tools were applied to an industrial, large scale process: a beet-sugar factory [2], [3]. The purpose was testing them and developing a simulator for control room operator training.

Modern process factories are highly automated, so that only a small number of operators are necessary to command the factory from a control room using a DCS or similar control equipment. As a result of it, they have a considerable responsibility, both in the normal operation of the plant

Conclusions

This paper presents a methodology for the development of distributed process simulation using OPC. The distributed component operates as OPC servers enclosing continuous simulations developed with the simulation language EcosimPro.

The use of OPC has many advantages and has been adopted by most of the companies in the process control sector as a standard for communications among control and instrumentation equipment. Its use has been tested in the paper in a distributed continuous process

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