**5.3 Modelling of control systems**

The Distributed Control System (DCS) of a power plant is a group of Programmable Logic Controllers (PLC) where all the control algorithms are executed in an automatic way. A DCS is a very complex system involving many thousands of signals and hundreds of diagrams. The control algorithms are organized in components with specific function or task, for instance: PID controllers, high/low detectors, timers, memories set/reset, etc. This organization is represented by means of a network of these components, which communicate information through connections, (Figure 14). These networks are organized in a hierarchical way, in the bottom levels are the basic elements like AND, OR, NOT gates, in the middle level are the diagrams, and finally in the top level are the modules. In this way, the DCS is constituted by a collection of modules.

Fossil Fuel Power Plant Simulators for Operator Training 117

been proven and documented. It is important to mention that, simulators are a very important part of these programmes, but their value as training tool is maximized when they are integrated in well-designed and structured training courses. The ADDIE model is a

The increase of power computing and the development of friendly graphical user interfaces had two main effects over the simulators; on the one hand, the power plants have replaced their former control boards with personal computers with graphical user interfaces. Naturally, the operators of these plants need a suitable training because they face a complete change in their operation paradigm, and because of this, the training simulators also require a HMI as the ones in the actual plants. On the other hand, a complete simulator can be installed in a single PC, with no demerit of the scope of the mathematical modelling or its real-time functioning. Furthermore, web services and cloud computing extend the training options, because specific training objectives can be fulfilled just with a PC with an internet connection. This kind of applications make possible to reach a big number of trainees with no necessity of: transporting personnel to a training centre, transporting a simulator to different places, or acquiring a simulator. Another important aspect is the inclusion of expert systems in a training simulator. This option is suitable for standalone applications which require reducing or even eliminating the necessity of a human instructor. A convenient knowledge representation of the expert gives to the simulation system all the

In the Object-Oriented Programming, an object is the mathematical model of a power plant component and the integration of these objects reflects the physical plant layout. The interactions among the components are satisfied with connectors, which are also related with the actual physical connections; this type of approaches simplifies the construction of simulators and provides a direct relation between the physical and simulated systems.

acslX (2010). acslX Software for Modeling and Simulation of Dynamic Systems and Processes, 21.09.2011, Available from http://www.acslx.com/products/ Ahmad, A.L.; Low, E.M. & Abd Shukor, S.R. (2010). *Safety Improvement and Operational* 

Arjona, M.; Hernández, C. & Gleason, E. (2003). *An Intelligent Tutoring System for Turbine* 

Alam-Jan, S.; Šulc, B. & Neuman, P. (2002). Object Oriented Modeling of a Training

Burgos, E. (1993). *Simulador de Rodado de Turbine para el Adiestramiento de Operadores*, Boletín

Cameron, D.; Clausen, C. & Morton, W. (2002). Chapter 5.3 Dynamic Simulators for

R., pp. 393-432, Elsevier, ISB N: 0-444-50827-9, The Netherlands.

*Enhancement via Dynamic Process Simulator: A Review*, Chemical Product and Process

*Startup Training of Electrical Power Plant Operators*. Expert Systems with

Simulator, *Proceedings International Carpathian Control Conference ICCC' 2002,* pp

Operator Training, In: *Software Architectures and Tools for Computer Aided Process Engineering-Computer-Aided Chemical Engineering, Vol. 11)*, Braunschweig, I. & Gani,

suitable methodology to get this goal.

**7. References** 

elements to conduct a training session in an autonomous way.

Modeling: Vol. 5, No. 1, Article 25, pp 1-25.

757-762, May 27-30, 2003. Malenovice, Czech.

Applications, Vol. 24, No.1, pp. 95-101.

IIE, Vol. 17, No. 4 pp. 167-172.

Fig. 14. Control diagram of a DCS

One of the most viable approaches to simulate the DCS is the translation of the control algorithms of the actual power plant; this guarantees a full reproduction of all control loops, alarms and signals to the HMI. In the context of a simulator and according to the methodology described by Romero-Jiménez et al. (2008), the translation procedure involves mainly the next tasks:


In the case of small control systems or when the control loops are not included in the DCS for its translation, these control algorithms can be developed by means of a graphical tool like VisSim (VisSim, 2011), using as reference the SAMA diagrams of the actual power plant. VisSim provides almost all the basic modules required to model control systems and generates C code, so it can be easily coupled to the simulator solver. In such way, the SAMA diagrams can be drawn totally in the VisSim environment to reproduce the required control. As expected, it is necessary coding in a manual way the modules with a specific function do not available in the VisSim libraries.
