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Monitoring System for Co-generative Power Plants

Ion MICIU1, Florin HĂRŢESCU2
1 IPA SA – Automation Engineering;
169 Calea Floreasca, 14495 Bucharest, Romania
ionmiciu@ipa.ro
2 I C I Bucharest
(National Institute for R & D in Informatics)

8-10 Averescu Blvd.
011455 Bucharest 1, Romania
flory@ici.ro

Abstract: Electric power systems are an integral part of the way of life in modern society. The electricity supplied by these systems has proved to be a very convenient, safe and clean form of energy. The monitoring of the gas co-generative processes is the main source of information for the technological and economic management. Based on a high performance system, a real-time model provides a permanent updated image of the efficient working status of the electrical power process, providing beside the direct acquired information complex calculations of specific consumptions. The purpose of the automatic functioning of the entire co-generative power plant is the optimisation of the co-generative electrical energy commissioning in the national energy system and the commissioning of thermal energy to the consumers.

Keywords: Electric power systems, Co-generative gas power plant, Control of distributed parameter systems, Distribution Management System, Process control, Optimisation, Simulation, Real time systems.

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CITE THIS PAPER AS:
Ion MICIU, Florin HĂRŢESCU, Monitoring System for Co-generative Power Plants, Studies in Informatics and Control, ISSN 1220-1766, vol. 18 (4), pp. 379-388, 2009.

1. Introduction

Most of the electric power plants have been subject to a continuous step-by-step modernization process lately. In many cases this process ended with the purchase and installation of a variety of modern equipment and software applications, which was satisfactory for a certain level of development of the power plant.

Obviously, this challenging goal can only be achieved, at a reasonable level of investment, by integration of the all existing sources of information on the power plant – equipment and software applications.

Automation systems use more and more communication systems to be able to carry out their task properly. Therefore, today it’s already available a wide catalogue of products that allows the embedded systems used for the automation to interface to one or more field bus networks and to one or more wide range communication networks such as telephone network, Internet, PROFIBUS etc.

Most of the co-generation systems can be characterized as topping systems or as bottoming systems.

In the topping systems, a high temperature fluid (residual gas, steam) fuels an engine for producing electricity, while the low temperature agent is utilized in thermal processes for heating / cooling the extent.

In the bottoming systems, the high temperature agent is produced mainly for a process, for example, in a furnace, or a cement oven; after the end of this process, the hot gases are used directly for powering a gas turbine if the pressure is proper, or indirectly for producing steam in a recuperation boiler, after which is used for powering a generator with steam turbine.

The system presented is based on a RT-ARCH (Real Time ARCHitecture), architecture of software tools used in process control. The system is composed by classical algorithms running on a network of PLC-s and controlling algorithms implemented in a process computer.

Some of them are typical numerical algorithms, and the others are adaptive control algorithms.

REFERENCES

  1. HĂRŢESCU, F., RT-ARCH – A New Approach in Real Time Application Design, IASTED Mini and Microcomputers and Their Applications, Lugano, Switzerland, June, 1990.
  2. EREMIA, M., Electric Power Systems, Editura Academiei Române, Bucureşti, 2006.
  3. MICIU, I., F. HĂRŢESCU, Integrated System for Control and Monitoring in Real Time of Efficient Electrical and Thermal Energy Production, – Proceedings of the 8th Conference on Applied Informatics and Communications, Rhodes, Greece, 2008.
  4. VETTER, M., C. Wittwer, Model-based Development of Controller Strategies for Domestic Fuel Cell Cogeneration Plants.
  5. MANOLAS, D. A., C. A. FRANGOPOULOS, T.P. GIALAMAS, D. T. TSAHALIS, Operation Optimisation of an Industrial Cogeneration System by a Genetic Algorithm.
  6. MASAHIDE, Y., U. TSUNEO, Y. JUN’ICHI, S. KASUMASA, Optimal Design of Cogeneration Systems by Using Hamiltonian Algorithm.
  7. MĂDĂRĂŞAN, T., M. BĂLAN, Termodinamica tehnica, Editura Sincron, Cluj-Napoca, 1999.
  8. KIRILLIN, V. A., V. V. SICEV, A. E. SEINDLIN, Termodinamica, E. S. E. Bucuresti, 1985.
  9. VLADEA, I., Tratat de termodinamica tehnica si transmiterea caldurii, E. D. P. Bucureşti.
  10. STEPHAN, K., F. MAYINGER, Thermodynamik, Band 1 und 2, Springer – Verlag Berlin / Heidelberg, 1992.
  11. HAHNE, E., Grundlagen der Technischen Thermodynamik Band 1 und 2, Insitut furThemodynamik und Warme technik der Universitat Stuttgart.
  12. LIPPER, T., H. SETETTER, P. KRZYSLAK, Calculation and Diagnosis of Thermal Cycles inApplication, in: Proc. Xth Int. Conf. ” Steam and Gas Turbines for Power and CogenerationPlants. Karlovy Vary, Czech Republic Oct. 1994, pp. 178-187.
  13. ASTROM K., J. WITTENMARK, Adaptive Control, Addison Wesley Company, 1989.
  14. DUMITRACHE, I., Intelligent Techniques for Control Applications, The 9th CSCS Conference, May 1993.
  15. CICHOCKI, A., R. UNBEHAUEN, Neural Netwarks for Optimization and Signal Processing, John Wiley & Sons, Ltd. 1993.
  16. FLEMING, P. J., Application of Multiobjective Optimization to Compensator Design for SISO Control Systems, Electronics Letters, Vol.22.
  17. FLEMING, P. J., Computer-Aided Control System Design of Regulators using a Multiobjective Optimization Approach, Proc. IFAC Control Applications of Nonlinear Optimization.
  18. GILL, P. E., MURRAY, W., Numerical Linear Algebra and Optimization, Vol.1, Addison Wesley.
  19. SELIC, B., P. T. WARD, The Challenges of Real Time Software Design, Embedded Systems Programming, Miller Freemans Inc., Oct. 1996.
  20. SELIC, B., G. GULLIKSONS, P. T. WARD, Real Time Object Oriented Modelling, John Wiley & Sons, 1994.
  21. WANG, W., Designing Secure Mechanisms for Online Processes.
  22. HAUSLEIN, A., PAGE B., Knowledge-based Approaches to Modelling and Simulation Support. Systems Analysis, Modelling Simulation 8 (1991), 4/5, pp. 257-272.
  23. HĂRŢESCU, F., M. COSMA, S. TEODORESCU, Nonstop-32, A Fault-tolerant System Used in Metallurgical Plants, Studies in Informatics and Control, 1993.
  24. HĂRŢESCU, F., C. DANILOV, M. COSMA, L. NEDELCU, Real Time Tools for Building Automation Applications Generator, Studies in Informatics and Control, 1997.