Use of pre-commissioning results to develop, tune and validate the operator intelligent support system at unit № 1 of novovoronezh NPP II
The AES#200 power unit control concept contains requirements to the information support of control in different operating modes to be implemented as part of the unit’s automated process control system (APCS). The requirements include standard APCS functions intended for the primary processing of measurement data, organization of alarms, arrangement of archives, presentation of measured, calculated and diagnostic data, as well as to monitor the status of critical safety functions.
The list lacks the function that is essential for the safe and reliable operation of equipment. This is the capability to analyze the course of the process in real time and prospectively which makes it possible to provide the operator with the guidance on the best way to control the process, specifically in situations with a limited time available for decision#making.
Therefore, a decision was made in 2014 by Novovoronezh NPP, VNIIAES and JSC «SNIIP-Atom» to develop an operator intelligent support system (OISS) to be a part of the top level system at unit 1 of Novovoronezh NPP II. A software model of the unit was built as part of this work to operate in the OISS.
The fundamentals of the OISS construction are discussed. Operating data obtained in the process of pre#commissioning are used to validate the model.
Two individual cases are considered to illustrate the process of the computational model adaptation based on test results: – determination of model characteristics for the reactor coolant pumps; – fine tuning of the steam generator water level regulators.
The data obtained at the commissioning stage of Novovoronezh II’s unit 1 are used to adjust and perfect the OISS mathematical process models.
- Gelovani V.A., Bashlykov A.A., Britkov V.B., Vyazilov E.D. Intellectual decision support systems in emergency situations. Moscow. Institute of System Analysis RAS, 2001, 304 p. (in Russian)
- Lebedev V.G. Principles of constructing an intelligent user interface for decision support systems by the operator. Problemy upravleniya, 2004, no. 3, pp. 43-47 (in Russian).
- Nechaev Y.I., Petrov O.N. Information support of the operator in the analysis of complex situations. State Marine Technical University of St. Petersburg, 2007. Available at http://www.ict.edu.ru/vconf/files/9223.pdf/ (accessed Jun 26 2017) (in Russian).
- Britkov V.B. Communication Emergency Decision Support Systems Integration. The International Emergency Management Society Conference National and International Issues Concerning Research and Applications. Copenhagen, Denmark, 1997, pp. 395-403.
- Britkov V.B. Distributed System for Emergency Decision Support With System Analysis And Modern Information Technology Implementation. Proc. of the International Emergency Management and Engineering Conference. Montreal, Canada, 1996, pp. 87-92.
- Germond A.J, Niebur D. Survey of Knowledge-Based System in Power System Europe, Proc. IEEE, May 1996, v. 80, no. 5, pp. 732-744.
- Kirscher D.S., Wollenberg B.F. Intelligent Alarm Processing in Power Systems, Proc. IEEE, May 1996, v. 80, no. 5, pp. 663-672.
- Leibowitz J. An Expert System Forecast. Journal of Information Systems Management, Spring 1994, pp. 69-72.
- Nelson W.B. REACTOR: An Expert System for Diagnosis and Treatment of Nuclear Reactor Accident. Proc. of the IIConference of American Association Artificial Intelligence. Aug. 1983, pp. 296-301.
- Shaw R.W. Adapting the RAINS model to develop strategies to reduce acidification in the USSR. Proc. of International Institute for Applied System Analysis, Austria, 1990, pp. 184-188.
- Yeremeyev A.P. A Parallel Model for a Production System of the Tabular Type. Soviet Journal of Computer and Systems Sciences. July-August 1991, v. 29, no. 4, pp. 80-88 (in Russian).
- Bashlykov A.A. SPRINT-RV – intelligent information system for real-time decision support when managing complex modes of operation of ecologically dangerous objects and technologies on the basis of industrial computers. Pribory. 2001, no. 2, pp. 24 -26 (In Russian).
- Sobajic D.J., Pao Y.H. An Artificial intelligence system for power system contingency screening, IEEE Transaction on Power Systems. 1988, v. 3, no. 2, pp.647-653.
- Rouse W.B Models of human problem solving detection, diagnosis and compensation for system failures. Automatica. 1983, v. 19, no. 6, pp. 613-625.
- Lee D.T. Expert Decision-Support Systems for Decision-Making. Journal of Information Technology. 1988, v. 3, no. 2, pp 85-94.