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An approach to coordination of power generating units

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The importance of the problem of power generating facility identification is justified against the background of interconnection of the European and Russian power grids. Intelligent control techniques for power generation facilities are presented. A methodology for estimating the dynamics of participation of the power grid generating facilities in the overall primary frequency regulation in contingency situations is developed based on frequency and generating capacity time series. Process identification algorithms, based on virtual model design using process data archives and knowledge bases, are discussed. Associative search methods are used for identification algorithm development.
Rocznik
Strony
305--318
Opis fizyczny
Bibliogr. 29 poz., wykr.
Twórcy
autor
Bibliografia
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  • BAKHTADZE, N., LOTOTSKY, V., MAXIMOV, E. and PAVLOV, B. (2007) Associative Search Models in Industrial Systems. IFAC International Workshops Intelligent Assembly and Disassembly (IAD’07) & Intelligent Manufacturing Systems (IMS’07). 1, 120-126.
  • CHUKREEV, YU.YA., KHOKHLOV, M.V. and ALLA, E.A. (2000) Supervisory control of regional power grid states using artificial neuron network technology (in Russian). Elektrichestvo 4, 2-10.
  • GAVRILOV, A.V. (2002) The Model of Associative Memory of Intelligent System. In: Proc. 6th Russian-Korean International Symposium on Science and Technology. CityplaceNovosibirsk. 1, 174-177.
  • GJELSVIK, T., RTTING, A. and RYNSTRAND, J. (1992) Long-term scheduling of hydro-thermal power systems. In: Proc. 2nd Int. Conf. Hydropower, 539-546.
  • GONZALEZ, C., JUAN, J., MIRA, J., PRIETO, F.J.and SANCHEZ, M.J. (2003) Long-term generation scheduling in systems with large hydro resources in a deregulated electric power market. Power Engineering Society General Meeting, IEEE, 1, 323-326.
  • HUNT, E. (1989) Cognitive Science: Definition, Status and Questions. Annual Review of Psychology, 40.
  • KANG, CH., GUO, L., BAI, L., XU, R., HE, J., XU, K. (2006) Joint analysis of power system reliability and market price considering the uncertainties of load forecasts. In: International Conference on Power System Technology. MK4-02 C0614.
  • KOZHEVNIKOV, D.A. (2008) System operator’s infrastructural role increases (in Russian). Promyshlenny Yezhenedel’nik, 8, 236-239.
  • KRAFTNAT, S. (2000) The system operator’s role and challenges in an open market environment. Power Engineering Society IEEE Winter Meeting 2 (1), 822-830, 2000.
  • LARICHEV, O.I., ASANOV, A., NARYZHNY, Y. and STRAHOV, S. (2001) ESTHER. Expert System for the Diagnostics of Acute Drug Poisonings. Proc. 21st SGES International Conference on Knowledge Based Systems and Applied Artificial Intelligence. Springer, Cambridge, 159-168.
  • MO, B., GJELSVIK, A. and GRUNDT, A. (2001) An integrated risk management of hydro power scheduling and contract management. IEEE Trans. Power Systems 16, 216-221.
  • MURTY, P.S.R. (2005) Operation & Control in Power Systems. BS Publication.
  • NEWELL, A. and SIMON, H.A. (1972) Human Problem Solving. Prentice Hall, Englewood Cliffs, NJ.
  • NOVITSKY, D.A. (2008) Power system state planning for reliability provision (in Russian). Proceedings of the Press Conference in Power Ministry of Russian Federation.
  • OPPEL, L.J. and ARONSON, D. (1999) Information technology. Its increased importance in the power industry after deregulation. Power Engineering Society Summer Meeting, IEEE. 2 (1), 1196-1199.
  • OU, Y. and SINGH, C. (2003) Calculation of risk and statistical indices associated with available transfer capacity. IEEE Proceedings. Generation, Transmission & Distribution, 150 (2).
  • PATEL, V.L. and RAMONI, M.F. (1997) Cognitive Models of Directional Inference in Expert Medical Reasoning. In: P. Feltovich, K. Ford and R. Hofman, eds., Expertise in Context: Human and Machine. AAAI Press, Menlo Park, CA.
  • PEREIRA, M. (1989) Optimal stochastic operations scheduling of large hydroelectric systems. Int. J. Electr. Power Energy Syst. 11, 161-169.
  • PIRAS, A. (1996) A multiresponse structural connectionist model for short term electrical load forecasting. EPFL, Lausanne.
  • PRIKHNO, V.L. (2004) Hierarchical principles of steady state models development based on telemetry information (in Russian). Transactions of the Institute of Electrodynamics of Ukrainian National Academy of Sciences. Kiev, 147-148.
  • RZEWUSKI, M. ET AL. (1999) Economic load dispatch problem solving using global optimization algorithms (in Polish). Nat. Conf. on Evolutionary Computation and Global Optimization, Potok Zoty, Poland, 275-282.
  • SHEBLE, G.B. and FAHD, G.N. (1994) Unit Commitment literature synopsis. IEEE Trans, on Power Systems 9 (1), 128-135.
  • STOFT, S. (2002) Power System Economics. IEEE Press.
  • TAKAGI, T. and SUGENO, M. (1985) Fuzzy identification of systems and its applications to modeling and control. IEEE Trans. Systems Man Cybernetics 26 (1), 116-132.
  • VOROPAI, N.I. and HANDSCIN, E.J. (2001) Liberalization and modernization of power systems. IEEE Power Engineering Review 21 (1), 16-19.
  • ZAKHAROV, V.N. and ULYANOV, S.V. (1995) Fuzzy models of intelligent industrial controllers and control systems. II. Evolution and principles of design. Journal of Computer and Systems Sciences International 33 (2), 102-106.
  • ZHU, CH., JIANZHONG, Z., JUNJIE, Y. and WEI, W. (2006) Optimal scheduling of hydropower plant with uncertainty energy price risks. International Conference on Power System Technology. MK1-07 C1345.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0045-0032
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