Development and comparative analysis of mathematical models for the functioning of the regional power system of the Samara region
Journal of Samara State Technical University, Ser. Physical and Mathematical Sciences, Tome 28 (2024) no. 3, pp. 586-608.

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Systematic research into the operations of the regional power system aimed at improving the efficiency of energy complex management, taking into account the contribution of utilized resources, is fundamentally impossible without the enhancement of mathematical models and methods for their identification based on statistical data. This article presents the results of an analysis of a well-known mathematical description of the functioning of the regional power system, highlighting significant shortcomings that negatively impact both the reliability of assessments of key performance indicators of the energy complex and the accuracy of forecasts made based on the constructed model. The study examines and systematizes various three-factor regression models and covariance-stationary time series models based on linear and nonlinear regression into three main groups. Algorithms for numerical methods of least squares estimation of the parameters of these models based on observational results are described. Results of mathematical modeling of the dynamics of energy system output based on statistical data published in the annual reports of regional ministries and energy companies are provided. A statistical analysis of the obtained results is conducted. A comparative analysis of the developed mathematical models based on forecast error assessment allowed for the selection of the most effective mathematical model with minimal forecasting error from the considered set of models over a time period ranging from one to five years.
Keywords: regional energy system, multiplicative power-law production function, factor elasticity, covariance-stationary time series models, autoregressive models, statistical analysis
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V. E. Zoteev; L. A. Sagitova; A. A. Gavrilova. Development and comparative analysis of mathematical models for the functioning of the regional power system of the Samara region. Journal of Samara State Technical University, Ser. Physical and Mathematical Sciences, Tome 28 (2024) no. 3, pp. 586-608. http://geodesic.mathdoc.fr/item/VSGTU_2024_28_3_a8/

[1] Gavrilova A. A., Capenko M. V., “Synthesis of mathematical models of the regional energy system as multidimensional production functions”, Vestn. Samar. Gos. Tekhn. Univ., Ser. Techn. Nauki, 2002, no. 14, 126–192 (In Russian)

[2] Kolmykov D. S., Gavrilova A. A., “Model analysis of the operating efficiency of regional energy production”, Proceedings of the Third All-Russian Scientific Conference (29–31 May 2006). Part 2, Matem. Mod. Kraev. Zadachi, Samara State Technical Univ., Samara, 2006, 93–96 (In Russian)

[3] Diligensky N. V., Gavrilova A. A., Salov A. G., Gavrilov V. K., “Modeling performance analysis of combined generation of heat and power energy of regional power system”, Izv. Vyssh. Uchebn. Zaved. Severo-Kavkazsk. Region. Tekhn. Nauki, 2008, no. 5, 37–40 (In Russian)

[4] Salov A. G., Gavrilova A. A., “System analysis and modeling of the activities of energy generating enterprises in order to assess the efficiency of their functioning in the context of the formation of market relations”, Vestn. Saratov. Gos. Tekhn. Univ., 1:1 (2008), 86–91 (In Russian)

[5] Salov A. G., Gavrilova A. A., Ivanova D. V., “Study of the economic characteristics of the regional industrial complex using statistical and modeling analysis methods”, Nauchnoe Obozrenie, 2015, no. 15, 327–332 (In Russian)

[6] Salov A. G., Gavrilova A. A., Knyazev P. A., Kruglov V. A., “Simulation model of region energy system on the base of three-factor production function”, Urban Construction and Architecture, 2016, no. 3, 140–145 (In Russian) | DOI

[7] Ivanova D. V., Salov A. G., Gavrilova A. A., “Control algorithms development for manufacturing and economic systems activity”, J. Phys.: Conf. Ser., 1111 (2018), 012073 | DOI

[8] Gavrilova A. A., Salov A. G., Sistemnaia metodologiia analiza i modelirovaniia energoeffektivnosti generiruiushchikh kompanii [System Methodology for Analysis and Modeling of Energy Efficiency of Generating Companies], Nauchno-tekhnicheskii Tsentr, Samara, 2021, 277 pp. (In Russian)

[9] Abramov A. P., Bessonov V. A., Nikiforov L. T., Sviridenko K. S., Issledovanie dinamiki makroekonomicheskikh pokazatelei metodom proizvodstvennykh funktsii [Study of the Dynamics of Macroeconomic Indicators by the Production Functions Method], Computing Center of the USSR Academy of Sciences, Moscow, 1987, 62 pp. (In Russian)

[10] Zamkov O. O., Tolstopiatenko A. V., Cheremnykh Yu. N., Matematicheskie metody v ekonomike Mathematical Methods in Economics, Moscow State Univ., Moscow, 1997, 368 pp. (In Russian)

[11] Zoteev V. E., Bashkinova E. V., Starokvasheva P. V., “Mathematical modeling of the functioning of the energy system of the Samara region”, Perspektivnye informatsionnye tekhnologii (PIT 2020), Proceedings of the International Scientific and Technical Conference, Samar. Nauchn. Tsentr RAN, Samara, 2020, 361–365 (In Russian)

[12] Vuchkov I., Boyadjieva L., Solakov O., Prikladnoi lineinyi regressionnyi analiz [Applied Linear Regression Analysis], Finansy i Statistika, Moscow, 1987, 238 pp. (In Russian)

[13] Draper N. R., Smith H., Applied Regression Analysis, Wiley Series in Probability and Statistics, John Wiley and Sons, New York, 1998, xvii+706 pp. | DOI | Zbl

[14] Demidenko E. Z., Lineinaia i nelineinaia regressii [Linear and Nonlinear Regression], Finansy i Statistika, Moscow, 1981, 302 pp. (In Russian)

[15] Seber G. A. F., Lee A. J., Linear Regression Analysis, Wiley Series in Probability and Statistics, Wiley, Hoboken, NJ, 2003, xvi+557 pp. | Zbl

[16] Box G. E. P., Jenkins G. M.; Reinsel G. C., Ljung G. M., Time Series Analysis. Forecasting and Control, Wiley Series in Probability and Statistics, John Wiley and Sons, Hoboken, NJ, 2016, 712 pp. | Zbl

[17] Anderson T. W., The Statistical Analysis of Time Series, Wiley Classics Library, John Wiley and Sons, Chichester, 1994, xiv+704 pp. | Zbl

[18] Kendall M. G., Stuart A., The Advanced Theory of Statistics, v. 3, Design and Analysis, and Time-Series, Charles Griffin, London, 1976, x+585 pp. | Zbl

[19] Otnes R. K., Enochson L., Applied Time Series Analysis, v. 1, Basic Techniques, John Wiley and Sons, New York, 1978, xiv+449 pp. | Zbl

[20] Kashyap R. L., Ramachandra Rao A., Dynamic Stochastic Models from Empirical Data, Mathematics in Science and Engineering, 122, Academic Press, New York, 1976, xvi+334 pp | DOI

[21] Durbin J., Watson G. S, “Testing for serial correlation in least squares regression: I”, Biometrika, 37:3/4 (1950), 409–428 | DOI | Zbl

[22] Granovsky V. A., Siraya T. N., Metody obrabotki eksperimental'nykh dannykh pri izmereniiakh [Methods of Processing Experimental Data in measurements], Energoatomizdat, Leningrad, 1990, 288 pp. (In Russian)

[23] Zoteev V. E., “A numerical method of nonlinear estimation based on difference equations”, Vestn. Samar. Gos. Tekhn. Univ., Ser. Fiz.-Mat. Nauki [J. Samara State Tech. Univ., Ser. Phys. Math. Sci.], 22:4 (2018), 669–701 (In Russian) | DOI | Zbl