ORIGINAL PAPER
Combined model of optimal electricity production: evidence from Ukraine
More details
Hide details
1
Department of International Economic Relations, Sumy State University, Ukraine
2
Department of Management, Sumy State University, Ukraine
3
Economic Cybernetics Department, Sumy State University, Ukraine
Submission date: 2021-08-28
Final revision date: 2021-12-16
Acceptance date: 2021-12-16
Publication date: 2022-03-25
Corresponding author
Yuliia Halynska
Department of International Economic Relations, Sumy State University, Sumy, Ukraine
Polityka Energetyczna – Energy Policy Journal 2022;25(1):39-58
KEYWORDS
TOPICS
ABSTRACT
The article proposes a methodology for the formation of a combined model of the equilibrium values of pricing and the volume of electricity production, taking into account green and traditional sources of electricity production on the example of Ukraine. In accordance with the projected price and volume of electricity production in 2021, a model for redistributing electricity sources were considered, taking into account the minimization of budgetary resources and the risk of electricity production with appropriate restrictions in the production of various types of electricity and their impact on minimizing the price for the end user.
The studies have shown that important factors in the formation of electricity prices are indicators of the cost and volume of production, distribution and transportation of electricity to consumers, which largely depends on the formation and further development of the energy market in Ukraine. Also, the redistribution of the volumes of traditional and non-traditional electricity in the common “pot” is of great importance while minimizing risks and budgetary constraints. Balancing the system for generating electricity from various sources will help not only optimize long-term electricity prices and minimize tariffs for the end user, but also allow planning profit in the form of long-term market return on investment.
The analysis of the results showed that the optimal distribution of energy production makes it possible to obtain energy resources in the required volume with lower purchase costs and with minimal risk.
METADATA IN OTHER LANGUAGES:
Polish
Połączony model do optymalizacji produkcji energii elektrycznej: przykład Ukrainy
optymalna produkcja energii elektrycznej, taryfy energii elektrycznej, model połączony, tradycyjne źródła, zielone taryfy, oszczędność zasobów
W artykule proponowano metodologię tworzenia modelu łączącego równowagę ceny i wielkość produkcji energii elektrycznej, biorąc pod uwagę zielone i tradycyjne źródła produkcji energii elektrycznej na przykładzie Ukrainy.
Na podstawie przewidywanych cen i wielkości produkcji energii elektrycznej w 2021 r. rozważono model dywersyfikacji źródeł energii elektrycznej, który bierze pod uwagę minimalizację środków budżetowych i ryzyko produkcji energii elektrycznej z odpowiednimi ograniczeniami dotyczącymi różnych rodzajów energii elektrycznej i ich wpływu na minimalizację ceny dla użytkownika końcowego.
Badania wykazały, że ważnymi czynnikami tworzenia cen energii elektrycznej są wskaźniki kosztów i wielkości produkcji, dystrybucji i transportu energii elektrycznej konsumentom, co w dużej mierze zależy od sposobu tworzenia i dalszego rozwoju rynku energii w Ukrainie.
Ponadto połączenie tradycyjnej i nietradycyjnej energii elektrycznej ma ogromne znaczenie, jednocześnie minimalizując ryzyko i ograniczenia budżetowe.
Bilansowanie systemu generacji energii elektrycznej z różnych źródeł nie tylko pomoże zoptymalizować długoterminowe ceny energii elektrycznej i zminimalizować taryfy dla użytkownika końcowego, ale pozwala również na zaplanowanie zysku w formie długoterminowego zwrotu z inwestycji.
Analiza wyników wykazała, że optymalny podział produkcji energii umożliwia uzyskanie zasobów energetycznych w wymaganej wielkości przy niższych kosztach zakupu i przy minimalnym ryzyku.
REFERENCES (33)
1.
Better, M. and Glover, F. 2006. Selecting project portfolios by optimizing simulations. The Engineering Economist 51(2), pp. 81−97, DOI: 10.1080/00137910600695593.
3.
Babenko et al. 2019 – Babenko, V., Sidorov, V., Koniaieva, Y. and Kysliuk, L. 2019. Features in scientific and technical cooperation in the field of non-conventional renewable energy. Global Journal of Environmental Science and Management 5 (SI), pp.105−112, DOI: 10.22034/gjesm.2019.05.SI.12.
4.
Bai, C. and Sarkis, J. 2018. Evaluating complex decision and predictive environments: the case of green supply chain flexibility. Technological and Economic Development of Economy 24(4), pp. 1630–1658, DOI: 10.3846/20294913.2018.1483977.
5.
Carazo, A.F. 2015. Multi-criteria project portfolio selection. Handbook on project management and scheduling 2, pp. 709−728. Springer International Publishing, DOI: 10.1007/978-3-319-05915-0_3.
6.
Chang et al. 2020 – Chang, C.L., McAleer, M. and Wong, W.K. 2020. Risk and financial management of COVID-19 in business, economics and finance. Journal of Risk Financial Management 13, р. 102.
8.
Fullerton, D. 2017. Distributional effects of environmental and energy policy. New York.
9.
García et al. 2020 – García, F., González-Bueno, J., Guijarro, F. and Oliver, J. 2020. Forecasting the environmental, social, and governance rating of firms by using corporate financial performance variables: A rough set approach. Sustainability 12(8), 3324, DOI: 10.3390/su12083324.
10.
Getsov et al. 2017 – Getsov, P. Wang, Bo., Mardirossian, G., Nedkov, R., Stoyanov, S., Prokopenko, O. and Boyanov, P. 2017. Equipment for evaluation of the characteristics of electronic-optic converters. Comptes Rendus de L’Academie Bulgare des Sciences 70(11), pp. 1575−1578.
12.
Haghighi et al. 2019 – Haghighi, M.H., Mousavi, S.M., Antuchevičienė, J. and Mohagheghi, V. 2019. A new analytical methodology to handle time-cost trade-off problem with considering quality loss cost under intervalvalued fuzzy uncertainty. Technological and Economic Development of Economy 25(2), pp. 277−299, DOI: 10.3846/tede.2019.8422.
13.
Halynska, Yu. and Bondar, T. 2020. Innovation and Modern Applied Science in Environmental Studies. Proc. In Conf., Kenitra, Morocco.
14.
Halynska, Y. 2018. Strategic view on the rental policy in the field of environmental managemen. Problems and Perspectives in Management 16(1), pp. 1−11. [Online]
https://businessperspectives.o... [Accessed: 2021-11-16].
15.
Halynska, Yu. and Oliinyk, V. 2020. Modeling of the distribution mechanism for fuel industry enterprises’ rental income in the system «State − Region – Enterprise». Journal of Advanced Research in Law and Economics XI 2(48), pp. 370–381, DOI: 10.14505/jarle.v11.2(48).10.
16.
Halynska, Yu and Bondar, T. 2021. Combined electricity pricing model taking into account the “green tariff” and traditional factors E3S Web Conference The International Conference on ‘Innovation and Modern Applied Science in Environmental Studies’ Kenitra, Morocco December 25th-27th. Volume 234, DOI: 10.1051/e3sconf/202123400019.
17.
Huang, X. and Zhao, T. 2014. Project selection and scheduling with uncertain net income and investment cost. Applied Mathematics and Computation 247, pp. 61−71, DOI: 10.1016/j.amc.2014.08.082.
18.
Jimenez-Rodriguez, R. and Sanchez, M. 2005. Oil price shocks and real GDP growth: empirical evidence for some OECD countries. Applied Economics 37(2), pp. 201–228, DOI: 10.1080/0003684042000281561.
19.
Kozmenko, O. and Oliynyk, V. 2015. Statistical model of risk assessment of insurance company’s functioning. Investment Management and Financial Innovations 12(2), pp. 189–194.
20.
Liu et al. 2018 – Liu, N., Chen, Y. and Liu, Y. 2018. Optimizing portfolio selection problems under credibilistic CVaR criterion. Journal of Intelligent and Fuzzy Systems 34(1), pp. 335–347, DOI: 10.3233/JIFS-171298.
21.
Matvieieva et al. 2015 – Matvieieva, Y., Myroshnychenko, I. and Bondar, T. 2015. Assessment of the social, ecologic and economic development of machine building enterprises. Economic Annals-XXI 7–8(1), pp. 40–44.
22.
Oliinyk, V. 2018. Optimal Management of GDP Components. Journal of Advanced Research in Law and Economics 9(2/32), pp. 603–614, DOI: 10.14505/jarle.v9.2(32).24.
23.
Oliinyk et al. 2018 – Oliinyk, V., Wiebe, I., Syniavska, O. and Yatsenko, V. 2018. Optimization model of Bass. Journal of Applied Economic Sciences 13(8/62), pp. 2168–2183.
24.
Oliinyk, V. and Kozmenko, O. 2019. Optimization of investment portfolio management. Serbian Journal of Management 14(2), pp. 373−387, DOI: 10.5937/sjm14-16806.
25.
Prokopenko, O. and Kasyanenko, T. 2013. Complex approach to scientific grounding at selecting the direction (variant) of eco-aimed innovative development at different levels of management. Actual Problems of Economics 139(1), pp. 98−105.
26.
Pursky et al. 2019 – Pursky, O., Dubovyk, T., Moroz, I., Buchatska, I. and Savchuk, A. 2019. The price competition simulation at the blended trading market. CEUR Workshop Proceedings 2422, pp. 15–26. [Online]
http://ceur-ws.org/Vol-2422/pa... [Accessed: 2021-10-20].
27.
Ramazanov et al. 2019 – Ramazanov, S., Antoshkina, L., Babenko, V. and Akhmedov, R. 2019. Integrated model of stochastic dynamics for control of a socio-ecological-oriented innovation economy. Periodicals of Engineering and Natural Sciences 7(2), pp. 763−773, DOI: 10.21533/pen.v7i2.557.
28.
Ratti, R.A. and Vespignani, J.L. 2016. Oil prices and global factor macroeconomic variables. Energy Economics 59, pp. 198–212, DOI: 10.1016/j.eneco.2016.06.002.
29.
Sengupta, A. 2010. Environmental Regulation and Industry Dynamics. The B.E. Journal of Economic Analysis & Policy 10(1), Article 52.
30.
Strishenets, О. 2016. Global trends in the development of the energy economy in the XXI century: adaptation to Ukrainian realities. Economic Journal of the Lesia Ukrainka East European National University 1, pp. 73–79. [Online]
http://www.irbis-nbuv.gov.ua/c... [Accessed: 2021-01-25].
31.
Telizhenko, A. and Halynska, Y. 2016. Risk in the formation of collaboration alliance of the redistribution natural rental income. Problems and Perspectives in Management 14(4), pp. 181−185, DOI: 10.21511/ppm.14(4-1).2016.06.
32.
Verkhovna Rada of Ukraine 2018. About the statement of the Procedure for formation of the forecast balance of electric energy of the united power system of Ukraine for the settlement year № 539. [Online]
https://zakon.rada.gov.ua/laws... [Accessed: 2021-11-25].
33.
Zengin, Y. and Ada, E. 2010. Cost management through product design: target costing approach. International Journal of Production Research 48(19), pp. 5593–5611, DOI: 10.1080/00207540903130876.