Regional Distribution and Optimization Methods of Electricity Consumption by Sectors
Abstract
The sectoral distribution of regional electricity consumption and its optimization play a crucial role in ensuring economic stability and efficiency. This article analyzes the dynamics of distribution and losses of net electricity generated in the Republic of Uzbekistan from 1992 to 2020 across various economic sectors. The research results indicate a decrease in energy consumption in the industrial and construction sectors, an increase in the share of household consumers, and a reduction in energy demand in the agricultural sector. The rise in power grid losses confirms the need to modernize the electricity distribution system. The use of strategic and operational management models is proposed to optimize regional electricity supply. Optimization can be implemented at the strategic level using the Multiverse algorithm, and at the operational level using the Gurobi solver. The research findings provide scientifically grounded recommendations for effective planning of electricity distribution, minimizing energy losses, and enhancing economic efficiency. This article has significant theoretical and practical importance for exploring opportunities to optimize electricity supply strategies and apply econometric models.
References
B. B. Ateba, P. B. Issock Issock, I. Struweg, C. De Meyer-Heydenrych, и R. Inglesi-Lotz, «Strategic analyses on the South African grid supply and consumption inefficiencies by market segments», Energy Sources Part B Econ. Plan. Policy, т. 19, вып. 1, 2024, doi: 10.1080/15567249.2024.2393638.
Z. A. Barkhordar, S. Habibzadeh, и N. Alizadeh, «Deriving electricity consumption patterns using a decomposition approach», Results Eng., т. 16, 2022, doi: 10.1016/j.rineng.2022.100628.
R. Cheng, Z. Xu, P. Liu, Z. Wang, Z. Li, и I. Jones, «A multi-region optimization planning model for China’s power sector», Appl. Energy, т. 137, сс. 413–426, 2015, doi: 10.1016/j.apenergy.2014.10.023.
T. S. Cheong, V. J. Li, и X. Shi, «Regional disparity and convergence of electricity consumption in China: A distribution dynamics approach», China Econ. Rev., т. 58, 2019, doi: 10.1016/j.chieco.2018.02.003.
J.-S. Chou, N.-Q. Nguyen, и K. Srinivasan, «Forecasting Regional Energy Consumption via Jellyfish Search-Optimized Convolutional-Based Deep Learning», Int. J. Energy Res., т. 2023, 2023, doi: 10.1155/2023/3056688.
H. Hino, H. Shen, N. Murata, S. Wakao, и Y. Hayashi, «A versatile clustering method for electricity consumption pattern analysis in households», IEEE Trans. Smart Grid, т. 4, вып. 2, сс. 1048–1057, 2013, doi: 10.1109/TSG.2013.2240319.
D. Li, X. Wang, и W. Zhao, «Optimization on national energy consumption distribution under total amount control of pollutants», Energy Educ. Sci. Technol. Part Energy Sci. Res., т. 32, вып. 6, сс. 6137–6148, 2014.
Y. Wang и J. Zhen, «Regional electricity cooperation model for cost-effective electricity management with an emphasis on economic efficiency», Energy Policy, т. 195, 2024, doi: 10.1016/j.enpol.2024.114383.
B.-W. Yi, J.-H. Xu, и Y. Fan, «Inter-regional power grid planning up to 2030 in China considering renewable energy development and regional pollutant control: A multi-region bottom-up optimization model», Appl. Energy, т. 184, сс. 641–658, 2016, doi: 10.1016/j.apenergy.2016.11.021.
Y. Zhang и др., «Optimization of China’s electric power sector targeting water stress and carbon emissions», Appl. Energy, т. 271, 2020, doi: 10.1016/j.apenergy.2020.115221.
W.-Q. Zhou и др., «Research on optimizing air pollutant emission inventory based on electricity consumption data», Zhongguo Huanjing KexueChina Environ. Sci., т. 43, вып. 7, сс. 3350–3359, 2023.
Jumbe, C.B.L., 2004. Cointegration and causality between electricity consumption and GDP: empirical evidence from Malawi. Energy Economics 26, 61–68. 10.1016/j.eneco.2009.10.016
D. N. Gujarati and D. C. Porter, Basic Econometrics, 5th ed. New York, NY, USA: McGraw-Hill, 2009. https://archive.org/details/basic-econometric-by-damodar-n.-gujarati-and-dawn-c.-porter.
S. M. Al-Fattah, M. I. Khan, and A. R. Aziz, “Electricity consumption-growth nexus: Evidence from panel data for transition countries,” International Journal of Energy Economics and Policy, vol. 10, no. 5, pp. 123–135, 2020. https://www.researchgate.net/publication/46490977_Electricity_consumption-growth_nexus_Evidence_from_panel_data_for_transition_countries.
J. H. Stock and M. W. Watson, Introduction to Econometrics, 3rd ed. Boston, MA, USA: Pearson, 2015.: https://archive.org/details/basic-econometric-by-damodar-n.-gujarati-and-dawn-c.-porter.
P. Joskow, “Incentive regulation and its application to electricity networks,” Review of Network Economics, vol. 7, no. 4, pp. 1–27, 2008. DOI:10.2202/1446-9022.1161
S. N. Paterakis, O. Erdinç, J. P. S. Catalão, and P. S. Georgilakis, “A Multi-Objective Optimization Approach to Risk-Constrained Energy and Reserve Procurement Using Demand Response,” IEEE Transactions on Power Systems, vol. 32, no. 2, pp. 1497–1508, Mar. 2017. DOI: 10.1109/TPWRS.2016.2598697.
S. Chattopadhyay, “Optimizing Renewable Energy Systems through Artificial Intelligence: Review and Future Prospects,” Energy & Environment, vol. 30, no. 6, pp. 1074–1092, Dec. 2019. DOI: 10.1177/0958305X241256293 .
Juraev, F. D. S. (2021). Problems Of Informatization Of Management Of Agricultural Industry And Modeling Of Agriconomic System In A Market Economy. The American Journal of Applied sciences, 3(02), 49-54. https://www.eeseaec.org/energeticeskij-profil-uzbekistana
Juraev, F. D., Mallaev, A. R., Aralov, G. M., Ibragimov, B. S., & Ibragimov, I. (2023). Algorithms for improving the process of modeling complex systems based on big data: On the example of regional agricultural production. In E3S Web of Conferences (Vol. 392, p. 01050). EDP Sciences. // https://doi.org/10.1051/e3sconf/202339201050
Mukhitdinov, K. S., & Juraev, F. D. Methods of Macroeconomic Modeling. International Journal of Trend in Scientific Research and Development (IJTSRD), e-ISSN, 2456-6470.
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