Karpov, Valery (2012): Анализ подходов к обеспечению энергетической безопасности регионов. Published in: Актуальные вопросы развития региональной экономики: Материалы Международной научно-практической конференции. (2012): pp. 57-61.
Preview |
PDF
MPRA_paper_59296.pdf Download (214kB) | Preview |
Abstract
This article analyzes the models and methods of their solutions for the optimization of the various parameters of power systems: a model of integer linear programming, fuzzy logic and stochastic programming. The article notes that the choice of this or that technique is determined by the objectives of the calculation, in particular the conditions of energy supply in the region, the presence or absence of domestic energy resources in the region, etc. From the point of view of energy security for the region, not having its own energy resources, according to the authors, the most appropriate from an economic point of view, are the model MARKAL (Market Allocation) and optimization model EFOM (Energy Flow Optimization Model). These models consider the energy security of the region with a common ground and allow you to optimize all the flows of energy in the region.
Item Type: | MPRA Paper |
---|---|
Original Title: | Анализ подходов к обеспечению энергетической безопасности регионов |
English Title: | Analysis of approaches to energy security regions |
Language: | Russian |
Keywords: | energy system, energy security, MARKAL, EFOM, energy resources, the economic model. |
Subjects: | L - Industrial Organization > L5 - Regulation and Industrial Policy > L52 - Industrial Policy ; Sectoral Planning Methods L - Industrial Organization > L7 - Industry Studies: Primary Products and Construction > L78 - Government Policy Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q3 - Nonrenewable Resources and Conservation > Q32 - Exhaustible Resources and Economic Development Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q43 - Energy and the Macroeconomy Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q47 - Energy Forecasting Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q48 - Government Policy R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R11 - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R13 - General Equilibrium and Welfare Economic Analysis of Regional Economies |
Item ID: | 59296 |
Depositing User: | Dr.Ph. Valery Karpov |
Date Deposited: | 16 Oct 2014 00:03 |
Last Modified: | 28 Sep 2019 04:35 |
References: | 1. Воропай Н.И., Клименко С.М., Криворуцкий Л.Д. и др. О сущности и основных проблемах энергетической безопасности России // Известия РАН. Энергетика. – 1996. – № 3. – С. 38-49. 2. Воропай Н.И., Славин Г.Б., Чельцов М.Б. О формировании терминологии в области энергетической безопасности / Энергетическая политика России на рубеже веков. Т. 1. − М.: Папирус ПРО, 2001. – С. 157-166. 3. Веселов Ф.В., Волкова Е.А., Курилов А.Е., Макарова А.С., Хоршев А.А. Методы и инструментарий прогнозирования развития электроэнергетики. // Известия РАН. Энергетика. – 2010. – № 4. – С. 82-94. 4. Energy Dictionary / World Energy Council. − Paris: Jouve SI, 1992. – 635 p. 5. Системные исследования в энергетике: Ретроспектива научных направлений СЭИ-ИСЭМ / Отв. ред. Воропай Н.И. – Новосибирск: Наука, 2010. – 686 с. 6. Kannan R., Ekins P., Strachan N. The structure and use of the UK MARKAL model / Inter-national Handbook on the Economics of Energy. Vol. 140. – Edward Elgar Publishing, 2009. – P. 285-310. 7. Grohnheit P.E.. Economic interpretation of the EFOM model / Energy Economics. Vol. 13. – 1991. – № 2. – P. 143-152. 8. Cai Y.P., Huang G.H., Tan Q. An inexact optimization model for regional energy systems planning in the mixed stochastic and fuzzy environment // Int. J. Energy Res. – Vol. 33. – 2009. – P. 443-468. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/59296 |