Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/75786
Title: From a forecasting methodology for the electric energy consumption of mono-towns to its sustainability
Authors: Fedorova, S. V.
Khudyakov, P. Y.
Melkozerov, N. A.
Firsova, D. A.
Issue Date: 2014
Publisher: WITPress
Citation: From a forecasting methodology for the electric energy consumption of mono-towns to its sustainability / S. V. Fedorova, P. Y. Khudyakov, N. A. Melkozerov et al. // WIT Transactions on Ecology and the Environment. — 2014. — Vol. 186. — P. 185-196.
Abstract: The need of Russia for a resource-innovative energy strategy for the period up to 2035 makes it urgent to create a methodology of strategic forecasting for the electric energy consumption of mono-towns, which will result in the efficient development of a power supply system, ensuring territories’ sustainability. For this purpose, it is necessary to consider a mono-town as a complete system, a living organism with a definite life cycle and structure of energy consumers. The authors offer a technocoenosis approach to carry out the ranking and structural analysis of the electric energy consumption of one of the Sverdlovsk region’s mono-towns, taking into account dynamics in population, enterprises, organizations and institutions for the period of 5 years. The provided analysis makes it possible to judge the technocoenosis optimality using characteristic exponent β, depending on the structural features of the territory. The authors developed an algorithm for electric energy consumption forecasting, based on Support Vector Machines (SVM), which takes into account the electric energy of mono-towns’ consumers and the climatic factors. Forecasting accuracy was achieved using cross-validation of the input data in order to optimize the training model. The corresponding changes in electric energy consumption, when a characteristic exponent is optimal, will result in a target forecast that provides the sustainable development of mono-towns. © 2014 WIT Press.
Keywords: ELECTRIC ENERGY CONSUMPTION
FORECASTING ALGORITHM
MONO-TOWN SUSTAINABILITY
STRATEGY
TECHNOCOENOSIS APPROACH
ALGORITHM
ARTIFICIAL INTELLIGENCE
ELECTRICITY SUPPLY
ENERGY USE
FORECASTING METHOD
SUSTAINABILITY
RUSSIAN FEDERATION
SVERDLOVSK
URI: http://hdl.handle.net/10995/75786
Access: info:eu-repo/semantics/openAccess
Conference name: 5th International Conference on Energy and Sustainability, 2014
Conference date: 16 December 2014 through 18 December 2014
SCOPUS ID: 84926486278
PURE ID: 310938
ISSN: 1743-3541
DOI: 10.2495/ESUS140161
metadata.dc.description.sponsorship: International Journal of Sustainable Development and Planning;WIT Transactions on Ecology and the Environment
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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