Home  Journals  Regional Economics: Theory and Practice  12(459) - 2018 December

Optimization of the regional energy system with high potential of use of bio-waste and bioresources as energy sources with respect to ecological and economic parameters: The Krasnodar Krai case

Vol. 16, Iss. 12, DECEMBER 2018

Article PDF Version

Received: 7 November 2018

Received in revised form: 21 November 2018

Accepted: 28 November 2018

Available online: 14 December 2018

Subject Heading: ECONOMIC-MATHEMATICAL MODELING

JEL Classification: O44, Q01

Pages: 2383–2398

https://doi.org/10.24891/re.16.12.2383

Subject This article discusses the prospects for the development of the regional energy system through proliferation of the traditional energy technologies use. It also examines the potential for the development of various types of renewable energy sources that can offset the growing energy deficit.
Objectives The article aims to develop an economic and mathematical model that allows optimizing the development of the regional energy system with respect to ecological and economic criteria.
Methods For the study, we used the life-cycle assessment (LCA) methodology in accordance with ISO 14000, cost-effectiveness analysis (CEA), and the linear programming (LP) method.
Results The article says that when optimizing the development of the regional energy system of the Krasnodar Krai in terms of economic parameters, it is preferable to utilize bio-waste and solid household waste (MSW) as sources of energy, fully utilizing the potential of wind power. Photovoltaics (PV) generation can be involved by residual principle. When optimizing the energy mix with respect to environmental criteria, the involvement of biogas generation is impractical.
Conclusions After full use of the potential of processing of MSW and wind energy, the difference between the used potential of renewable sources of energy and the required volume of generation can be compensated by the development of photovoltaics.

Keywords: regional energy system, energy balance, environmental footprint, product life cycle analysis, optimization, modeling

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