Structural and Operating Features of the Creation of an Interstate Electric Power Interconnection in North-East Asia with Large-Scale Penetration of Renewables
Sergei Podkovalnikov,
Lyudmila Chudinova,
Ivan L. Trofimov and
Leonid Trofimov
Additional contact information
Sergei Podkovalnikov: Electric Power Systems Department, Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences, Lermontov Str., 130, 664033 Irkutsk, Russia
Lyudmila Chudinova: Electric Power Systems Department, Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences, Lermontov Str., 130, 664033 Irkutsk, Russia
Ivan L. Trofimov: Electric Power Systems Department, Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences, Lermontov Str., 130, 664033 Irkutsk, Russia
Leonid Trofimov: Electric Power Systems Department, Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences, Lermontov Str., 130, 664033 Irkutsk, Russia
Energies, 2022, vol. 15, issue 10, 1-29
Abstract:
Transition to green energy is the dominant process in the electricity sector globally, including in North-East Asia (NEA). The interstate power grid expansion in the NEA will facilitate the large-scale development of intermittent and uncertain green generation. This paper is aimed at considering the structural and operating features and effectiveness of a potential NEA power grid with large-scale penetration of renewables. A computing and geo-information system provides collection, processing, storage, and geo-visualization of technical and economic data. It incorporates a mathematical model for the optimization of the expansion and operation of power systems. Benefits (including saving the capacity, investment, fuel cost, and total cost) of power interconnection have been estimated in the study. Transfer capability required for the interstate electric ties was calculated and proved quite significant. A tax on greenhouse gases emission from thermal power plants, including carbon dioxide (CO 2 ), has been used in the study as an economic incentive to facilitate the penetration of renewable energy sources in NEA power interconnection. An installed capacity, power generation mix, power exchange among countries, and operating modes (dispatching) have been calculated for different levels of CO 2 emission tax. This study has shown the economic viability of the interconnection, defined major indices of interstate transmission grid infrastructure, revealed the changes in the mix of generating capacities and their operation under conditions of large-scale expansion of renewables, and found out the roles of various countries with different levels of CO 2 tax, detailed the impact of CO 2 emission tax in encouraging capacity additions and power generation growth from renewables. These capacities altogether suppress the expansion of coal-fired power plants in the potential North-East Asia power grid and contribute to achieving Sustainable Development Goals (SDG), particularly SDG 7, to ensure access to affordable, reliable, sustainable, and modern energy for all.
Keywords: prospective power grid; renewable energy; carbon emission; tax; optimization model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.mdpi.com/1996-1073/15/10/3647/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/10/3647/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:10:p:3647-:d:816884
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().