Modeling the Development of Energy Systems of Remote Areas in the Context of the Energy Transition

Authors

  • Y.D. Severina Melentiev Energy Systems Institute SB RAS, Irkutsk, Russia
  • V.A. Shakirov Melentiev Energy Systems Institute SB RAS, Irkutsk, Russia
  • L.N. Takaishvili Melentiev Energy Systems Institute SB RAS, Irkutsk, Russia

DOI:

https://doi.org/10.25729/esr.2024.04.0005

Keywords:

energy transition, decarbonization, modeling, energy system, renewable energy sources, long-term development

Abstract

This study focuses on the relevance of modeling the long-term development of energy systems in the context of the energy transition. The comparative analysis of software products for the modeling of energy systems and complexes is presented. Open source software such as SpineOpt, PyPsa, Switch, TEMOA, and TIMES are discussed in more detail. Based on this comparative analysis, SpineOpt is selected for further use as it is most feature-rich. The use of SpineOpt is considered in modeling the long-term development of the energy system of Novikovo located on the Tonin-Aniva peninsula in the Sakhalin region. An overview of the energy system, outline of plausible development options, and chosen key technologies are provided. The time frame of modeling extends to 2050 with multiple scenarios of development of the area considered. The scenarios differed in the constraints imposed on CO2 emissions and new capacity additions of renewables. For each scenario, the model produced the optimal dynamics of evolution of the electricity generation mix, along with estimates of costs, greenhouse gas emissions, and hydrogen and germanium production volumes. Total CO2 emissions during the modeled timespan, which extended to 2050, were about 946 thousand tons under the most stringent constraints, and 2,458 thousand tons under moderate ones. At the same time, capital expenditures for the construction of energy facilities amounted to $51.6 million and $45.8 million, respectively. The solutions resulting from modeling enable identifying the most promising areas for development and technologies to be adopted.

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Published

2024-12-28