innovationИнформация и инновацииInformation and Innovations1994-24432949-2157МЦНТИ10.31432/1994-2443.2025.15innovation-314Research ArticleИНФОРМАЦИОННЫЕ ПРОЦЕССЫInformation processesТехнологический суверенитет как актуальная проблема энергетической безопасности. Предварительный анализTechnological Sovereignty as a Current Energy Security Challenge. Preliminary analysishttps://orcid.org/0000-0001-9903-2800ЧигаревБ. Н.ChigarevB. N.

Борис Николаевич Чигарев, к. ф.-м. н., старший научный сотрудник

ул. Губкина, дом 3, 119333, г. Москва

Boris N. Chigarev, Cand. Sci. (Phys.-Math.), Senior Researcher

3, Gubkina str., 119333 Moscow

bchigarev@ipng.ruИнститут проблем нефти и газа РАНРоссияOil and Gas Research Institute, Russian Academy of SciencesRussian Federation2025010220262032558Copyright © Чигарев Б.Н., 20262026Чигарев Б.Н.Chigarev B.N.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://journal.icsti.int/jour/article/view/314

Актуальность данной работы определяется важностью энергетической безопасности, которая заключается не только в снижении зависимости от ископаемого топлива, но и в избежание зависимости от передовых технологий. Развитие искусственного интеллекта, требующего значительных энергетических и технологических ресурсов, смещает акцент конкуренции с энергетической безопасности на технологический суверенитет. Целью данного исследования было выявление подходящих инструментов для анализа текста аннотаций, полученных из большого объема библиометрических записей. Основное внимание уделялось предварительной оценке актуальных тем в энергетическом секторе с целью эффективного анализа тенденций в вопросах технологического суверенитета. Данные. В данной работе использовано 10 тысяч библиометрических записей за 2024 год, отсортированных по релевантности и экспортированных из открытой базы данных аннотаций Scilit по запросу: «энергия И технология». Фильтры применены для категорий наиболее связанной с технологиями: «Энергетические системы и электромобили», «Энергетические системы и технологии», «Управление электроэнергией» и «Ядерные технологии и приборостроение». Результаты. Основной темой проанализированных библиометрических данных была возобновляемая энергия. На основе ключевых слов выделено двенадцать кластеров, три из которых — водород, хранение тепловой энергии и выбросы парниковых газов — представляют наибольший интерес. Эти кластеры отражают ключевые слова, полученные как из Yake!, так и из PatternRank. Программа Yake! превосходит PatternRank по времени выполнения и представлению найденных ключевых слов в текстах аннотаций. Продемонстрирована возможность использования AnyAscii для предварительной обработки текста. Выводы. Исследование показало, что для более полного анализа рассматриваемого вопроса необходимо расширить источники данных, например, использовать OnePetro для тем, связанных с нефтью и газом, IEEE Xplore для вопросов энергетических систем и Semantic Scholar для оценки роли ИИ в энергетическом секторе.

The relevance of this work is determined by the importance of energy security, which consists not only in reducing dependence on fossil fuels, but also in avoiding dependence on advanced technologies. The development of artificial intelligence, which requires significant energy and technological resources, is shifting the focus of competition from energy security to technological sovereignty. The aim of this study was to identify suitable tools for analyzing abstracts text obtained from a large volume of bibliometric records. It focused on the preliminary assessment of current topics in the energy sector with the aim of effectively analyzing trends in technological sovereignty issues. Data. In this paper 10 thousand bibliometric records for the year 2024, sorted by relevance and exported from the open abstract database Sciliton the query: “energy AND technology”. Filters were applied on the “Subject” category most related to technology: Power Systems & Electric Vehicles, Energy Systems & Technologies, Electrical Energy Management, and Nuclear Technology & Instrumentation. Results. The main topic of the analyzed bibliometric data was renewable energy. Based on keywords, twelve clusters were identified, three of which — hydrogen, thermal energy storage, and greenhouse gas emissions — are of greatest interest. These clusters reflect keywords derived from both Yake! and PatternRank. The Yake! program outperforms PatternRank in terms of run time and representation of found keywords in abstract texts. The feasibility of using AnyAscii for text preprocessing is demonstrated. Conclusions. The study showed that it is necessary to expand data sources for a more comprehensive analysis of the issue under consideration, for example, using OnePetro for topics related to oil and gas, IEEE Xplore for energy systems issues, and Semantic Scholar for assessing the role of AI in the energy sector.

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The authors declare that there are no conflicts of interest present.