텍스트 마이닝 및 토픽 모델링을 활용한 마이크로그리드 연구 동향 분석: 재생에너지 통합과 섹터 커플링을 중심으로

초록

This review study quantitatively analyzes academic trends and examines the technological evolution of microgrids, which are expanding rapidly due to the global energy transition. To ensure academic reliability, 206 SCIE-indexed publications from the past 18 years (2008–2025) were analyzed using Natural Language Processing(NLP)-based text mining and LDA Topic modeling. The analysis reveals that the fundamental basis of microgrid research lies in energy management systems and optimization algorithms. In particular, robust optimization for managing the uncertainty of renewable energy accounts for the largest share of the literature. Furthermore, the paradigm of flexibility resources is shifting from stationary facilities to electric vehicles and demand response. The study also demonstrates that sector coupling, integrating electrical and thermal energy, is establishing an independent research domain centered on distributed control. Notably, the intertopic distance analysis identifies a research gap between deterministic grid control and market-based economic mechanisms, suggesting a lack of integrated real-time optimization frameworks. The findings imply that microgrids are evolving into intelligent platforms that integrate multi-source energy and mobile resources. This study provides a strategic basis for future research aimed at ensuring the interoperability, reliability, and economic viability of next-generation microgrid systems.

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