Exploring Recent Global Scholarly Interest in Energy Demand Forecasting: A Bibliometric Analysis of Conference Papers in the Scopus Database

DOI

10.2991/978-94-6239-622-7_17How to use a DOI?

Keywords

Energy; Energy demand; Forecast; Bibliometric

Abstract

Within the framework of growing concerns about energy security worldwide, energy demand forecasting is pivotal to policy-making and sustainable development strategies. However, systematic analysis of global research trends in this field is still limited, especially in the conference paper data source, which often reflects new scientific achievements and discussions faster than slower publication in journals. To capture the most current picture of the field in the past 5 years, this study selected and conducted bibliometric analysis on 348 conference papers extracted from the Scopus database in the period 2020 - 2024. By employing this methodology, the study elucidates trends in the annual growth of publications, citation patterns, prominent contributors, and international research collaboration. The findings indicate that China is a prominent country in terms of publication volume, academic participation, and the number of authors contributing many works on the topic. Concurrently, the analysis revealed five major research themes and commonly used keywords across numerous conference papers. Based on these findings, we propose future research directions such as applying machine learning to develop energy management models for smart grids integrated with renewable energy. By selecting data from recent conferences, this study not only reflects the most up-to-date state of the art in the field of energy demand forecasting but also lays the foundation for more targeted and impactful research directions in the future.

Research purpose: The research purpose of this study is to analyze global research trends in energy demand forecasting through a bibliometric analysis of conference papers from 2020 - 2024, aiming to clarify publication patterns, academic collaboration, and key themes to guide future research.

Research motivation: Growing concerns over energy security have emphasized the importance of energy demand forecasting for policy and sustainable development. However, systematic analyses of global research trends in this area, especially within conference papers, remain limited and call for further investigation.

Research design, approach, and method: This study adopts a bibliometric research design with a quantitative approach. Data were retrieved from the Scopus database, focusing on 348 conference papers published between 2020 and 2024. Data analysis was conducted using Microsoft Excel and VOSviewer software. Using bibliometric techniques, the analysis examines publication growth, citation patterns, leading contributors, international collaboration, and co-occurrence keyword to identify research trends and emerging themes in energy demand forecasting.

Main findings: The study reveals a significant growth in research on energy demand forecasting, with a sharp increase in conference papers and contributing authors, particularly between 2022 and 2024. China, India, and the United States emerge as the leading contributors, reflecting a close link between research activity and their large energy consumption needs. Keyword analysis highlights machine learning as a central theme, underscoring its potential to optimize energy management and advance renewable energy integration. Overall, bibliometric analysis proves to be an effective tool in mapping research trends and identifying emerging directions in this field.

Practical/managerial implications: The findings provide policymakers and energy managers with insights into global research trends, enabling them to better align national strategies with emerging technologies such as machine learning in energy forecasting. Identifying leading contributors and collaboration networks helps decision-makers recognize potential partners and benchmark best practices. Last but not least, understanding the link between research activity and energy consumption patterns can support more effective planning for energy security, sustainable development, and the integration of renewable energy sources.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Toan-Vu Le
AU  - Thao Tran Phuong
AU  - Nhung Do Hoai
AU  - Long Do Duc
PY  - 2026
DA  - 2026/04/21
TI  - Exploring Recent Global Scholarly Interest in Energy Demand Forecasting: A Bibliometric Analysis of Conference Papers in the Scopus Database
BT  - Proceedings of the International Conference on Emerging Challenges: Business Dynamics in Disruptive Economy (ICECH 2025)
PB  - Atlantis Press
SP  - 258
EP  - 276
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-622-7_17
DO  - 10.2991/978-94-6239-622-7_17
ID  - Le2026
ER  -