TY - JOUR
T1 - Exploring the Intersection of Artificial Intelligence and Microgrids in Developing Economies
T2 - A Review of Practical Applications
AU - Bodewes, William
AU - de Hoog, Julian
AU - Ratnam, Elizabeth L.
AU - Halgamuge, Saman
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/3
Y1 - 2024/3
N2 - Purpose of Review: This paper reviews practical challenges for microgrid electrification projects in low- and middle-income economies, proposing a Social-Technical-Economic-Political (STEP) framework. With our STEP framework, we review recent Artificial Intelligence (AI) methods capable of accelerating microgrid adoption in developing economies. Recent Findings: Many authors have employed novel AI methods in microgrid applications including to support energy management systems, fault detection, generation sizing, and load forecasting. Despite these research initiatives, limited works have investigated the specific challenges for developing economies. That is, high-income countries often have high-quality power, reliable wireless communication infrastructure, and greater access to equipment and technical skills. Accordingly, there are numerous opportunities for the adaptation of AI methods to meet the constraints of developing economies. Summary: In this paper, we provide a comprehensive review of the electrification challenges in developing economies alongside an assessment of novel AI approaches for microgrid applications. We also identify emerging opportunities for AI research in the context of developing economies and our proposed STEP framework.
AB - Purpose of Review: This paper reviews practical challenges for microgrid electrification projects in low- and middle-income economies, proposing a Social-Technical-Economic-Political (STEP) framework. With our STEP framework, we review recent Artificial Intelligence (AI) methods capable of accelerating microgrid adoption in developing economies. Recent Findings: Many authors have employed novel AI methods in microgrid applications including to support energy management systems, fault detection, generation sizing, and load forecasting. Despite these research initiatives, limited works have investigated the specific challenges for developing economies. That is, high-income countries often have high-quality power, reliable wireless communication infrastructure, and greater access to equipment and technical skills. Accordingly, there are numerous opportunities for the adaptation of AI methods to meet the constraints of developing economies. Summary: In this paper, we provide a comprehensive review of the electrification challenges in developing economies alongside an assessment of novel AI approaches for microgrid applications. We also identify emerging opportunities for AI research in the context of developing economies and our proposed STEP framework.
KW - Artificial intelligence
KW - Developing economies
KW - Electrification
KW - Microgrids
UR - http://www.scopus.com/inward/record.url?scp=85188741939&partnerID=8YFLogxK
U2 - 10.1007/s40518-024-00233-w
DO - 10.1007/s40518-024-00233-w
M3 - Review Article
AN - SCOPUS:85188741939
SN - 2196-3010
VL - 11
SP - 10
EP - 23
JO - Current Sustainable/Renewable Energy Reports
JF - Current Sustainable/Renewable Energy Reports
ER -