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Energy Management System for Mini-grid
Subject area: Science,Engineering and Technology · Area of research: Engineering
DOI: 10.64388/IREV9I10-1715825
Abstract
This review paper provides a comprehensive analysis of Energy Management Systems (EMS) for mini-grid systems, focusing on their role in enhancing system efficiency, reliability, and cost-effectiveness in remote or decentralized settings. It explores the challenges of managing intermittent renewable energy sources—such as photovoltaic (PV) and wind—alongside battery energy storage systems (BESS) and backup generators. To this end, the paper critically examines hierarchical, centralized, and decentralized control strategies for balancing demand and supply. The paper also compares methodologies for optimizing energy flow, including classical programming, metaheuristic techniques, and artificial intelligence (AI) approaches. The paper also reviews demand-side management (DSM), load forecasting, and demand response programs to improve operational efficiency. The review concludes that advanced EMS, specifically those leveraging AI and predictive control, are critical for accelerating the transition to renewable-based, sustainable mini-grids.
Keywords
Mini-grid, Centralized control, Decentralized Control, state of charge (SOC), Smart Meters / IoT, Demand Side Management (DSM)
References
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How to cite this paper
@article{1715825,
author = {Paul Nosike},
title = {Energy Management System for Mini-grid},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {10},
pages = {154-170},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1715825.pdf},
abstract = {This review paper provides a comprehensive analysis of Energy Management Systems (EMS) for mini-grid systems, focusing on their role in enhancing system efficiency, reliability, and cost-effectiveness in remote or decentralized settings. It explores the challenges of managing intermittent renewable energy sources—such as photovoltaic (PV) and wind—alongside battery energy storage systems (BESS) and backup generators. To this end, the paper critically examines hierarchical, centralized, and decentralized control strategies for balancing demand and supply. The paper also compares methodologies for optimizing energy flow, including classical programming, metaheuristic techniques, and artificial intelligence (AI) approaches. The paper also reviews demand-side management (DSM), load forecasting, and demand response programs to improve operational efficiency. The review concludes that advanced EMS, specifically those leveraging AI and predictive control, are critical for accelerating the transition to renewable-based, sustainable mini-grids.},
keywords = {Mini-grid, Centralized control, Decentralized Control, state of charge (SOC), Smart Meters / IoT, Demand Side Management (DSM)},
month = {April},
doi = {https://doi.org/10.64388/IREV9I10-1715825}
}