An Overview of the Prospects and Challenges of Using Artificial
The paper first starts by presenting the conventional control system of microgrids and their energy management, along with the basics of AI tools and techniques. Then, the features and
The paper first starts by presenting the conventional control system of microgrids and their energy management, along with the basics of AI tools and techniques. Then, the features and
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ABSTRACT The concept of microgrids (MGs) as compact power systems, incorporating distributed energy resources, generating units, storage systems, and loads, is widely acknowledged
Reviews microgrid architecture, key components, and control strategies. Highlights various AI models along with their challenges and advantages. Presents AI applications in sizing, control,
To tackle the mentioned concerns, a proposed intelligent energy management system aims to enhance the performance of small-scale microgrid systems.
This work supports the advancement of intelligent, autonomous energy systems and contributes to the development of resilient, grid-interactive solar microgrids.
This paper presents an intelligent energy management system (EMS) for microgrids. The intelligent EMS employs load and photovoltaic (PV) generation forecasting.
Our results show that the proposed method optimizes MG operation, especially under demanding conditions such as variable renewable energy supply and unanticipated load fluctuations.
By 2035, microgrids are envisioned to be essential building blocks of the future electricity delivery system to support resilience, decarbonization, and affordability. Microgrids will be increasingly
Intelligent microgrids provide a self-sufficient energy source, often powered by solar or wind. They ensure continuous power, improve quality of life, and support local economic activities.
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