AI Technologies and Their Applications in Small-Scale Electric Power Systems

As the landscape of electric power systems is transforming towards decentralization, small-scale electric power systems have garnered increased attention. Meanwhile, the proliferation of artificial intelligence (AI) technologies has provided new opportunities for power system management. Thus, this...

Full description

Saved in:
Bibliographic Details
Published in:IEEE access 2024, Vol.12, p.109984-110001
Main Authors: Shahid, Arqum, Plaum, Freddy, Korotko, Tarmo, Rosin, Argo
Format: Article
Language:English
Subjects:
Artificial intelligence
Business metrics
Demand analysis
Distributed generation
Electric power
Electric power grids
Electric power systems
Energy consumption
Energy management
Hybrid systems
Indicators
Interactive systems
Microgrids
Performance evaluation
performance indicators
Power system stability
Power systems
Reliability
Renewable energy sources
Reviews
Small scale technology
Virtual power plants
Virtual reality
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:As the landscape of electric power systems is transforming towards decentralization, small-scale electric power systems have garnered increased attention. Meanwhile, the proliferation of artificial intelligence (AI) technologies has provided new opportunities for power system management. Thus, this review paper examines AI technology applications and their range of uses in small-scale electrical power systems. First, a brief overview of the evolution of small-scale electric power systems and the importance of AI integration is given. The background section explains the principles of small-scale electric power systems, including stand-alone systems, grid-interactive systems, microgrids, hybrid systems, and virtual power plants. A thorough analysis is conducted on the effects of AI technologies on power system aspects such as energy consumption, demand response, grid management, operation, energy generation, and storage. Based on this foundation, AI Acceleration Performance Indicators (AAPIs) for small-scale electric power systems are developed to establish a standardized framework for evaluating and comparing different studies. AAPI framework considers a binary scoring for five quantitative Key Performance Indicators (KPIs) and five qualitative KPIs examined through a three-tiered scale - established, evolved, and emerging.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3440067