| Abstract: |
Emerging technologies and prospects of distribution systems during the last decades, the global energy demand is exponentially increasing, supplemented with the share of renewable energy sources (RESs) and smart grid technologies, which have shifted from a traditional centralized generation to more simplified, decentralized structures. Intelligent Automated Power Distribution Systems (IAPDS) is an integration of computational intelligence, real-time communication networks, and the adaptive control strategy that allows the Grid to operate in a self-healing, fault-tolerant and energy efficient manner. This review paper provides a systematic meta-analysis of previous works related to the design, implementation and performance evaluation of IAPDS (2005−2024). This paper addresses these issues by systematically reviewing and synthesizing the main enabling technologies driving modern intelligent distribution systems from published peer-reviewed publications (N = 200+), including: AI, ML, IoT, SCADA systems, and AMI. The review then goes on to critique existing techniques implemented in load forecasting, fault identification, demand-side management, and automated switching respectively, while stress-testing unresolved research barriers on cybersecurity threats, scalability problems, and interoperability challenges. The results reveal that the IAPDS architectures which merge the multi-agent systems with the deep reinforcement learning technology achieve the best performance in the aspects of fault recovery automatically and on-load balancing in real-time. Finally, this paper ends with a futures perspective on emerging avenues for research and the transformative role of IAPDS in realizing sustainable, resilient and carbon-neutral power systems. |
