The ongoing digital transformation in power grids has made the Internet of Things (IoT) a critical component for the development of next generation smart grids. The article provides a detailed review on technologies related to IoT and their utilization within the current power grid ecosystem that includes various IoT layers like perception layer sensors, advanced metering infrastructure (AMI), and cloud computing/ artificial intelligence(AI) based energy management platforms. The paper discusses the layered IoT architecture for smart grids, explores various wireless communications solutions including ZigBee, LoRaWAN, NB-IoT and 5G. The article also examines enabling IoT technologies including big data analysis, blockchain-based secure transactions for energy trading and federated learning for privacy preservation. Emerging IoT paradigms like blockchain-enabled DL networks, lattice-based cryptography schemes for IoT devices and software-defined vehicular edge computing solutions are analyzed as critical components of next generation secure smart grid infrastructures. Application of IoT in demand response, fault detection, renewable sources integration, and distributed energy resource management is explored systematically. Issues associated with interoperability, scalability, cyberattacks, and real-time latency are also addressed with proposed mitigation approaches. Finally, the paper concludes with future research directions related to integrating AI and IoT technologies in the smart grid ecosystem.
Diksha, Meena Malik, Ruchika Gupta· International Conference on...· 0 citations
Smart grids are becoming more complicated with distributed energy resources, dynamic load changes, real-time operating requirements. The conventional black-box artificial intelligence (AI) models lack in trust, transparency and compliance with regulations, thereby limiting their use in practical deployment. To resolve these issues, this paper suggests a conceptual unified GenAI-XAI framework for smart grids. Explainable Artificial Intelligence (XAI) offers an interpretable and reliable decision-making ability for existing scalability and real-time integration related issues. Recent advances in Generative AI (GenAI) complement XAI by supporting in scenario modeling, intelligent decision assistance, and synthetic data generation. The study presents a comparative analysis of XAI methods and a systematic taxonomy of GenAi applications in anomaly detection, load forecasting, energy optimization, and predictive maintenance The proposed conceptual framework help to improves adaptability, transparency,, and operational efficiency, thereby facilitating the development of a sustainable, resilient, and smart grid systems.
The smart grid systems are increasingly becoming digital where the system is taking a new direction into greater operational efficiency and real time energy management. The increased number of Internet of Things (IoT) devices and communication networks has widened the area of attack as well, thus smart grids are vulnerable to more sophisticated cyber attacks like false data injection, denial-of-data manipulation and service attacks. The traditional centralized security controls are not sufficient because of the limitation of single point failure, scalability limitations, and demand decentralized and resilient security controls. The use of blockchain technology in this regard has become a potential solution in order to improve the level of security by utilizing the transparent, decentralized, and immutable features of the technology. To provide cybersecurity approaches of smart grid systems, a taxonomical structure of blockchain technology is proposed in this paper. Besides that it shows the categorization of the various techniques into secure data management, secure energy trading, device authentication, data integrity assurance and communication protection. A detailed analysis of existing works was undertaken to determine their efficiency based on the security, scale and complexity of implementation. The results of the review describe some of the major challenges, such as latency and energy overhead and provide future research opportunities on effective smart grid security frameworks.
F. Basheer, Hari Gobind Pathak, Meena Malik et al.· International Conference on...· 0 citations
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