Advanced Metering Infrastructure (AMI) is a key enabler of digital and intelligent power systems, particularly in microgrid environments. However, existing research often addresses AMI from fragmented perspectives, limiting a comprehensive understanding of its role within integrated and data-driven energy systems. This paper presents a structured analysis of AMI based on a bibliometric and thematic review of recent literature, identifying the main research trends, technological drivers, and emerging directions in the field. The results reveal a transition of AMI toward a data-centric platform that supports real-time monitoring, bidirectional energy management, and intelligent decision-making. Key domains include cybersecurity, data analytics, communication systems, and distributed energy integration, while emerging technologies such as artificial intelligence and the Internet of Energy play a critical role in future developments. Finally, the paper outlines key challenges and provides strategic recommendations to support the effective deployment of AMI in microgrids, contributing to the development of resilient and sustainable energy systems.
Low-carbon development is a key direction for the world's development today. With the proposal of the dual carbon goals, the power grid is also responding actively. As advanced metering infrastructure can promote demand-side response, achieve two-way information flow, and guide users to use electricity during off-peak hours and fill valleys, advanced metering infrastructure is an important device for the smart grid to achieve low-carbon development. Therefore, this paper provides an overview of the current status of advanced metering infrastructure and the Smart Electricity Meters and phasor measurement units within them through methods such as literature retrieval. It also analyses the challenges faced by Smart Electricity Meters and phasor measurement units in a low-carbon environment, as well as their future optimization directions and development trends. After analysis, it is found that Smart Electricity Meters can now perform demand response based on price and non-intrusive load detection. It is necessary to optimize the accuracy and stability of high-frequency collected data and enhance network security. The phasor measurement unit can collect data at high frequency and in real time and synchronize it to the power grid system. It is necessary to optimize the high precision and low latency of the measurement.
Xijun Huang· MATEC Web of Conferences· 0 citations
Over the last couple of decades, a transition has evolved from the traditional centralized power grid to a distributed grid of microgrids (GoMGs) dominated by power electronics-based generation. The primary objective of this evolution is to achieve a sustainable, resilient grid while ensuring clean, reliable, and self-adaptive energy access across various operating conditions. However, this new energy paradigm, with high penetration of renewable energy, poses amplified challenges in controlling and securing GoMGs to maintain resiliency, reliability, sustainability, and operational stability. To address these issues and ensure a smarter, cybersecure, data-driven, and sustainable MG, many researchers at the intersection of power electronics, power systems, and artificial intelligence (AI) are exploring ways to develop and implement efficient and reliable AI-based techniques. This article sheds light on the multidimensional perspectives of sustainability and resiliency in GoMGs, focusing on security, stability, accessibility, and scalability in relation to the current state of technological maturity. Building on this vision, a futuristic roadmap is presented to enhance sustainability and resiliency using cutting-edge AI applications, enabling pre-event strategies, such as prediction, optimization, and adaptation, as well as post-event mitigation and restoration techniques.
M. Shadmand, Uzair Asif, Debotrinya Sur et al.· IEEE Energy Sustainability M...· 0 citations
The goal of the study presented in this article is to investigate all current issues related to the proper deployment of load forecasting (LF) techniques in smart grids (SGs). The latter concept has recently emerged as a potential solution to the global energy problem as well as to the ever-increasing and diverse consumer demands. To this end, more flexible dispersed production units are involved, mainly based on renewable energy sources (RESs). Another key novelty of SGs is their ability to gather information directly from consumers and production units in real time, thus facilitating optimum network planning and recovery as well as minimization of outage probability. Hence, it is important to use appropriate advanced infrastructure, which, in combination with modern telecommunication networks, will enable the full exploitation of SGs. In this context, to make the electricity system more efficient, avoid voltage and frequency imbalance issues and implement optimal production and consumption planning, LF is a vital process and plays a key role in the management of future electricity systems. Therefore, recent state-of-the art approaches in LF methods are also presented and discussed. In the same context, current limitations and proposals for future work are identified as well.
E. Tsampasis, Christos Pergamalis, Mario Sulokoka et al.· Telecom· 0 citations
Electric vehicles (EVs) are increasingly regarded as a key component of low-carbon mobility and the sustainable energy transition. However, their large-scale deployment raises challenges that extend beyond vehicle technologies and require a system-level understanding of interactions with power networks, energy resources and users. This paper presents a critical review of the literature published since 2012, examining EV development from an integrated energy perspective that includes vehicle technologies, charging infrastructure, power electronics, grid integration, renewable energy coupling and environmental implications. A structured methodology is used to identify and analyze peer-reviewed studies, with particular emphasis on high-impact review articles that consolidate knowledge across disciplines. The analysis shows that, despite significant technological progress, large-scale EV deployment remains constrained by infrastructure limitations, distribution grid readiness, charging coordination strategies, material availability and socio-technical factors. Simulation-based studies play a central role in anticipating these impacts and informing deployment strategies before real-world implementation. Rather than addressing individual components in isolation, this review highlights interdependencies between technologies, control approaches and energy systems. Based on this synthesis, key research priorities and high-level challenges are identified, providing guidance for future research and policy aimed at enabling EVs to effectively support sustainable ambient energy and mobility systems worldwide deployment.
Antonio Alonso-Cepeda, R. Villena-Ruiz, A. Honrubia-Escribano et al.· Sustainability· 0 citations
Modern energy management systems, even within advanced energy internet (EI) infrastructures, remain fundamentally reactive, optimization-bound, and incapable of reasoning about context, intent, or uncertainty. While the EI paradigm has established a powerful cyber-physical architecture for interconnecting distributed energy resources via software-defined packetized networks, the question of how such systems should think, adapt, and govern energy decisions intelligently remains an open challenge. This paper introduces cognitive energy management (CEM); a new conceptual framework that addresses this gap by redefining how energy systems perceive, reason, learn, and act within complex operational environments. Grounded in the EI cyber-physical foundation, CEM extends beyond conventional optimization by embedding goal-directed reasoning and continuous adaptation into the energy management loop, positioning itself as the cognitive governance layer of EI-based infrastructures. We formally define CEM, distinguish it from rule-based and optimization-based paradigms through structured comparison, and articulate its core architectural layers. To demonstrate the framework's practical value, we develop a toy problem grounded in smart port energy management; one of the most operationally demanding EI node environments in modern infrastructure. Specifically, we model a predictive vessel turnaround scenario in which a CEM-enabled system plans energy procurement, storage pre-charging, and load scheduling across a six-hour operational horizon. The demonstration illustrates how CEM moves the EI beyond feasibility-seeking toward intelligent, anticipatory energy governance.
Hafiz Majid Hussain, Wajiha Samer, J. Haakana· 0 citations
Energy resilience is becoming a key requirement for future smart infrastructures, particularly in Smart City environments characterized by large-scale distribution, heterogeneous stakeholders, and long operational lifetimes. While energyefficient communication has been widely studied, integrating it into sustainable and resilient urban systems remains a challenge. This paper presents a visionary, architecture-driven perspective on energy-resilient communication systems, with a primary focus on Smart City applications. Drawing on architectural experience from the EKI-Saxony initiative, the paper introduces a reference architecture for Smart Cities that integrates energy-autonomous field devices, mobile service entities, and modular platform services via adaptive, decentralized communication mechanisms. The SmartGreenZitty concept illustrates how energy-resilient communication can be operationalized as an enabling infrastructure layer for sustainable urban services rather than as an isolated technology. Beyond Smart City environments, the paper outlines how the same architectural principles, such as energy autonomy, decentralized intelligence, and graceful degradation, can be transferred to industrial ecosystems, including smart factories, logistics, and automation systems. The presented architecture aims to support long-term, robust, and adaptable digital infrastructures across domains. This paper does not propose new communication protocols or quantitative performance evaluations, but instead focuses on system-level architectural principles intended to guide future implementation and evaluation efforts.
N. Belov, T. Stoppe, Julian Haase et al.· International Conference on...· 0 citations