Distributed ledger technology (DLT), commonly referred to as blockchain, is emerging as a transformative technology solution for managing Virtual Power Plants (VPPs), which aggregate distributed energy resources (DERs). Smart contracts are a key feature of DLT that may be leveraged to streamline complex tasks, from resource onboarding to real-time market transactions, ensuring data reliability, interoperability, and transparency. Through adoption of DLT, utilities may enhance operational efficiency and stakeholder trust, creating secure, transparent ledgers of energy information exchanges, controls and transactions accessible to energy providers, consumers, regulators and other system stakeholders. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">The article provides an overview of the technology features, and an accessible and practical roadmap for integrating DLT into energy systems, outlining key steps from initial planning and transaction selection to deployment. Emphasizing real-world applicability, it illustrates DLT’s pivotal role in modernizing energy grids to meet evolving demands and sustainability goals.

The electric utility industry is transforming to enhance efficiency, reliability, resilience, and sustainability. This article explores how cloud computing is driving this transformation, particularly in distribution systems and areas with limited telecommunication infrastructure. By leveraging satellite or cellular internet, utilities can transmit substation data directly to cloud platforms, eliminating the need for on-premises data collection and historian systems. Cloud-based solutions offer scalable, flexible, secure, and cost-effective alternatives to traditional in-house systems, facilitating the rapid deployment of real-time data applications. This approach enables utilities to manage operations efficiently, even in remote or underdeveloped regions. The article examines cloud computing paradigms, system architectures, and their integration into utility operations. A novel sensor-to-cloud architecture is presented, showcasing how real-time synchronized measurements enhance grid monitoring, alarming, parameter estimation, and enterprise-wide access to critical operational data.

This paper presents a brief overview of the development history, advantages, disadvantages, and application scenarios of small modular reactors (SMRs). It explores relevant simulation technologies, human–system interfaces (HSIs), and instrumentation and control (I&C) systems. Particular attention is given to the integration of advanced digital technologies, including digital twins (DTs) and hardware-in-the-loop (HIL) real-time emulation, in the context of SMRs. Finally, a digital twin emulation prototype of a small modular light-water reactor (smLWR) is provided, which is hoped to offer some modest assistance to peers in the field.

Digital twins are emerging in power electronics as a tool for optimized design, fast prototyping, and smart maintenance, given the increasing demand in terms of high power density, reliability, and low cost. A power electronics digital twin can be regarded as a virtual representation of a power electronics system, embodied by a high-fidelity model running in real time, of which the states and model parameters are updated based on the feedback from the sensors or their data fusions. Digital twin models are developed in multiple domains and run in real time or even faster than real time. The data collected from the physical entities are transferred with controlled latencies and quality, and then processed to iterate the models to represent physical power electronics from application-oriented views. However, due to the nonlinearities and fast switching behaviors of power electronics, one significant challenge is to ensure high fidelity and fast computation simultaneously, which stimulates the real-time simulation (RTS) of power electronics with an ultralow time step. Moreover, the electrical, thermal, and electrothermal aspects shall all be considered to improve the model’s accuracy. To consider the uncertainties, the parameters of the digital twin models are either identified by advanced optimization algorithms or represented by probabilistic expressions. To make it possible, real-time communication should be established between the physical and digital twins. Empowered by modern Internet of Things (IoT) technology, many sensor signals can be transferred in a timely fashion to ensure real-time capability of the digital twin. The digital twin gives insightful information about its physical counterpart based on which smart decisions can be made to improve the design, prototyping, control, and lifecycle management of power electronics converters and systems. In this article, we review the digital twin of modern power electronics, and get an insight into its enabling technologies and possible applications.

In academic curricula, power system protection and feedback control are distinct topics. The former primarily addresses fault analysis and power system relaying, while the latter delves into dynamical system analysis and feedback control design for a range of objectives (e.g., command order tracking and stabilization). In the practical engineering world, protection and control are typically regarded as integrated technologies essential for ensuring power grids operate as expected and remain protected from faults. There have been widespread cries and concerns within the current power grids regarding the impact of high penetration of inverter-based resources (IBRs) on the protection systems. A funding opportunity announcement from the U.S. Department of Energy’s Solar Energy Technologies Office (DE-FOA-0002745 Solar and Wind Grid Services and Reliability Demonstration) in 2022 specifically sought technologies to assess the adverse impact of IBRs on protection and mitigation measures.

Electrifying haul trucks and other vehicles in underground mines will have a significant impact on reducing greenhouse gas (GHG) emissions and operational costs as well as improving worker health and safety.

Electrification, the transition to electric-powered systems, offers multiple advantages across various sectors, facilitating grid evolution. It has predominantly evolved in areas such as distributed energy resources, e-mobility (covering land, sea, and space vehicles), smart houses, smart appliances, mining electrification, and the expanding needs of data centers. Initial stages of adoption have been achieved in these domains. Driven by technological readiness, economic considerations, and changing policy landscapes, this shift demands a comprehensive, layered strategy to optimize efficiency, emissions, cost, and accuracy. Advances in battery technologies, grid improvements, and renewable energy, combined with strategic frameworks, enable effective electrification adoption in these critical areas, highlighting societal and sustainable growth benefits.

Analysis, design, implementation, and control of an engineering system always start with modeling. On the one hand, modeling is always a process of simplification. For example, we can simply model a battery by an ideal constant voltage source and a light bulb by a resistor. Then, we can analyze the circuit and calculate circuit quantities (current, voltage, power, etc.). On the other hand, depending on the scope of study, we need to have enough details or a certain level of fidelity in the models so that meaningful studies can be carried out. For example, copper polygons in low-frequency (e.g., ≤10 kHz) printed circuit boards (PCBs): they can be simply treated as copper conductors using lump parameters, while we should use transmission line theory when handling polygons in high-frequency (e.g., over gigahertz) PCBs.