This Special Issue on Multienergy Systems is motivated by the tremendous changes and opportunities in integrated planning, operation, and modeling of the energy systems, including electric, natural gas, and district heating–cooling systems together with the demand side. Traditionally, the role of electric power has been regarded as an energy carrier between the power plants and the consumers. Consequently

This article takes an integrated view of optimized capacity design and operation of islanded energy hubs. We consider energy hubs that incorporate emerging distributed energy resources as well as energy storage devices and fully support electricity and heat demand of an islanded installation. Both battery and hydrogen storage are incorporated. To explicitly account for the stochasticity in renewable

In many parts of the world, electric power systems have seen a significant shift toward generation from renewable energy and natural gas. Because of their ability to flexibly adjust power generation in real time, gas-fired power plants are frequently seen as the perfect partner for variable renewable generation. However, this reliance on gas generation increases interdependence and propagates uncertainty

Natural-gas and power systems are increasingly interdependent due to the integration of an increasing number of combined cycle gas turbines in the power generation mix. However, natural gas and power systems are generally independently operated. This is the result of history and the fact that natural gas has not been important for electricity production until recently. Adopting a power system perspective

We derive conditions for monotonicity properties that characterize general flows of a commodity over a network, where the flow is described by potential and flow dynamics on the edges, as well as potential continuity and the Kirchhoff–Neumann mass balance requirements at nodes. The transported commodity may be injected or withdrawn at any of the network nodes, and its movement throughout the network

Increasing quantities of renewable energy generation has yielded a need for greater energy storage capacity in power systems. Thermal storage in variable air volume (VAV) heating, ventilation, and air conditioning (HVAC) in commercial buildings has been identified as an inexpensive source of grid storage, but the true costs are not known. Recent literature explores the inefficiency associated with

Water pumping in drinking water distribution networks (WDNs) can be treated as a flexible load in the power distribution network (PDN). In this article, we formulate an optimization problem to minimize the electricity costs associated with pumping subject to WDN and PDN constraints. In practice, both water and power demands are uncertain and pumps should be scheduled to ensure that pump operation does

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The articles in this month’s special issue provide insight into future computing technologies such as novel architectures, spintronic memories, and quantum computing.

Computing systems are evolving rapidly. At the device level, emerging devices are beginning to compete with traditional CMOS systems. At the architecture level, novel architectures are successfully avoiding the communication bottleneck that is a central feature, and a central limitation, of the von Neumann architecture. Furthermore, such systems are increasingly plagued by unreliability. This unreliability

Building a quantum computer that surpasses the computational power of its classical counterpart is a great engineering challenge. Quantum software optimizations can provide an accelerated pathway to the first generation of quantum computing (QC) applications that might save years of engineering effort. Current quantum software stacks follow a layered approach similar to the stack of classical computers

On January 26, 1926 (see Fig. 1 ), John Logie Baird gave a demonstration at his laboratory in 22 Frith Street, London, of the live transmission of moving images, obtained in reflected light with tonal graduation, to members of the Royal Institution. This event is generally accepted as the first public demonstration of true television [1] , [2, pp. 88–107] , [3, pp. 65–84] . Ten months earlier, on March

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

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Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”),

In a computational context, self-awareness (SA) is a capability of an autonomous system to describe the acquired experience about itself and its surrounding environment with appropriate models and correlate them incrementally with the currently perceived situation to expand its knowledge continuously. This article introduces a bio-inspired framework for generative and descriptive dynamic models that

In this article, we describe an approach to autonomous system construction that not only supports self-awareness but also formal verification. This is based on modular construction where the key autonomous decision making is captured within a symbolically described “agent.” So, this article leads us from traditional systems architectures, via agent-based computing, to explainability, reconfigurability

Modern distributed systems and Internet-of-Things applications are governed by fast living and changing requirements. Moreover, they have to struggle with huge amounts of data that they create or have to process. To improve the self-awareness of such systems and enable proactive and autonomous decisions, reliable time series forecasting methods are required. However, selecting a suitable forecasting

To promote engineering self-aware and self-adaptive software systems in a reusable manner, architectural patterns and the related methodology provide an unified solution to handle the recurring problems in the engineering process. However, in existing patterns and methods, domain knowledge and engineers’ expertise that is built over time are not explicitly linked to the self-aware processes. This link

The need to adaptively manage computer systems and networks so as to offer good Quality of Service (QoS) and Quality of Experience (QoE) with secure operation at relatively low levels of energy consumption is challenged by their sheer complexity and the wide variability of the workloads. A possible way forward is through self-awareness, whereby self-measurement and self-observation, together with on-line

A multitude of autonomous robotic platforms collectively organized as a swarm attracts increasing attention for remote sensing and exploration tasks. A navigation system is essential for the swarm to collectively localize itself as well as external sources. In this article, we propose a self-aware swarm navigation system that is conscious of the causality between its position and the localization uncertainty

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

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Multienergy systems (MESs) are able to unlock the energy system flexibility using the coupling across multiple energy sectors. Such coupling contributes to improving the overall energy efficiency and promoting the accommodation of renewable energy. Among a wide range of literature, this article provides a perspective of network analytics on how to model, optimize, and conduct low-carbon analysis on

This article reviews modern district heating systems (DHS), with the main emphasis on the new challenges in modeling, operation, and planning. We give a brief historical overview of evolution of heating systems around the world and provide the description of DHS in the countries where they constitute a substantial component of the energy supply infrastructure. Main modeling approaches are then reviewed

Multienergy systems (MES) can optimally deploy their internal operational flexibility to use combinations of different energy vectors to meet the needs of end-users and potentially support the wider system. Key relevant applications of MES are multienergy districts (MEDs) with, for example, integrated electricity and gas distribution and district heating networks. Simulation and optimization of MEDs

Multicarrier energy systems (MCESs) are characterized by strong coordination in operation and planning across multiple energy vectors and/or sectors to deliver reliable, cost-effective energy services to end users/customers with minimal impact on the environment. They have efficiency and flexibility benefits and are deployed in large and small scales on the supply and demand sides and at the network

In a multienergy framework, power-to-heat technology is becoming increasingly attractive. This interest is mainly due to the possibility of exploiting excesses and unbalances of electricity, which are becoming more and more common with the increasing capacity of the renewable sources. An interesting option consists in using heat pumps to convert excess of electricity produced by photovoltaic systems

Rail traffic systems are widely acknowledged to be an alternative green transportation for goods and people due to their higher mobility, energy efficiency (EE), and/or substantially lower environmental impact than conventional transportation systems. Railway communications have attracted significant attention due to its potential for not only improving operational mobility, safety, and reliability

Railway communications has attracted significant attention from both academia and industries due to the booming development of railways, especially high-speed railways (HSRs). To be in line with the vision of future smart rail communications, the rail transport industry needs to develop innovative communication network architectures and key technologies that ensure high-quality transmissions for both

The accuracies for many pattern recognition tasks have increased rapidly year by year, achieving or even outperforming human performance. From the perspective of accuracy, pattern recognition seems to be a nearly solved problem. However, once launched in real applications, the high-accuracy pattern recognition systems may become unstable and unreliable due to the lack of robustness in open and changing

This is a survey article on the information transmission capability of haptic devices and ways of maximizing it. It is intended for readers who are engineering professionals interested in developing novel haptic interfaces for a variety of applications but are not necessarily trained in haptic science or human user research. We posit that the ultimate goal of any interface is the exchange of information

Indoor areas, such as offices and shopping malls, are a natural environment for initial millimeter-wave (mmWave) deployments. Although we already have the technology that enables us to realize indoor mmWave deployments, there are many remaining challenges associated with system-level design and planning for such. The objective of this article is to bring together multiple strands of research to provide

The role of modeling and simulation in development and operational planning of gas distribution networks is crucially important for system designers and operators, since it allows to get a detailed knowledge of the hydraulic properties of the network. The challenges in simulation of gas distribution networks are usually that of computational efficiency of the methods due to large dimensionality of

This article reviews recent works applying machine learning (ML) techniques in the context of energy systems’ reliability assessment and control. We showcase both the progress achieved to date as well as the important future directions for further research, while providing an adequate background in the fields of reliability management and of ML. The objective is to foster the synergy between these

Multienergy systems (MES), in which multiple energy vectors are integrated and optimally operated, are key assets in low-carbon energy systems. Multienergy interactions of distributed energy resources via different energy networks generate the so-called distributed MES (DMES). While it is now well recognized that DMES can provide power system flexibility by shifting across different energy vectors

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For ac electricity grids, the aim has always been at low-cost and disruption-proof solutions. The power grid is inherently vulnerable to environmental disturbances. However, the introduction of power electronics (PEs) and changes in load and generator characteristics have introduced a game changer at an unprecedented pace over the last decade. During this change, load specifications, load characteristics

Being able to manipulate and control light flows at small scales holds the promise to open groundbreaking opportunities for a variety of technologies. Consider, for instance, the challenges currently faced in the world of computing: as data rates and processing demands increase worldwide at an exponential rate, we are facing unsustainable increases in energy consumption associated with data centers

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

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Since its inception, the semiconductor industry has used a physical dimension (the minimum gate length of a transistor) as a means to gauge continuous technology advancement. This metric is all but obsolete today. As a replacement, we propose a density metric, which aims to capture how advances in semiconductor device technologies enable system-level benefits. The proposed metric can be used to gauge

Since its inception, the semiconductor industry has used the physical dimension (the gate length) as a means to gauge its continuous advancement. This metric is all but obsolete today. In this month’s opinion piece, the authors examine historical trends and analyze how device technology provides for benefits at the system level, and propose a new density metric. This density metric aims to capture

Domain-specific hardware is becoming a promising topic in the backdrop of improvement slow down for general-purpose processors due to the foreseeable end of Moore’s Law. Machine learning, especially deep neural networks (DNNs), has become the most dazzling domain witnessing successful applications in a wide spectrum of artificial intelligence (AI) tasks. The incomparable accuracy of DNNs is achieved

Providing connectivity to around half of the world population living in rural or underprivileged areas is a tremendous challenge, but, at the same time, a unique opportunity. Access to the Internet would provide the population living in these areas a possibility to progress on the educational, health, environment, and business levels. In this article, a survey of technologies for providing connectivity