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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 18882

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Dr. Francesco Bellotti

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Electrical, Electronics and Telecommunication Engineering and Naval Architecture Department, University of Genoa, 16145 Genoa, Italy
Interests: electric vehicles; intelligent transportation systems; edge computing; Internet of Things; cyber–physical systems; human–computer interaction; serious games; deep learning, machine learning; object detection; trajectory prediction; reinforcement learning; datasets
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Dr. Riccardo Berta

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Electrical, Electronics and Telecommunication Engineering and Naval Architecture Department (DITEN), University of Genoa, Via Opera Pia 11/A, 16145 Genova, GE, Italy
Interests: applications of electronic systems; technology-enhanced learning; internet of things; games; electric vehicles charging
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Special Issue Information

Dear colleagues,

Bringing ever more intelligence to the operational fields, Internet-of-Things (IoT) systems promise to significantly improve the processes of energy generation, distribution, and utilization.

IoT supports real-time monitoring, situational awareness and intelligence, control, and cyber security, which can make the energy eco-system more effective, efficient, secure, reliable, resilient. Insights from data collected from field devices could be used to develop new services, improve real-time decision-making, solve critical problems, reduce wastage, early detect maintenace issues, enhance energy access also by poorer people.

Achieving these targets requires developing complex hardware/software systems, spanning from the edge to the cloud, in a variety of application domains and dealing with issues such as scalability, interoperability, safety, security, consumption, pollution.

The goal of this Special Issue is to present and discuss IoT-based solutions that advance the technological state of the art of energy-related applications.

Prof. Dr. Francesco Bellotti
Prof. Dr. Riccardo Berta
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

internet of things
edge computing
cloud computing
embedded systems and applications
cyber-physical systems
energy distribution
energy harvesting
smart grid

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Tiny Machine Learning for Energy Applications in Energies

Published Papers (5 papers)

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Research

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17 pages, 2906 KiB

Open AccessArticle

IoT Solution for AI-Enabled PRIVACY-PREServing with Big Data Transferring: An Application for Healthcare Using Blockchain

by Mohamed Elhoseny, Khalid Haseeb, Asghar Ali Shah, Irshad Ahmad, Zahoor Jan and Mohammed. I. Alghamdi

Energies 2021, 14(17), 5364; https://doi.org/10.3390/en14175364 - 28 Aug 2021

Cited by 20 | Viewed by 2617

Abstract

Internet of Things (IoT) performs a vital role in providing connectivity between computing devices, processes, and things. It significantly increases the communication facilities and giving up-to-date information to distributed networks. On the other hand, the techniques of artificial intelligence offer numerous and valuable services in emerging fields. An IoT-based healthcare solution facilitates patients, hospitals, and professionals to observe real-time and critical data. In the literature, most of the solution suffers from data intermission, high ethical standards, and trustworthiness communication. Moreover, network interruption with recurrent expose of sensitive and personal health data decreases the reliance on network systems. Therefore, this paper intends to propose an IoT solution for AI-enabled privacy-preserving with big data transferring using blockchain. Firstly, the proposed algorithm uses a graph-modeling to develop a scalable and reliable system for gathering and transmitting data. In addition, it extracts the subset of nodes using the artificial intelligence approach and achieves efficient services for the healthcare system. Secondly, symmetric-based digital certificates are utilized to offer authentic and confidential transmission with communication resources using blockchain. The proposed algorithm is explored with existing solutions through multiple simulations and proved improvement in terms of realistic parameters. Full article

(This article belongs to the Special Issue IoT Systems for Energy Applications)

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11 pages, 6299 KiB

Open AccessArticle

Optimal Cloud Orchestration Model of Containerized Task Scheduling Strategy Using Integer Linear Programming: Case Studies of IoTcloudServe@TEIN Project

by Nawat Swatthong and Chaodit Aswakul

Energies 2021, 14(15), 4536; https://doi.org/10.3390/en14154536 - 27 Jul 2021

Cited by 1 | Viewed by 1860

Abstract

As a playground for cloud computing and IoT networking environment, IoTcloudServe@TEIN has been established in the Trans-Eurasia Information Network (TEIN). In the IoTcloudServe@TEIN platform, a cloud orchestration for conducting the flow of IoT task demands is imperative for effectively improving performance. In this paper, we propose the model of optimal containerized task scheduling in cloud orchestration that maximizes the average payoff from completing tasks within the whole cloud system with different levels of cloud hierarchies. Based on integer linear programming, the model can take into account demand requirement and resource availability in terms of storage, computation, network, and splittable task granularity. To show the insights obtainable from the proposed model, the edge-core cluster of IoTcloudServe@TEIN and its peer-to-peer federated cloud scenario with OF@TEIN+ are numerically experimented and herein reported. To evaluate the model’s performance, payoff level and task completion time are considered by comparing with a well-known round-robin scheduling algorithm. The proposed ILP model can be a guideline for the cloud orchestration in IoTcloudserve@TEIN because of the lower task completion time and the higher payoff level especially upon the large demand growth, which is the major operation range of concerns in practice. Moreover, the proposed model illustrates mathematically the significance of implementing cloud architecture with refined splittable task granularity via the light-weighted container technology that has been used as the basis for IoTcloudServe@TEIN clustering design. Full article

(This article belongs to the Special Issue IoT Systems for Energy Applications)

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19 pages, 4612 KiB

Open AccessArticle

Cloud Based IoT Solution for Fault Detection and Localization in Power Distribution Systems

by Mussawir Ul Mehmood, Abasin Ulasyar, Abraiz Khattak, Kashif Imran, Haris Sheh Zad and Shibli Nisar

Energies 2020, 13(11), 2686; https://doi.org/10.3390/en13112686 - 26 May 2020

Cited by 17 | Viewed by 3749

Abstract

Power restoring time in power distribution systems (PDS) can be minimized by using efficient fault localization techniques. This paper proposes a novel, robust and scalable cloud based internet of things (IoT) solution for identification and localization of faults in PDS. For this purpose, a new algorithm is developed that can detect single and multiple simultaneous faults in the presence of single and multiple device or sensor failures. The algorithm has utilized a zone based approach that divides a PDS into different zones. A current sensing device (CSD) was deployed at the boundary of a zone. The function of CSD is to provide time synchronized current measurements and communicate with a cloud server through an edge device (ED). Another contribution of this research work is the unique implementation of context aware policy (CAP) in ED. Due to CAP, only those measurements are transmitted to cloud server that differ from the previously transmitted measurements. The cloud server performed calculations at regular intervals to detect faults in PDS. A relational database model was utilized to log various fault events that occur in PDS. An IEEE 37 node test feeder was selected as PDS to observe the performance of our solution. Two test cases were designed to simulate individual and multiple simultaneous faults in PDS. A third test case was implemented to demonstrate the robustness and scalability of proposed solution to detect multiple simultaneous faults in PDS when single and multiple sensor failures were encountered. It was observed that the new algorithm successfully localized the faults for all the three cases. Consequently, significant reductions were noticed in the amount of data that was sent to the cloud server. In the end, a comparison study of a proposed solution was performed with existing methods to further highlight the benefits of our technique. Full article

(This article belongs to the Special Issue IoT Systems for Energy Applications)

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14 pages, 8023 KiB

Open AccessArticle

A Multi-Tone Rectenna System for Wireless Power Transfer

by Simone Ciccia, Alberto Scionti, Giuseppe Franco, Giorgio Giordanengo, Olivier Terzo and Giuseppe Vecchi

Energies 2020, 13(9), 2374; https://doi.org/10.3390/en13092374 - 09 May 2020

Cited by 1 | Viewed by 2086

Abstract

Battery-less sensors need a fast and stable wireless charging mechanism to ensure that they are being correctly activated and properly working. The major drawback of state-of-the-art wireless power transfer solutions stands in the maximum Equivalent Isotropic Radiated Power (EIRP) established from local regulations, even using directional antennas. Indeed, the maximum transferred power to the load is limited, making the charging process slow. To overcome such limitation, a novel method for implementing an effective wireless charging system is described. The proposed solution is designed to guarantee many independent charging contributions, i.e., multiple tones are used to distribute power along transmitted carriers. The proposed rectenna system is composed by a set of narrow-band rectifiers resonating at specific target frequencies, while combining at DC. Such orthogonal frequency schema, providing independent charging contributions, is not affected by the phase shift of incident signals (i.e., each carrier is independently rectified). The design of the proposed wireless-powered system is presented. The main advantage of the solution is the voltage delivered to the load, which is directly proportional to the number of used carriers. This is fundamental to ensure fast sensor wakes-up and functioning. To demonstrate the feasibility of the proposed system, the work has been complemented with the manufacturing of two rectennas, and the analysis of experimental results, which also validated the linear relationship between the number of used carriers. Full article

(This article belongs to the Special Issue IoT Systems for Energy Applications)

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Review

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24 pages, 1167 KiB

Open AccessReview

A Comprehensive Review on IoT Protocols’ Features in Smart Grid Communication

by Lilia Tightiz and Hyosik Yang

Energies 2020, 13(11), 2762; https://doi.org/10.3390/en13112762 - 01 Jun 2020

Cited by 97 | Viewed by 7513

Abstract

Since the smart grid deals with a large mass of data and critical missions, it requires ubiquitous, reliable, and real-time communication. The Internet of Things (IoT) technology, which has the potential of connecting all objects over the globe through the Internet, excels in providing robust information transmission infrastructure in the smart grid. There are a multitude of possible protocols, standards, and configurations for communication in the smart grid. A commonly applied communication standard IEC 61850 recommends the use of Manufacturing Message Specification (MMS) protocol for communication in Local Area Network (LAN) and eXtensible Messaging and Presence Protocol (XMPP) in Wide Area Network (WAN). However, a plethora of research on this topic compares the behavior of other IoT protocols and standard recommendations in the smart grid. On the other hand, the sky-rocketing penetration of Renewable Energy Sources (RES), especially in the form of micro grid, transformed the central control structure of the smart grid into a distributed style called Multi-Agent Systems (MAS). This new approach defined new communication requirements and more particular IoT protocol characteristic requirements. However, a limited number of the existing studies have considered IoT protocol characteristic requirements of the smart grid and its new control structures. In this paper, we initially investigate the communication requirements of the smart grid and introduce all IoT protocols and their specifications. We analyze IoT protocol characteristics and performances in the smart grid through literature review based on the smart grid communication requirements. In this approach, we highlight weak points of these practices making them fail to acquire the holistic guidelines in utilizing proper IoT protocol that can meet the smart grid environment interaction requirements. Using the existing facilities, the public Internet, we follow the arrangement of cost-effective high penetration communication requirements for new structures of the smart grid, i.e., the MAS and multi-micro grid. In this case, we consider IoT protocol Quality of Services (QoS) requirements, especially in the case of security and reliability, to satisfy stakeholders, namely utilities and prosumers. Addressing effective elements in applying IoT in the smart grid’s future trends is another contribution to this paper. Full article

(This article belongs to the Special Issue IoT Systems for Energy Applications)

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