Special Issue "Application of Internet of Things, Big Data and Artificial Intelligence in Electrical Energy and Power Systems"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: 31 August 2021.

Special Issue Editor

Prof. Dr. Eklas Hossain
E-Mail Website
Guest Editor
Electrical Engineering & Renewable Energy, Oregon Tech, 3201 Campus Drive, Klamath Falls, OR-97601, USA
Interests: Energy Systems; Smart Grids; Machine Learning; Big Data Analytics; Power Electronics ;Advanced Control System
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Special Issue Information

Dear Colleagues,

The recurrent electrical infrastructure has shifted from conventional layout to a smart scheme due to the inception of renewable energy technology. Newly established energy and power systems integrate several state-of-the-art devices to facilitate connectivity to improve the reliability of the system. Modern electric systems are focusing towards distributed architecture, enabling continuous monitoring and two-way communication amidst the systems by providing load forecasting and cost-efficient data acquisition. However, such systems would generate myriads of data, which would require optimization to reap out indispensable information. Artificial Intelligence, Big Data, and Internet of Things are revolutionary technologies, enacting in every aspect of conventional and modern energy power systems in monitoring and harvesting data through Internet of Things, handling huge datasets using smart and efficient algorithms and predictive models to exploit the benefits of the extracted information. Big data covers the predictive and behavioral analysis of a system using uncountable data that require more advanced methods such as Artificial Intelligence, Machine Learning, Deep Learning and their variances to analyze than the traditional tools and models. In order to go through the data to produce data driven prediction or decisions, Artificial Intelligence is used. Different Artificial Intelligence techniques such as Machine Learning, Deep Learning, Neural Networks, Fuzzy Logic, Genetic Algorithm, and even hybrid combinations of such algorithms can significantly contribute to solve problems in energy and power systems. By accumulating data, the system can learn to behave as the situation requires by themselves. Such features of the system can address several known and unknown issues of electrical systems.

The main aim of this Special Issue is to seek high quality submissions which highlight emerging breakthroughs in energy and power systems and address recent developments in electrical systems and significant applications of Internet of Things, Big Data, and Artificial Intelligence in relevant research. This session would warmly welcome both review and research papers of theoretical derivations and practical development on related fields from academics and industries. Topics include, but are not limited to:

  • Emerging technologies in energy and power systems
  • Advanced metering infrastructures in electrical systems
  • Design of control and communication devices in energy systems
  • Electrical system standards, policies, and regulations
  • Developments in Internet of Things technology in electrical systems
  • Application of Big Data in energy and power systems
  • Data management and grid analytics in electrical systems
  • Application of Artificial Intelligence, Machine Learning and Deep Learning algorithms in energy and power systems
  • Classification and forecasting in power and energy systems and utility grid

Prof. Dr. Eklas Hossain
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Electronics 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 1800 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.

Published Papers (3 papers)

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Research

Article
Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks
Electronics 2021, 10(9), 1068; https://doi.org/10.3390/electronics10091068 - 30 Apr 2021
Cited by 1 | Viewed by 668
Abstract
Many algorithms use clustering to improve vehicular ad hoc network performance. The expected points of many of these approaches support multiple rounds of data to the roadside unit and constantly include clustering in every round of single-hop data transmission towards the road side [...] Read more.
Many algorithms use clustering to improve vehicular ad hoc network performance. The expected points of many of these approaches support multiple rounds of data to the roadside unit and constantly include clustering in every round of single-hop data transmission towards the road side unit; however, the clustering in every round maximizes the number of control messages and there could be the possibility of collision and decreases in network energy. Multi-hop transmission prolongs the cluster head node’s lifetime and boosts the network’s efficiency. Accordingly, this article proposes a new fuzzy-clustering-based routing algorithm to benefit from multi-hop transmission clustering simultaneously. This research has analyzed the limitation of clustering in each round, different algorithms were used to perform the clustering, and multi-hop routing was used to transfer the data of every cluster to the road side unit. The fuzzy logic was used to choose the head node of each cluster. Three parameters, (1) distance of each node, (2) remaining energy, and (3) number of neighbors of every node, were considered as fuzzy criteria. The results of this research were compared to various other algorithms in relation to parameters like dead node in every round, first node expire, half node expire, last node expire, and the network lifetime. The simulation results show that the proposed approach outperforms other methods. On the other hand, the vehicular ad hoc network (VANET) environment is vulnerable at the time of data transmission. The NS-2 software tool was used to simulate and evaluate the proposed fuzzy logic opportunistic routing’s performance results concerning end-to-end delay, packet delivery, and network throughput. We compare to the existing protocols, such as fuzzy Internet of Things (IoT), two fuzzy, and Fuzzy-Based Driver Monitoring System (FDMS). The performance comparison also emphasizes an effective utilization of the resources. Simulations on the highway environment show that the suggested protocol has an improved Quality of Service (QoS) efficiency compared to the above published methods in the literature. Full article
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Article
Suppressing Voltage Spikes of MOSFET in H-Bridge Inverter Circuit
Electronics 2021, 10(4), 390; https://doi.org/10.3390/electronics10040390 - 05 Feb 2021
Cited by 1 | Viewed by 755
Abstract
Power electronics devices are made from semiconductor switches such as thyristors, MOSFETs, and diodes, along with passive elements of inductors, capacitors, and resistors, and integrated circuits. They are heavily used in power processing for applications in computing, communication, medical electronics, appliance control, and [...] Read more.
Power electronics devices are made from semiconductor switches such as thyristors, MOSFETs, and diodes, along with passive elements of inductors, capacitors, and resistors, and integrated circuits. They are heavily used in power processing for applications in computing, communication, medical electronics, appliance control, and as converters in high power DC and AC transmission in what is now called harmonized AC/DC networks. A converter’s operation is described as a periodic sequencing of different modes of operation corresponding to different topologies interfaced to filters made of passive elements. The performance of converters has improved considerably using high switching frequency, which leads to a significant improvement in a power converter’s performance. However, the high dv/dt through a fast-switching transient of the MOSFET is associated with parasitic components generating oscillations and voltage spikes having adverse effects on the operation of complementary switches, thereby affecting the safe operation of the power devices. In this paper, the MOSFET gate-driver circuit performance is improved to suppress the H-Bridge inverter’s voltage spikes. The proposed technique is a simple improvement to the gate driver based on the IR2112 driver (IC) by adding a capacitor to attenuate the effect of parasitic components and the freewheeling current, suppressing the negative voltage spikes. This paper’s main contribution is to improve the gate driver circuit’s capability for suppressing the voltage spikes in the H-Bridge inverter. The improved gate driver circuit is validated experimentally and is compared with the conventional gate driver. The experimental results show that the proposed technique can effectively suppress the MOSFET’s voltage spikes and oscillations. Full article
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Article
Resonant Energy Carrier Base Active Charge-Balancing Algorithm
Electronics 2020, 9(12), 2166; https://doi.org/10.3390/electronics9122166 - 17 Dec 2020
Cited by 2 | Viewed by 565
Abstract
This paper presents a single LC tank base cell-to-cell active voltage balancing algorithm for Li-ion batteries in electric vehicle (EV) applications. EV batteries face challenges in accomplishing fast balancing and high balancing efficiency with low circuit and control complexity. It addresses that LC [...] Read more.
This paper presents a single LC tank base cell-to-cell active voltage balancing algorithm for Li-ion batteries in electric vehicle (EV) applications. EV batteries face challenges in accomplishing fast balancing and high balancing efficiency with low circuit and control complexity. It addresses that LC resonant tank uses an energy carrier to transfer the voltage from an excessive voltage cell to the lowest voltage cell. The method requires 2N - 4 bidirectional MOSFET switches and a single LC resonant circuit, where N is the number of cells in the battery strings. The balancing speed is improved by allowing a short balancing path for voltage transfer and guarantees a fast balancing speed between any two cells in the battery string, and power consumption is reduced by operating all switches in zero-current switching conditions. The circuit was tested for 4400 mAh Li-ion battery cells under static, cyclic, and dynamic charging/discharging conditions. Two battery cells at the voltage 3.93 V and 3.65 V were balanced after 76 min, and the balancing efficiency is 94.8%. The result of dynamic and cyclic charging/discharging conditions shows that the balancing circuit is applicable for the energy storage devices and Li-ion battery cells for EV. Full article
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