Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.6
Journals
Electronics
Special Issues
Application of Internet of Things, Big Data and Artificial Intelligence...
share announcement

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: closed (31 August 2021) | Viewed by 29997

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
Special Issues, Collections and Topics in MDPI journals

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 submissions that pass pre-check are 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 2400 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.

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

18 pages, 8573 KiB  
Article
Artificial Jellyfish Search Algorithm-Based Selective Harmonic Elimination in a Cascaded H-Bridge Multilevel Inverter
by Nimra Idris Siddiqui, Afroz Alam, Layeba Quayyoom, Adil Sarwar, Mohd Tariq, Hani Vahedi, Shafiq Ahmad and Adamali Shah Noor Mohamed
Electronics 2021, 10(19), 2402; https://doi.org/10.3390/electronics10192402 - 1 Oct 2021
Cited by 22 | Viewed by 2507
Abstract
This paper used an artificial jellyfish search (AJFS) optimizer suitable for selective harmonic elimination-based modulation for multilevel inverter (MLI) voltage control application. The main objective was to remove the undesired lower-order harmonics in the output voltage waveform of an MLI. This algorithm was [...] Read more.
This paper used an artificial jellyfish search (AJFS) optimizer suitable for selective harmonic elimination-based modulation for multilevel inverter (MLI) voltage control application. The main objective was to remove the undesired lower-order harmonics in the output voltage waveform of an MLI. This algorithm was motivated by the behavior of jellyfish in the ocean. Jellyfish have the ability to find the global best position where a large quantity of nutritious food is available. The paper applied AJFS algorithm on five, seven, and nine levels of CHB-MLI. The optimum switching angle was calculated for the entire modulation range for the desired lower-order harmonics elimination. The problem formulated to achieve the objective was solved in a MATLAB environment. The total harmonic distortion (THD) values of five-, seven-, and nine-level inverters for various modulation indexes were computed using AJFS and compared with the powerful differential evolution (DE) algorithm. The comparison of THD results clearly demonstrated superior THD in the output of CHB-MLI of the AJFS algorithm over DE and GA algorithm for low and medium values of modulation index. The experimental results further validated the better performance of the AJFS algorithm. Full article
(This article belongs to the Special Issue Application of Internet of Things, Big Data and Artificial Intelligence in Electrical Energy and Power Systems)
►▼ Show Figures

Figure 1

25 pages, 3500 KiB  
Article
Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks
by Imran Memon, Mohammad Kamrul Hasan, Riaz Ahmed Shaikh, Jamel Nebhen, Khairul Azmi Abu Bakar, Eklas Hossain and Muhammad Hanif Tunio
Electronics 2021, 10(9), 1068; https://doi.org/10.3390/electronics10091068 - 30 Apr 2021
Cited by 32 | Viewed by 3474
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
(This article belongs to the Special Issue Application of Internet of Things, Big Data and Artificial Intelligence in Electrical Energy and Power Systems)
►▼ Show Figures

Figure 1

16 pages, 5237 KiB  
Article
Suppressing Voltage Spikes of MOSFET in H-Bridge Inverter Circuit
by Ezzidin Hassan Aboadla, Sheroz Khan, Kushsairy Abdul Kadir, Zulkhairi Md Yusof, Mohamed Hadi Habaebi, Shabana Habib, Muhammad Islam, Mohammad Kamrul Hasan and Eklas Hossain
Electronics 2021, 10(4), 390; https://doi.org/10.3390/electronics10040390 - 5 Feb 2021
Cited by 6 | Viewed by 13326
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
(This article belongs to the Special Issue Application of Internet of Things, Big Data and Artificial Intelligence in Electrical Energy and Power Systems)
►▼ Show Figures

Figure 1

21 pages, 6626 KiB  
Article
Resonant Energy Carrier Base Active Charge-Balancing Algorithm
by Mohammad Kamrul Hasan, AKM Ahasan Habib, Shayla Islam, Ahmad Tarmizi Abdul Ghani and Eklas Hossain
Electronics 2020, 9(12), 2166; https://doi.org/10.3390/electronics9122166 - 17 Dec 2020
Cited by 14 | Viewed by 3441
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
(This article belongs to the Special Issue Application of Internet of Things, Big Data and Artificial Intelligence in Electrical Energy and Power Systems)
►▼ Show Figures

Figure 1

Review

Jump to: Research

18 pages, 3830 KiB  
Review
Unmanned Aerial Vehicles for Crowd Monitoring and Analysis
by Muhammad Afif Husman, Waleed Albattah, Zulkifli Zainal Abidin, Yasir Mohd. Mustafah, Kushsairy Kadir, Shabana Habib, Muhammad Islam and Sheroz Khan
Electronics 2021, 10(23), 2974; https://doi.org/10.3390/electronics10232974 - 29 Nov 2021
Cited by 14 | Viewed by 6007
Abstract
Crowd monitoring and analysis has become increasingly used for unmanned aerial vehicle applications. From preventing stampede in high concentration crowds to estimating crowd density and to surveilling crowd movements, crowd monitoring and analysis have long been employed in the past by authorities and [...] Read more.
Crowd monitoring and analysis has become increasingly used for unmanned aerial vehicle applications. From preventing stampede in high concentration crowds to estimating crowd density and to surveilling crowd movements, crowd monitoring and analysis have long been employed in the past by authorities and regulatory bodies to tackle challenges posed by large crowds. Conventional methods of crowd analysis using static cameras are limited due to their low coverage area and non-flexible perspectives and features. Unmanned aerial vehicles have tremendously increased the quality of images obtained for crowd analysis reasons, relieving the relevant authorities of the venues’ inadequacies and of concerns of inaccessible locations and situation. This paper reviews existing literature sources regarding the use of aerial vehicles for crowd monitoring and analysis purposes. Vehicle specifications, onboard sensors, power management, and an analysis algorithm are critically reviewed and discussed. In addition, ethical and privacy issues surrounding the use of this technology are presented. Full article
(This article belongs to the Special Issue Application of Internet of Things, Big Data and Artificial Intelligence in Electrical Energy and Power Systems)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop