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Special Issue "Energy Processing and Smart Grid"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (2 December 2022) | Viewed by 2117

Special Issue Editors

Dr. Shriram Srinivasarangan Rangarajan
E-Mail Website
Guest Editor
1. Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, USA
2. Dayananda Sagar College of Engineering, Bengaluru, Karnataka, India
Interests: power systems; power electronics; smart grid; flexible AC transmission system (FACTS); power system stability; renewable energy system—PV and wind; smart inverters; power quality; distribution systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Tomonobu Senjyu
E-Mail Website
Guest Editor
Department of Electrical and Electronics Engineering, University of the Ryukyus, Nishihara, Okinawa 903-0213, Japan
Interests: high-efficiency energy conversion system; renewable energy in small islands; optimization of power system operation and control
Special Issues, Collections and Topics in MDPI journals
Dr. Hany A. Abdelsalam
E-Mail Website
Guest Editor
Electrical Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafr El-Sheikh 33516, Egypt
Interests: distribution system resiliency improvement; integration of renewable energy in power system; power system control and optimization; smart grid; real-time tuning and control of power system; power quality
Prof. Dr. E. Randolph Collins
E-Mail Website1 Website2
Guest Editor
Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, USA
Interests: power distribution systems; power electronics; electric machines; adjustable speed motor drives; electric power quality monitoring; grid connected inverters; renewable energy systems - PV and wind; smart inverters; distributed generation; electronic lighting and control; hardware-in-the-loop grid simulator
Special Issues, Collections and Topics in MDPI journals
Dr. Umashankar Subramaniam
E-Mail Website
Guest Editor
Department of Communications and Networks, Renewable Energy Lab, College of Engineering, Prince Sultan University, Riyadh 11586, Saudi Arabia
Interests: renewable energy with special interest in wind and solar energy; grid integration of renewable energy systems; machine learning & deep learning; V-G and G-V in EV using smart grid technologies; fast and wireless charging technologies for EV; power quality and auditing; real time power system simulator with energy storage and smart grid; big data and block chain applications in microgrids; energy efficiency improvements; reliability engineering; optimization using PSO; GA
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Guest Editors are inviting submissions for a Special Issue of Energies on the subject area of “Energy processing and Smart Grid.” The interdisciplinary applications with the involvement of several combined forces have led to the transformation of a traditional power system into a smarter domain. Such an empowerment of a traditional power system has become the need of the hour. The smart grid involves multidisciplinary domains that includes renewables and EVs, intelligent power electronics, intelligent decision and control systems, smart communication systems, computational intelligence, visual and data analytics, cyber security, intelligent measurements, and many more reliable aspects associated with the power system network.

This Special Issue focuses on the technological advancements in a smart grid environment that includes all applications of power systems and power electronics.

Topics of interest for publication include but are not limited to:

  • Technological advancements in all domains of power systems and power electronics;
  • Smart grid;
  • Electric machines and drives;
  • Transmission and distribution;
  • Renewable energy systems;
  • Electric vehicles (V2G and G2V);
  • Power-electronics based distributed generators;
  • HVDC and FACTS devices;
  • AC and DC microgrid systems;
  • Artificial intelligence, machine learning, and IoT in power systems and power electronics;
  • Power electronics in smart grid;
  • Smart inverters;
  • Digital signal processing in energy systems;
  • Power electronic converters;
  • Power quality;
  • Topologies and control of power electronic converters;
  • Energy storage technologies;
  • Power semiconductor devices;
  • Electric/hybrid vehicle converters and other transportation systems;
  • Industrial, commercial, and residential applications of power converters;
  • Multilevel converters;
  • Power electronics applications in power systems;
  • Control applications in power systems and power electronics.

Dr. Shriram Srinivasarangan Rangarajan
Prof. Dr. Tomonobu Senjyu
Dr. Hany A. Abdelsalam
Dr. E. Randolph Collins
Dr. Umashankar Subramaniam
Guest Editors

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. 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 2200 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

  • Power systems
  • Power electronics
  • Smart grid
  • Electric vehicles
  • Renewable energy

Published Papers (1 paper)

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Research

Article
A Classy Multifacet Clustering and Fused Optimization Based Classification Methodologies for SCADA Security
Energies 2022, 15(10), 3624; https://doi.org/10.3390/en15103624 - 15 May 2022
Cited by 9 | Viewed by 950
Abstract
Detecting intrusions from the supervisory control and data acquisition (SCADA) systems is one of the most essential and challenging processes in recent times. Most of the conventional works aim to develop an efficient intrusion detection system (IDS) framework for increasing the security of [...] Read more.
Detecting intrusions from the supervisory control and data acquisition (SCADA) systems is one of the most essential and challenging processes in recent times. Most of the conventional works aim to develop an efficient intrusion detection system (IDS) framework for increasing the security of SCADA against networking attacks. Nonetheless, it faces the problems of complexity in classification, requiring more time for training and testing, as well as increased misprediction results and error outputs. Hence, this research work intends to develop a novel IDS framework by implementing a combination of methodologies, such as clustering, optimization, and classification. The most popular and extensively utilized SCADA attacking datasets are taken for this system’s proposed IDS framework implementation and validation. The main contribution of this work is to accurately detect the intrusions from the given SCADA datasets with minimized computational operations and increased accuracy of classification. Additionally the proposed work aims to develop a simple and efficient classification technique for improving the security of SCADA systems. Initially, the dataset preprocessing and clustering processes were performed using the multifacet data clustering model (MDCM) in order to simplify the classification process. Then, the hybrid gradient descent spider monkey optimization (GDSMO) mechanism is implemented for selecting the optimal parameters from the clustered datasets, based on the global best solution. The main purpose of using the optimization methodology is to train the classifier with the optimized features to increase accuracy and reduce processing time. Moreover, the deep sequential long short term memory (DS-LSTM) is employed to identify the intrusions from the clustered datasets with efficient data model training. Finally, the proposed optimization-based classification methodology’s performance and results are validated and compared using various evaluation metrics. Full article
(This article belongs to the Special Issue Energy Processing and Smart Grid)
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