Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.5
Journals
Applied Sciences
Special Issues
Innovative Smart Grid Technologies for Electric Power System Development
share announcement

Innovative Smart Grid Technologies for Electric Power System Development

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 1223

Special Issue Editors

Dr. Santiago Bogarra Rodríguez

E-Mail Website
Guest Editor
Department of Electrical Engineering, ESEIAAT, Universitat Politècnica de Catalunya, 08222 Terrassa, Spain
Interests: electric aircraft; smart grid; smart sensors; electric; power system quality
Dr. Manuel Moreno-Eguilaz

E-Mail Website
Guest Editor
Department of Electronic Engineering, Technical University of Catalonia, UPC BarcelonaTech, 08028 Barcelona, Spain
Interests: deep learning; smart IoT devices; predictive maintenance; secure communications; fault-tolerant systems; identification and control of power converters
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are delighted to welcome you to the forefront of innovation in electrical power systems with our Special Issue, "Innovative Smart Grid Technologies for Electric Power System Development".

At the heart of innovative smart grid technologies lie the evolution of smart grid development and the emergence of microgrids. These advancements resonate deeply with the global drive towards the Sustainable Development Goals and energy transition policies, which champion a spectrum of transformative technologies and strategies aimed at bolstering grid reliability, efficiency, and sustainability.

In this era of groundbreaking developments, phenomena like the rise of local energy communities in Europe and the imperative for cooperative approaches in peer-to-peer energy sharing among prosumers have brought smart grid technologies to the forefront. Meanwhile, the enhancement of existing power grids with intelligent solutions like cutting-edge sensors, connectors, and control systems facilitates real-time data collection, nurturing demand response initiatives and enriching customer engagement. Furthermore, we will delve into the profound implications of the escalating adoption of electric vehicles (EVs) on the grid and how smart grid technologies can be harnessed to effectively bolster the EV charging infrastructure. We will also explore innovative methodologies for the ongoing assessment and optimization of distribution line capacity, ultimately enhancing the overall grid efficiency.

The Integration of self-healing grids and fault detection mechanisms is paramount in preserving grid integrity, and we will delve into the critical domain of cybersecurity measures, which are indispensable in safeguarding against cyber threats. Moreover, our discussions will encompass the pivotal role of energy storage technologies, particularly batteries, in grid stabilization, load management, and the seamless integration of intermittent renewable energy sources.

This Special Issue encompasses a broad spectrum of topics, including, but not limited to, smart connectors, smart protections, energy storage systems, energy harvesting, electric vehicle (eV) integration, and dynamic distribution line rating.

We look forward to receiving your contributions.

Welcome to a future of possibilities!

Best regards,

Dr. Santiago Bogarra Rodríguez
Dr. Manuel Moreno
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. Applied Sciences 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.

Keywords

  • smart sensors
  • smart connectors
  • smart protections
  • integration of EV charging
  • incorporation of distributed energy resources
  • energy storage technologies
  • energy harvesting
  • dynamic distribution line rating

Published Papers (2 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:

Review

35 pages, 2453 KiB  
Review
Digitalization Processes in Distribution Grids: A Comprehensive Review of Strategies and Challenges
by Morteza Aghahadi, Alessandro Bosisio, Marco Merlo, Alberto Berizzi, Andrea Pegoiani and Samuele Forciniti
Appl. Sci. 2024, 14(11), 4528; https://doi.org/10.3390/app14114528 - 25 May 2024
Viewed by 443
Abstract
This systematic review meticulously explores the transformative impact of digital technologies on the grid planning, grid operations, and energy market dynamics of power distribution grids. Utilizing a robust methodological framework, over 54,000 scholarly articles were analyzed to investigate the integration and effects of [...] Read more.
This systematic review meticulously explores the transformative impact of digital technologies on the grid planning, grid operations, and energy market dynamics of power distribution grids. Utilizing a robust methodological framework, over 54,000 scholarly articles were analyzed to investigate the integration and effects of artificial intelligence, machine learning, optimization, the Internet of Things, and advanced metering infrastructure within these key subsections. The literature was categorized to show how these technologies contribute specifically to grid planning, operation, and market mechanisms. It was found that digitalization significantly enhances grid planning through improved forecasting accuracy and robust infrastructure design. In operations, these technologies enable real-time management and advanced fault detection, thereby enhancing reliability and operational efficiency. Moreover, in the market domain, they support more efficient energy trading and help in achieving regulatory compliance, thus fostering transparent and competitive markets. However, challenges such as data complexity and system integration are identified as critical hurdles that must be overcome to fully harness the potential of smart grid technologies. This review not only highlights the comprehensive benefits but also maps out the interdependencies among the planning, operation, and market strategies, underlining the critical role of digital technologies in advancing sustainable and resilient energy systems. Full article
(This article belongs to the Special Issue Innovative Smart Grid Technologies for Electric Power System Development)
►▼ Show Figures

Figure 1

47 pages, 2546 KiB  
Review
From Time-Series to Hybrid Models: Advancements in Short-Term Load Forecasting Embracing Smart Grid Paradigm
by Salman Ali, Santiago Bogarra, Muhammad Naveed Riaz, Pyae Pyae Phyo, David Flynn and Ahmad Taha
Appl. Sci. 2024, 14(11), 4442; https://doi.org/10.3390/app14114442 - 23 May 2024
Viewed by 362
Abstract
This review paper is a foundational resource for power distribution and management decisions, thoroughly examining short-term load forecasting (STLF) models within power systems. The study categorizes these models into three groups: statistical approaches, intelligent-computing-based methods, and hybrid models. Performance indicators are compared, revealing [...] Read more.
This review paper is a foundational resource for power distribution and management decisions, thoroughly examining short-term load forecasting (STLF) models within power systems. The study categorizes these models into three groups: statistical approaches, intelligent-computing-based methods, and hybrid models. Performance indicators are compared, revealing the superiority of heuristic search and population-based optimization learning algorithms integrated with artificial neural networks (ANNs) for STLF. However, challenges persist in ANN models, particularly in weight initialization and susceptibility to local minima. The investigation underscores the necessity for sophisticated predictive models to enhance forecasting accuracy, advocating for the efficacy of hybrid models incorporating multiple predictive approaches. Acknowledging the changing landscape, the focus shifts to STLF in smart grids, exploring the transformative potential of advanced power networks. Smart measurement devices and storage systems are pivotal in boosting STLF accuracy, enabling more efficient energy management and resource allocation in evolving smart grid technologies. In summary, this review provides a comprehensive analysis of contemporary predictive models and suggests that ANNs and hybrid models could be the most suitable methods to attain reliable and accurate STLF. However, further research is required, including considerations of network complexity, improved training techniques, convergence rates, and highly correlated inputs to enhance STLF model performance in modern power systems. Full article
(This article belongs to the Special Issue Innovative Smart Grid Technologies for Electric Power System Development)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop