Special Issue "New Technologies for Smart Distribution Grid"

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

Deadline for manuscript submissions: 31 March 2020.

Special Issue Editors

Dr. Mario Mañana
E-Mail Website
Guest Editor
Department of Electrical and Energy Engineering, University of Cantabria, Avda. Los Castros s/n, 39005, Santander, Spain
Interests: smart grids, power quality, grid integration of renewable energies, energy efficiency
Dr. Ahmed Zobaa
E-Mail Website
Guest Editor
Electronic and Computer Engineering, College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge UB8 3PH, Middlesex, UK
Interests: power quality, (marine) renewable energy, smart grids, energy efficiency, and lighting applications
Special Issues and Collections in MDPI journals
Dr. Alfredo Vaccaro
E-Mail Website
Guest Editor
Department of Engineering, University of Sannio, Piazza Roma 21, 82100, Benevento, Italy
Interests: power systems analysis; reliable computing; decentralized optimization; self-organizing sensor networks; renewable power generators
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Electrical networks have undergone a great transformation during the last decade due to the technological advances in all fields of knowledge related to the generation, transport and distribution of electrical energy.

As electricity is becoming the key player in a low carbon economy, researchers are devoting more effort towards improving control and measurement systems.

At the same time, distribution networks incorporate new usage paradigms, such as electric vehicles and distributed generation systems based on renewable energies.

In this new scenario, power quality and the resilience of electrical networks to overcome fault conditions are critical issues.

The main aim of this Special Issue is to seek top-quality contributions that underline emerging applications and address recent breakthroughs in all aspects of “New Technologies for Smart Grids”. Potential topics include but are not limited to the following:

  • EV charging technologies.
  • Distributed generation.
  • Protection and fault detection.
  • Power quality issues.
  • Metering.
  • Blockchain.
  • Cyber security.
  • Maintenance.
  • New IT and communications technologies in smart grids.
  • AI techniques applied to distribution networks.
  • Smart appliances and electronic power conditioning devices.
  • Technology for self-healing and resilience networks.
  • Pilots, POC and demonstrations of applications of digital processing and communications to distribution networks.

Dr. Mario Mañana
Dr. Alfredo Vaccaro
Dr. Ahmed Zobaa
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 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 monthly 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 1400 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

  • Electric vehicles
  • Charging stations
  • Distributed power generation
  • Power system protection
  • Power distribution faults
  • Fault diagnosis and location
  • Renewable energy sources
  • Smart grids
  • Power quality
  • Artificial intelligence
  • Substation automation
  • Substation maintenance

Published Papers (2 papers)

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Research

Open AccessArticle
Optimal Home Energy Demand Management Based Multi-Criteria Decision Making Methods
Electronics 2019, 8(5), 524; https://doi.org/10.3390/electronics8050524 - 10 May 2019
Cited by 2
Abstract
From the growth of residential energy demands has emerged new approaches for load scheduling to realize better energy consumption by shifting the required demand in response to cost changes or incentive offers. In this paper, a hybrid method is proposed to optimize the [...] Read more.
From the growth of residential energy demands has emerged new approaches for load scheduling to realize better energy consumption by shifting the required demand in response to cost changes or incentive offers. In this paper, a hybrid method is proposed to optimize the load scheduling problem for cost and energy saving. The method comprises a multi-objective optimization differential evolution (MODE) algorithm to obtain a set of optimal solutions by minimizing the cost and peak of a load simultaneously, as a multi-objective function. Next, an integration of the analytic hierarchy process (AHP) and a technique for order preferences by similarity to ideal solution (TOPSIS) methods are used as multi-criteria decision making (MCDM) methods for sorting the optimal solutions’ set from the best to the worst, to enable the customer to choose the appropriate schedule time. The solutions are sorted based on the load peak and energy cost as multi-criteria. Data are for ten appliances of a household used for 24 h with a one-minute time slot. The results of the proposed method demonstrate both energy and cost savings of around 47% and 46%, respectively. Furthermore, the results are compared with other recent methods in the literature to show the superiority of the proposed method. Full article
(This article belongs to the Special Issue New Technologies for Smart Distribution Grid)
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Open AccessArticle
Two-Stage Energy Management of Multi-Smart Homes With Distributed Generation and Storage
Electronics 2019, 8(5), 512; https://doi.org/10.3390/electronics8050512 - 08 May 2019
Cited by 1
Abstract
This study presents a new two-stage hybrid optimization algorithm for scheduling the power consumption of households that have distributed energy generation and storage. In the first stage, non-identical home energy management systems (HEMSs) are modeled. HEMS may contain distributed generation systems (DGS) such [...] Read more.
This study presents a new two-stage hybrid optimization algorithm for scheduling the power consumption of households that have distributed energy generation and storage. In the first stage, non-identical home energy management systems (HEMSs) are modeled. HEMS may contain distributed generation systems (DGS) such as PV and wind turbines, distributed storage systems (DSS) such as electric vehicle (EV), and batteries. HEMS organizes the controllable appliances considering user preferences, amount of energy generated/stored and electricity price. A group of optimum consumption schedules for each HEMS is calculated by a Genetic Algorithm (GA). In the second stage, a neighborhood energy management system (NEMS) is established based on Bayesian Game (BG). In this game, HEMSs are players and their pre-determined optimal schedules are their actions. NEMS regulates the total power fluctuations by allowing the energy transfer among households. In the proposed algorithm, HEMS decreases the electricity cost of the users, while NEMS flats the load curve of the neighborhood to prevent overloading of the distribution transformer. The proposed HEMS and NEMS models are implemented from scratch. A survey of 250 participants was conducted to determine user habits. The results of the survey and the proposed system were compared. In conclusion, the proposed hybrid energy management system saves power by up to 25% and decreases cost by 8.7% on average. Full article
(This article belongs to the Special Issue New Technologies for Smart Distribution Grid)
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