Special Issue "Microgrids/Nanogrids Implementation, Planning, and Operation"

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: 30 October 2020.

Special Issue Editors

Special Issue Information

Dear Colleagues,

Microgrids can allow a better integration of distributed energy storage capacity and renewable energy sources into the power grid, therefore increasing its efficiency and resilience to natural and man-caused disruptive events. In addition, microgrids and nanogrids are potential solutions for providing a better electrical service to both insufficiently supplied and remote areas. Microgrids networking with an optimal energy management will lead to a sort of smart grid with numerous benefits, such as reduced cost, and enhanced reliability and resiliency.

The objective of this Special Issue is to address and disseminate state-of the-art research and results on the implementation, planning, and operation of microgrids/nanogrids, for which energy management is one of the core issues. Topics of interest include, but are not limited to:

– Implementation of control and optimization techniques in grid-connected and islanded modes;

– Peer-to-peer energy management systems in community microgrid;

– Peer-to-peer energy trading in microgrids;

– Power grid resilience enhancement through microgrid facilities;

– Self-healing strategies for resilience purpose;

– Power quality assessment and improvement;

– Microgrids transformation into virtual power plants;

– Mobility-aware vehicle-to-grid control in microgrids

– Building an (nanogrid-) integrated energy management and monitoring system;

– Maritime applications: shipboard microgrids, offshore platforms, and port electrification;

– Aerospace applications: satellite microgrids, spacecraft power systems, and moon/mars station microgrids;

– Applied IoT architecture and communication technologies for smart microgrids;

– Smart enabling technologies for the effective penetration of microgrids.

Prof. Dr. Mohamed Benbouzid
Prof. S. M. Muyeen
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. 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 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 (2 papers)

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Research

Open AccessArticle
Development and Implementation of a Novel Optimization Algorithm for Reliable and Economic Grid-Independent Hybrid Power System
Appl. Sci. 2020, 10(18), 6604; https://doi.org/10.3390/app10186604 - 21 Sep 2020
Abstract
Recently, fast uptake of renewable energy sources (RES) in the world has introduced new difficulties and challenges; one of the most important challenges is providing economic energy with high efficiency and good quality. To reach this goal, many traditional and smart algorithms have [...] Read more.
Recently, fast uptake of renewable energy sources (RES) in the world has introduced new difficulties and challenges; one of the most important challenges is providing economic energy with high efficiency and good quality. To reach this goal, many traditional and smart algorithms have been proposed and demonstrated their feasibility in obtaining the optimal solution. Therefore, this paper introduces an improved version of Bonobo Optimizer (BO) based on a quasi-oppositional method to solve the problem of designing a hybrid microgrid system including RES (photovoltaic (PV) panels, wind turbines (WT), and batteries) with diesel generators. A comparison between traditional BO, the Quasi-Oppositional BO (QOBO), and other optimization techniques called Harris Hawks Optimization (HHO), Artificial Electric Field Algorithm (AEFA) and Invasive Weed Optimization (IWO) is carried out to check the efficiency of the proposed QOBO. The QOBO is applied to a stand-alone hybrid microgrid system located in Aswan, Egypt. The results show the effectiveness of the QOBO algorithm to solve the optimal economic design problem for hybrid microgrid power systems. Full article
(This article belongs to the Special Issue Microgrids/Nanogrids Implementation, Planning, and Operation)
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Open AccessArticle
Long-Term Forecasting Potential of Photo-Voltaic Electricity Generation and Demand Using R
Appl. Sci. 2020, 10(13), 4462; https://doi.org/10.3390/app10134462 - 28 Jun 2020
Abstract
For micro-grid cost-benefit analyses, both energy production and demand must be estimated on the long-term of one year. However, there remains a scarcity of studies predicting energy production and demand simultaneously and in the long-term. By means of programming in R and applying [...] Read more.
For micro-grid cost-benefit analyses, both energy production and demand must be estimated on the long-term of one year. However, there remains a scarcity of studies predicting energy production and demand simultaneously and in the long-term. By means of programming in R and applying linear, non-linear, and support vector regression, we show the in depth analysis of the data of a micro-grid on solar power generation and building energy demand and its potential to be modeled simultaneously on the term of one year, in relation to electricity costs. We found solar power generation is linearly related to solar irradiance, but the effect of temperature on total output was less pronounced than anticipated. Building energy demand was found to be related to multiple parameters of both time and weather, and could be estimated through a quadratic function in relation to temperature. Models for both solar power generation and building energy demand could predict electricity costs within 8% of actual costs, which is not yet the ideal accuracy, but shows potential for future studies. These results provide important statistics for future studies where building energy consumption of any building type is correlated in detail to various time and weather parameters. Full article
(This article belongs to the Special Issue Microgrids/Nanogrids Implementation, Planning, and Operation)
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