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Special Issue "Data Mining in Smart Grids"

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

Deadline for manuscript submissions: 12 November 2019

Special Issue Editor

Guest Editor
Dr. Alfredo Vaccaro

Department of Engineering, University of Sannio, Piazza Roma 21, 82100, Benevento, Italy
Website | E-Mail
Interests: power systems analysis; reliable computing; decentralized optimization; self-organizing sensor networks; renewable power generators

Special Issue Information

Dear Colleagues,

Effective smart grid operation requires rapid decisions in a data-rich, but information limited environment. In this context, the grid sensors data-streaming could not provide the system operators with the necessary information to act on in the time frames necessary to minimize the impact of the disturbances. Even if there are fast models that can convert the data into information, the smart grid operator must deal with the challenge of not having a full understanding of the context of the information, and, therefore, the information content cannot be used with any high degree of confidence.

To address this issue, data mining has been recognized as the most promising enabling technology for improving decision-making processes, providing the right information at the right moment to the right decision maker.

This Special Issue will be focused on the emerging methodologies for data mining in Smart Grids. In this area, it will address many relevant topics, ranging from methods for uncertainty management, to advanced dispatching.

This Special Issue not only focuses on methodological breakthroughs and roadmaps in implementing the methodology, but also presents the much-needed sharing of the best practices.

Potential topics include, but are not limited to, the following:

- Fuzziness in smart grids computing

- Emerging techniques for renewable energy forecasting

- Robust and proactive solution of optimal smart grids operation

- Fuzzy-based smart grids monitoring and control frameworks

- Granular computing for uncertainty management in smart grids

- Self-organizing and decentralized paradigms for information processing

 

Dr. Alfredo Vaccaro
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 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. 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 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 (1 paper)

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Research

Open AccessArticle
A Decentralized Architecture Based on Cooperative Dynamic Agents for Online Voltage Regulation in Smart Grids
Energies 2019, 12(7), 1386; https://doi.org/10.3390/en12071386
Received: 1 March 2019 / Revised: 1 April 2019 / Accepted: 2 April 2019 / Published: 10 April 2019
PDF Full-text (2157 KB) | HTML Full-text | XML Full-text
Abstract
The large-scale integration of renewable power generators in power grids may cause complex technical issues, which could hinder their hosting capacity. In this context, the mitigation of the grid voltage fluctuations represents one of the main issues to address. Although different control paradigms, [...] Read more.
The large-scale integration of renewable power generators in power grids may cause complex technical issues, which could hinder their hosting capacity. In this context, the mitigation of the grid voltage fluctuations represents one of the main issues to address. Although different control paradigms, based on both local and global computing, could be deployed for online voltage regulation in active power networks, the identification of the most effective approach, which is influenced by the available computing resources, and the required control performance, is still an open problem. To face this issue, in this paper, the mathematical backbone, the expected performance, and the architectural requirements of a novel decentralized control paradigm based on dynamic agents are analyzed. Detailed simulation results obtained in a realistic case study are presented and discussed to prove the effectiveness and the robustness of the proposed method. Full article
(This article belongs to the Special Issue Data Mining in Smart Grids)
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