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Special Issue "Smart Energy Management for Smart Grids 2019"

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: 31 January 2019

Special Issue Editors

Guest Editor
Prof. Dr. José L. Bernal-Agustín

Electrical Engineering. Department, University of Zaragoza. Calle María de Luna, 3. 50018 Zaragoza, Spain
Website | E-Mail
Phone: +34 976 76 19 21
Fax: +34 976 76 22 26
Interests: evolutionary computation applications to engineering; renewable energy; distribution power system; energy management; electric markets
Guest Editor
Prof. Dr. Rodolfo Dufo-López

Electrical Engineering. Department, University of Zaragoza. Calle María de Luna, 3. 50018 Zaragoza, Spain
Website | E-Mail
Interests: renewable energy; distribution power systems; electricity storage; net metering; energy management; optimization algorithms

Special Issue Information

Dear Colleagues,

Electricity networks have evolved over the last few years, improving their reliability and increasing their functionality. These changes have led to the development of smart grids.

Smart grids allow communication between the different agents of the electrical system, and the interaction of these agents with the equipment, devices and software that are part of the smart grids. One notable, but not the only, feature of smart grids is their application in energy management. The possibility of transmitting information from metering equipment to electricity companies and consumers allows for proper demand management, both from the point of view of the companies and the consumer. Energy management through smart grids improves safety and quality by adequately monitoring the different elements of the grid, and facilitates the use of new storage technologies, the renewable energies integration, the implementation of electric vehicles and self-consumption systems.

Many aspects must be taken into account to ensure that smart grids function properly, including the development of control and measurement devices, communication systems and the software required to manage all devices, reducing costs and maximizing reliability.

Taking into account all the above, this Special Issue is dedicated to topics related to “Smart Energy Management for Smart Grids”, including both technical and economic topics.

Prof. Dr. José L. Bernal-Agustín
Prof. Dr. Rodolfo Dufo-López
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. Energies 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 1600 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 metering
  • Load management
  • Energy management
  • Energy storage
  • Communication systems
  • Electrical grid protection
  • Grid connected renewable generation
  • Distributed generation
  • Self-consumption
  • Vehicle-to-Grid (V2G)
  • Load forecasting

Published Papers (1 paper)

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Research

Open AccessArticle QoE-Aware Smart Home Energy Management Considering Renewables and Electric Vehicles
Energies 2018, 11(9), 2304; https://doi.org/10.3390/en11092304
Received: 13 August 2018 / Revised: 29 August 2018 / Accepted: 30 August 2018 / Published: 1 September 2018
PDF Full-text (755 KB) | HTML Full-text | XML Full-text
Abstract
To reduce the peak load and electricity bill while preserving the user comfort, a quality of experience (QoE)-aware smart appliance control algorithm for the smart home energy management system (sHEMS) with renewable energy sources (RES) and electric vehicles (EV) was proposed. The proposed
[...] Read more.
To reduce the peak load and electricity bill while preserving the user comfort, a quality of experience (QoE)-aware smart appliance control algorithm for the smart home energy management system (sHEMS) with renewable energy sources (RES) and electric vehicles (EV) was proposed. The proposed algorithm decreases the peak load and electricity bill by deferring starting times of delay-tolerant appliances from peak to off-peak hours, controlling the temperature setting of heating, ventilation, and air conditioning (HVAC), and properly scheduling the discharging and charging periods of an EV. In this paper, the user comfort is evaluated by means of QoE functions. To preserve the user’s QoE, the delay of the starting time of a home appliance and the temperature setting of HVAC are constrained by a QoE threshold. Additionally, to solve the trade-off problem between the peak load/electricity bill reduction and user’s QoE, a fuzzy logic controller for dynamically adjusting the QoE threshold to optimize the user’s QoE was also designed. Simulation results demonstrate that the proposed smart appliance control algorithm with a fuzzy-controlled QoE threshold significantly reduces the peak load and electricity bill while optimally preserving the user’s QoE. Compared with the baseline case, the proposed scheme reduces the electricity bill by 65% under the scenario with RES and EV. Additionally, compared with the method of optimal scheduling of appliances in the literature, the proposed scheme achieves much better peak load reduction performance and user’s QoE. Full article
(This article belongs to the Special Issue Smart Energy Management for Smart Grids 2019)
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