Special Issue "Selected Papers on Power, Energy and Environmental Engineering"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "J: State-of-the-Art Energy Related Technologies".

Deadline for manuscript submissions: 15 February 2022.

Special Issue Editor

Prof. Dr. Naoyuki Ishimura
E-Mail Website
Guest Editor
Faculty of Commerce, Chuo University, Hachioji, Tokyo 192-0393, Japan
Interests: numerical analysis; mathematical finance; nonlinear analysis

Special Issue Information

Dear Colleagues,

The issue of climate change is the most pressing issue of our times. This challenge, and in particular the goal of keeping global warming below 2 degrees centigrade, requires an urgent shift to a low carbon economy. The increase in renewable energies is essential to meet climate targets without slowing economic growth and reducing well-being. Therefore, in order to address this massive challenge, we encourage frontier studies in the fields of power, energy, and environmental engineering were submitted, dealing with new developments in theory, analytical and numerical simulation and modeling, experimentation, demonstration, advanced deployment and case studies, results of laboratory or field operational tests. Sensible energy consumption has the potential to reduce the overwhelming dependence on fossil fuels, thereby improving energy security, boosting economic development and creating jobs. We hope that this Special Issue will provide a valuable place for scientific communication from various relevant fields, and enhance the progress of such areas. We highly welcome your contributions as well as invite the potential readers to join.

Prof. Dr. Naoyuki Ishimura
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 2000 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

  • Environmental restoration and ecological engineering
  • Environmental Science and Technology
  • Modelling and decision support tools
  • Clean Technologies
  • Power Control
  • Smart Grids
  • Industrial, commercial, and residential applications
  • Renewable Energy
  • Sustainable Cities

Published Papers (1 paper)

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Research

Article
Bi-Level Poisoning Attack Model and Countermeasure for Appliance Consumption Data of Smart Homes
Energies 2021, 14(13), 3887; https://doi.org/10.3390/en14133887 - 28 Jun 2021
Viewed by 464
Abstract
Accurate building energy prediction is useful in various applications starting from building energy automation and management to optimal storage control. However, vulnerabilities should be considered when designing building energy prediction models, as intelligent attackers can deliberately influence the model performance using sophisticated attack [...] Read more.
Accurate building energy prediction is useful in various applications starting from building energy automation and management to optimal storage control. However, vulnerabilities should be considered when designing building energy prediction models, as intelligent attackers can deliberately influence the model performance using sophisticated attack models. These may consequently degrade the prediction accuracy, which may affect the efficiency and performance of the building energy management systems. In this paper, we investigate the impact of bi-level poisoning attacks on regression models of energy usage obtained from household appliances. Furthermore, an effective countermeasure against the poisoning attacks on the prediction model is proposed in this paper. Attacks and defenses are evaluated on a benchmark dataset. Experimental results show that an intelligent cyber-attacker can poison the prediction model to manipulate the decision. However, our proposed solution successfully ensures defense against such poisoning attacks effectively compared to other benchmark techniques. Full article
(This article belongs to the Special Issue Selected Papers on Power, Energy and Environmental Engineering)
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