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Towards a Sustainable Future: Addressing AI and Big Data, Energy,...
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Towards a Sustainable Future: Addressing AI and Big Data, Energy, Climate, and Public Healthcare Challenges

A special issue of Electronics (ISSN 2079-9292).

Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 5641

Special Issue Editors

Dr. Vesselin Chobanov

E-Mail Website
Guest Editor
Faculty of Automatics, Technical University of Sofia, 1000 Sofia, Bulgaria
Interests: field of grid integration challenges of renewable energy sources and prospective solutions ; complexity of power system processes; on-going transformation of power systems: impacts of renewable energies; energy transformation; impacts of prosumers and electrical vehicles; impacts of liberalization and power markets; reducing carbon footprint; amendment of legislation; grid integration challenges for power systems with high shares of fluctuating renewable energy sources (RES): trends & challenges in power system operation; role of operational flexibility in power systems; modeling and analysis of power systems and their operation
Dr. Todor Galev

E-Mail Website
Guest Editor
Research Department, Center for the Study of Democracy, 1000 Sofia, Bulgaria
Interests: energy security; innovation policies; alternative energy technologies; geopolitical dimensions of energy and financial markets
Prof. Dr. Marco Mussetta

E-Mail Website
Guest Editor
Department of Energy, Politecnico di Milano, 20133 Milano, MI, Italy
Interests: computational intelligence; optimization; machine learning; fuzzy logic; wireless sensor networks; renewable energy; photovoltaics; wind power; forecasting
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Energy Union is taking important action to address global issues, including the COVID-19 outbreak, military activity, and climate change and disasters. They must enable unrestricted cross-border energy flow and secure the supply in every EU country, for every European, making energy more secure, cheap, and sustainable.

By introducing new technologies and modernized infrastructure, the Energy Union will reduce/contain costs while creating new jobs and skills. This will lead to a more sustainable, low-carbon, and green economy, putting Europe at the forefront of renewable energy production and global warming mitigation. By addressing the challenges facing the energy industry and improving opportunities for public health development, we can work towards a more sustainable future for all.

Rapidly developing technologies cannot always ensure the security of supply, availability of energy, and sustainability of energy consumption, which necessitates a discussion of the methodologies, analyses, impacts, and issues that the energy business will face as a result of climate change as well as these aspects impact on public health.

This Special Issue aims to contribute to long-term decisions based on a scientific approach that can influence future strategic decisions and policies in the sector.

Participants can write on one of the listed topics but are not limited to:

  • Mathematical models for managing challenges—energy, climate, public health;
  • The relationship between energy poverty and energy security;
  • Diversification of the import of energy raw materials;
  • Smart control of climate resilience;
  • Energy transitions;
  • Energy availability and sustainability of energy consumption;
  • Impact of the Green Deal on Climate change and Public health;
  • Baseline risk analysis;
  • Green Healthcare Providers (Green Hospitals, etc..);
  • Energy security and sustainability of energy consumption in the context of Climate change/ Public health;
  • Opportunities to improve public health based on artificial intelligence, big data, etc.;
  • Systems of the future with impact on strategic sectors-energy, climate, and public health.

Dr. Vesselin Chobanov
Dr. Todor Galev
Dr. Marco Mussetta
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 submissions that pass pre-check are 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 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 2400 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

  • renewable energy
  • power quality
  • diversification
  • energy transition
  • energy poverty
  • energy security
  • green deal
  • climate change
  • public health
  • big data
  • AI
  • healthcare

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

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15 pages, 2921 KiB  
Article
Dynamic User Tourism Interest Modeling through Domain Information Integration: A Hierarchical Approach
by Hiroyoshi Todo, Xiliang Zhang, Zhongguo Zhang and Yuki Todo
Electronics 2024, 13(15), 2970; https://doi.org/10.3390/electronics13152970 - 27 Jul 2024
Viewed by 706
Abstract
With the exponential growth of online review platforms, understanding user preferences and interests in the tourism domain has become increasingly critical for businesses and service providers. However, extracting meaningful insights from the vast amount of available data poses a significant challenge. Traditional methods [...] Read more.
With the exponential growth of online review platforms, understanding user preferences and interests in the tourism domain has become increasingly critical for businesses and service providers. However, extracting meaningful insights from the vast amount of available data poses a significant challenge. Traditional methods often struggle to capture the nuanced and hierarchical nature of user interests within the tourism domain. This paper pioneers the integration of domain information modeling technology into the realm of online review information mining, presenting a novel approach to constructing a user tourism interest model. Unlike existing methods, which primarily rely on flat or simplistic representations of user data, our approach leverages the hierarchical structure inherent in tourism domain information modeling. By harnessing big data within the tourism domain, we construct hierarchical tourism attributes and apply a conditional random field model along with an affective dictionary to facilitate the hierarchical mining of user travel interest information. This culminates in the establishment of a comprehensive user travel interest model using advanced information modeling techniques. Building upon this foundation, we further propose a dynamic user travel interest model, showcasing its adaptability and responsiveness to changing user preferences. Finally, we validate the accuracy and effectiveness of our model through simulation experiments within a user travel recommendation system, demonstrating significant improvements over traditional methods. Full article
(This article belongs to the Special Issue Towards a Sustainable Future: Addressing AI and Big Data, Energy, Climate, and Public Healthcare Challenges)
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19 pages, 873 KiB  
Article
From Sensors to Insights: An Original Method for Consumer Behavior Identification in Appliance Usage
by Raluca Laura Portase, Ramona Tolas and Rodica Potolea
Electronics 2024, 13(7), 1364; https://doi.org/10.3390/electronics13071364 - 4 Apr 2024
Viewed by 922
Abstract
In light of the energy crisis, extensive research is being conducted to enhance load forecasting, optimize the targeting of demand response programs, and advise building occupants on actions to enhance energy performance. Cluster analysis is increasingly applied to usage data across all consumer [...] Read more.
In light of the energy crisis, extensive research is being conducted to enhance load forecasting, optimize the targeting of demand response programs, and advise building occupants on actions to enhance energy performance. Cluster analysis is increasingly applied to usage data across all consumer types. More accurate consumer identification translates to improved resource planning. In the context of Industry 4.0, where comprehensive data are collected across various domains, we propose using existing sensor data from household appliances to extract the usage patterns and characterize the resource demands of consumers from residential households. We propose a general pipeline for extracting features from raw sensor data alongside global features for clustering device usages and classifying them based on extracted time series. We applied the proposed method to real data from three different types of household devices. We propose a strategy to identify the number of existent clusters in real data. We employed the label data obtained from clustering for the classification of consumers based on data recorded on different time ranges and achieved an increase in accuracy of up to 15% when we expanded the time range for the recorded data on the entire dataset, obtaining an accuracy of over 99.89%. We further explore the data meta-features for a minimal dataset by examining the necessary time interval for the recorded data, dataset dimensions, and the feature set. This analysis aims to achieve an effective trade-off between time and performance. Full article
(This article belongs to the Special Issue Towards a Sustainable Future: Addressing AI and Big Data, Energy, Climate, and Public Healthcare Challenges)
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26 pages, 2944 KiB  
Article
Implementation of Nonlinear Controller to Improve DC Microgrid Stability: A Comparative Analysis of Sliding Mode Control Variants
by Syeda Shafia Zehra, Alberto Dolara, Muhammad Ahsan Amjed and Marco Mussetta
Electronics 2023, 12(21), 4540; https://doi.org/10.3390/electronics12214540 - 4 Nov 2023
Cited by 7 | Viewed by 1574
Abstract
Electricity generation from sustainable renewable energy sources is constantly accelerating due to a rapid increase in demand from consumers. This requires an effective energy management and control system to fulfil the power demand without compromising the system’s performance. For this application, a nonlinear [...] Read more.
Electricity generation from sustainable renewable energy sources is constantly accelerating due to a rapid increase in demand from consumers. This requires an effective energy management and control system to fulfil the power demand without compromising the system’s performance. For this application, a nonlinear barrier sliding mode controller (BSMC) for a microgrid formed with PV, a fuel cell and an energy storage system comprising a battery and supercapacitor working in grid-connected mode is implemented. The advantages of the BSMC are twofold: The sliding surface oscillates in the close vicinity of zero by adapting an optimal gain value to ensure the smooth tracking of power to its references without overestimating the gains. Secondly, it exhibits a noticeable robustness to variations and disturbance, which is the bottleneck of the problem in a grid-connected mode. The stability of the presented controllers was analyzed with the Lyapunov stability criterion. Moreover, a comparison of the BSMC with sliding mode and supertwisting sliding mode controllers was carried out in MATLAB/Simulink (2020b) with real PV experimental data. The results and the numerical analysis verify the effectiveness of the BSMC in regulating the DC bus voltage in the presence of an external disturbance under varying conventional load and environmental conditions. Full article
(This article belongs to the Special Issue Towards a Sustainable Future: Addressing AI and Big Data, Energy, Climate, and Public Healthcare Challenges)
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Review

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26 pages, 532 KiB  
Review
Conversational Agents for Energy Awareness and Efficiency: A Survey
by Manuela Sanguinetti and Maurizio Atzori
Electronics 2024, 13(2), 401; https://doi.org/10.3390/electronics13020401 - 18 Jan 2024
Viewed by 1462
Abstract
The need to reduce greenhouse gas emissions and promote energy efficiency is crucial to achieve the energy transition and sustainable development goals. The availability of tools that provide clear information on energy consumption plays a key role in this transition, enabling users to [...] Read more.
The need to reduce greenhouse gas emissions and promote energy efficiency is crucial to achieve the energy transition and sustainable development goals. The availability of tools that provide clear information on energy consumption plays a key role in this transition, enabling users to monitor, manage, and optimize their energy use. This process, commonly referred to as energy feedback or eco-feedback, involves delivering information regarding energy usage and potentially suggesting more sustainable practices. Within the range of available tools, conversational agents can represent a valuable channel to receive detailed information about energy consumption and tailored advice for improving energy efficiency. The aim of this article is thus to explore the application of conversational agents, focusing on eco-feedback, as these tools are primarily devised to foster user awareness of energy usage and enhance more participatory conservation strategies. To this end, we conducted a keyword-based search of major scientific article databases, applying strict criteria to select relevant studies. The results of the collection showed that there is a very diverse landscape with respect to this topic. The surveyed works exhibit a high versatility in feedback goals. Furthermore, while predominantly applied domestically, they also show potential in commercial and industrial settings. Implementation choices also vary to a great extent, while evaluation practices lack a systematic approach and highlight the need for greater consistency. In light of these remarks, we also outline possible future extensions of this type of application, exploring in particular the emerging challenges associated with the increased use of renewable sources and the rise of local decentralized energy communities. Full article
(This article belongs to the Special Issue Towards a Sustainable Future: Addressing AI and Big Data, Energy, Climate, and Public Healthcare Challenges)
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