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Materials and Energy in Negative and Neutral Carbon Society: 2nd Edition

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D1: Advanced Energy Materials".

Deadline for manuscript submissions: 10 July 2025 | Viewed by 2701

Special Issue Editors

Prof. Dr. Hideaki Ohgaki

E-Mail Website
Guest Editor
Advanced Energy Generation Research Division, Kyoto University, Kyoto 606-8501, Japan
Interests: renewable energy implementation; rural electrification; nuclear technology
Special Issues, Collections and Topics in MDPI journals
Dr. Boonyang Plangklang

E-Mail Website
Guest Editor
Faculty of Electrical Engineering, Rajamangala University of Technology Thanyaburi (RMUTT), Pathumthani 12110, Thailand
Interests: electrical power system; solar and renewable energy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are currently facing a major transitional era, from a fossil-based society to a carbon-neutral society, or, recently, even a negative carbon society. Developments in energy science and technology, and related material science, are indispensable to enable this transition. To boost these developments at the global scale, collaborative research is one of the key approaches. Much collaborative research has been promoted, with plenty of fruitful outcomes thus far. A good example of such collaborative research is the EMSES conference, which originated from collaborative work between Japan and Thailand in the field of “ecologically friendly energy science and technology”, beginning in 2001. This Special Issue aims to present and disseminate the most recent research related to energy science and technology, and related material science, to accelerate the transition to a carbon-neutral and negative-carbon society. Papers through international collaborations are welcomed, but are not limited.

The topics include the following:

  • Material Science and Nano Technology;
  • Energy Technology;
  • Environmental Science;
  • Energy Society and Sustainability;
  • Electric Vehicle Technologies;
  • Carbon Capture and Utilization (CCU);
  • Nuclear Technology;
  • Related Topics in Material and Energy.

The 16th Eco-Energy and Materials Sciences and Engineering Symposium (EMSES 2025, January 8–10, 2025, International Science Innovation Building, Kyoto University, Yoshida Campus, Kyoto, Japan).

Prof. Dr. Hideaki Ohgaki
Dr. Boonyang Plangklang
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. 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 2600 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

  • eco-energy
  • materials science
  • green energy and energy saving
  • renewable energy
  • carbon-neutral society, carbon-negative society, and sustainability
  • interdisciplinary/transdisciplinary

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Related Special Issue

Published Papers (4 papers)

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Research

22 pages, 2842 KiB  
Article
Design of Multi-Objective Energy Management for Remote Communities Connected with an Optimal Hybrid Integrated Photovoltaic–Hydropower–Battery Energy Storage System (PV-HP-BESS) Using Improved Particle Swarm Optimization
by Chaimongkol Pengtem, Saksit Deeum, Amirullah, Hideaki Ohgaki, Sillawat Romphochai, Pimnapat Bhumkittipich and Krischonme Bhumkittipich
Energies 2025, 18(9), 2250; https://doi.org/10.3390/en18092250 - 28 Apr 2025
Viewed by 100
Abstract
The potential for electricity distribution in power systems has significantly increased over the years. This is mainly because of the discovery of alternative electricity generation sources, such as renewable energy, coupled with distributed generation (DG), making electricity more widely accessible. However, challenges remain [...] Read more.
The potential for electricity distribution in power systems has significantly increased over the years. This is mainly because of the discovery of alternative electricity generation sources, such as renewable energy, coupled with distributed generation (DG), making electricity more widely accessible. However, challenges remain in distributing electricity to remote area communities (RACs), especially because of difficult terrain and the complexity of installing power plants, leaving some areas without access to electricity. In this study, we used an improved particle swarm optimization (IPSO) technique to propose multi-objective energy management for remote area communities within a hybrid integrated Photovoltaic–(PV)–Hydropower plant (HPP)–Battery Energy Storage System (BESS). The multi-objective functions enhance power quality and voltage stability to meet grid code requirements. The proposed method was applied to the IEEE 15-bus system, which is consistent with systems commonly used in remote area communities, under the following scenarios: Case I—random installation of PV-HPP-BESS and PI parameter control of BESS; Case II—optimal location of PV-HP-BESS and PI parameter control of BESS using IPSO; Case III—sudden short circuit of the transmission line in Case II. Effectiveness was verified through hardware-in-the-loop (HIL) testing. The experimental results indicate that the proposed method significantly improves power quality and stability under disturbances, demonstrating superior performance. Full article
(This article belongs to the Special Issue Materials and Energy in Negative and Neutral Carbon Society: 2nd Edition)
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15 pages, 2437 KiB  
Article
Route-Based Optimization Methods for Energy Consumption Modeling of Electric Trucks
by Nitikorn Junhuathon, Guntinan Sakulphaisan, Sitthiporn Prukmahachaikul and Keerati Chayakulkheeree
Energies 2025, 18(8), 1986; https://doi.org/10.3390/en18081986 - 12 Apr 2025
Viewed by 282
Abstract
This study presents an advanced method for modeling energy consumption in electric trucks by incorporating regenerative braking probability into conventional modeling equations. Traditional models typically assume uniform regenerative energy recovery, ignoring the variability introduced by differing driving behaviors and braking scenarios. To address [...] Read more.
This study presents an advanced method for modeling energy consumption in electric trucks by incorporating regenerative braking probability into conventional modeling equations. Traditional models typically assume uniform regenerative energy recovery, ignoring the variability introduced by differing driving behaviors and braking scenarios. To address this gap, the proposed method explicitly integrates regenerative probability, capturing the dynamic interactions between driving conditions and regenerative braking events. The research involves systematic data preprocessing techniques, including outlier detection and correction, to ensure high data integrity. Moreover, a genetic algorithm is employed to optimize critical features such as aerodynamic drag coefficient, rolling resistance, and regenerative braking efficiency and probability, aiming to minimize discrepancies between predicted and actual energy consumption. The validation results demonstrate that the enhanced model provides a significantly improved accuracy in predicting energy recovery and state-of-charge estimations, supporting more effective and sustainable energy management practices for electric truck operations. Full article
(This article belongs to the Special Issue Materials and Energy in Negative and Neutral Carbon Society: 2nd Edition)
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17 pages, 4964 KiB  
Article
Optimal of Placement for Battery Energy Storage System Installation Using Fuzzy Expert System in Thailand: A Case Study of Critical Closed-Circuit Television Positions
by Chatchanan Panapiphat, Ekawit Songkoh, Siamrat Phonkaporn, Karun Sirichunchuen and Pramuk Unahalekhaka
Energies 2025, 18(6), 1328; https://doi.org/10.3390/en18061328 - 7 Mar 2025
Viewed by 529
Abstract
This paper presents placement optimization for battery energy storage system installation using a fuzzy expert system. Nowadays, the Bangkok Metropolitan Administration (BMA) has installed CCTV cameras for surveillance, deterrence, and to record events as evidence for legal proceedings. However, in some areas, there [...] Read more.
This paper presents placement optimization for battery energy storage system installation using a fuzzy expert system. Nowadays, the Bangkok Metropolitan Administration (BMA) has installed CCTV cameras for surveillance, deterrence, and to record events as evidence for legal proceedings. However, in some areas, there is no BESS, so when the power goes out, recording cannot continue. This article uses a Fuzzy Logic Expert System to assess critical areas for the consideration of future BESS installation in Bangkok. The key factors include (1) the number of CCTV image requests from the Bangkok Metropolitan Administration, (2) the duration of power outages from the BMA, and (3) the total power consumption of the CCTV in each subdistrict. The study results show that the fuzzy expert system can effectively handle ambiguous data and improve decision-making. The Latkrabang and Lamphlatiew subdistricts have the most critical points where investment in BESS installation is most appropriate. The size of the BESS was determined based on the maximum recorded power outage duration of 57 min, with the backup power design for the BESS set at 1 h. The DIgSILENT program was used to determine the size of the BESS at each critical point, which was calculated to be 160.2 Wh. Full article
(This article belongs to the Special Issue Materials and Energy in Negative and Neutral Carbon Society: 2nd Edition)
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14 pages, 5938 KiB  
Article
Optimization of Sizing of Battery Energy Storage System for Residential Households by Load Forecasting with Artificial Intelligence (AI): Case of EV Charging Installation
by Nopphamat Promasa, Ekawit Songkoh, Siamrat Phonkaphon, Karun Sirichunchuen, Chaliew Ketkaew and Pramuk Unahalekhaka
Energies 2025, 18(5), 1245; https://doi.org/10.3390/en18051245 - 4 Mar 2025
Cited by 1 | Viewed by 793
Abstract
This paper presents the optimization sizing of a battery energy storage system for residential use from load forecasting using AI. The solar rooftop panel installation and charging systems for electric vehicles are connected to the low-voltage electrical system of the Metropolitan Electricity Authority [...] Read more.
This paper presents the optimization sizing of a battery energy storage system for residential use from load forecasting using AI. The solar rooftop panel installation and charging systems for electric vehicles are connected to the low-voltage electrical system of the Metropolitan Electricity Authority (MEA). The daily electricity demand for future load forecasting used the long short-term memory (LSTM) technique in order to analyze the appropriate size of the battery energy storage system (BESS) for residences. The solar rooftop installation capacity is 5.5 kWp, which produces an average of 28.78 kWh/day. The minimum actual daily load in a month is 67.04 kWh, comprising the base load and the load from charging electric vehicles, which can determine the size of the battery energy storage system as 21.03 kWh. For this research, load forecasting will be presented to find the appropriate size of BESS by considering the minimum daily load over the month, which is equal to 102.67 kWh, which can determine the size of the BESS to be 17.84 kWh. When comparing the size of BESS from actual load values with the load from the forecast, it can significantly reduce the size and cost of BESS. Full article
(This article belongs to the Special Issue Materials and Energy in Negative and Neutral Carbon Society: 2nd Edition)
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