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Clean and Efficient Use of Energy: 2nd Edition
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Clean and Efficient Use of Energy: 2nd Edition

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "B2: Clean Energy".

Deadline for manuscript submissions: 25 April 2025 | Viewed by 2650

Special Issue Editors

Dr. Gangli Zhu

E-Mail Website
Guest Editor
Lanzhou Institute of Chemical Physics (LICP), Chinese Academy of Sciences, Lanzhou 730000, China
Interests: clean fuel; CO2 conversion; catalyst characterization; biodiesel; hydrogen storage; polyoxymethylene diethyl ethers; ethanol; methanol
Special Issues, Collections and Topics in MDPI journals
Dr. Kegong Fang

E-Mail Website
Guest Editor
State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China
Interests: chemistry and engineering; nanomaterials synthesis; heterogeneous catalysis; syngas conversion to oxygenates; alcohol coupling and alkane dehydrogenation
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Shenghua Liu

E-Mail Website
Guest Editor
School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Interests: clean alternative fuels for internal combustion engines; emissions and controls of internal combustion engines; internal combustion engines; combustion of internal combustion engines and control of harmful emissions; clean alternative fuels for petroleum; methanol vehicle testing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to share the success of our Special Issues “Clean and Efficient Use of Energy”. More detail information could be found at the following link: https://www.mdpi.com/journal/energies/special_issues/1AJ0H482FX.

We now seek to launch the second volume of this Special Issue “Clean and Efficient Use of Energy: 2nd Edition".

At present, energy is being consistently consumed in an intensive manner for socio-economic activities. Humans must reduce their environmental impact and combat the climate change impacts of energy consumption. For example, carbon dioxide (CO2) has attracted global attention recently because of its negative impact on global warming and climate change. Sustainable energy and clean and efficient energy utilization are essential to meet the sustainability goals of the future. This will require the development and implementation of energy resources, including traditional oil, coal, natural gas, and hydroelectric power as well as promising renewable sources (solar, biomass, wind, geothermal, etc.). The emissions and waste from energy utilization processes need to be eliminated or reused. Additionally, the various pathways need to be extensively analyzed.

This Special Issue is dedicated to the clean and efficient use of energy. Therefore, we invite original papers addressing the various topics related to the cleanliness, efficiency and sustainability of energy. In this Special Issue, the types of paper may include reviews, original research articles, highlights, perspectives, short communications, commentaries, and so on.

The topics of interest include but are not limited to the following:

  1. Biomass energy conversion and utilization;
  2. Conversion and utilization of CO2;
  3. Elimination of pollutants in the use of energy;
  4. Electrocatalysis in energy applications;
  5. Clean alternative fuels;
  6. Emissions and controls in the use of energy;
  7. Clean and efficient utilization of coal;
  8. Clean utilization of methanol, ethanol and derived fuels;
  9. Hydrogen storage and release;
  10. Evaluating and implementing alternative energy approaches.

Dr. Gangli Zhu
Dr. Kegong Fang
Prof. Dr. Shenghua Liu
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

  • biomass
  • alternative fuels
  • CO2 utilization
  • elimination of pollutants
  • energy storage and release
  • electrocatalysis

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Related Special Issue

Published Papers (4 papers)

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Research

18 pages, 3455 KiB  
Article
The Wideband Oscillatory Localization Method Based on Combining Compressed Sensing and Graph Attention Networks
by Jinggeng Gao, Yong Yang, Honglei Xu, Yingzhou Xie, Chen Zhou and Haiying Dong
Energies 2024, 17(23), 6062; https://doi.org/10.3390/en17236062 - 2 Dec 2024
Viewed by 403
Abstract
Due to the increasing integration of new energy sources, the power system now exhibits low inertia, in which the broadband oscillation problem is increasingly significant in the face of the strong coupling of complex and variable power systems, and the current lack of [...] Read more.
Due to the increasing integration of new energy sources, the power system now exhibits low inertia, in which the broadband oscillation problem is increasingly significant in the face of the strong coupling of complex and variable power systems, and the current lack of uniform and effective mathematical models and analysis methods. To solve this major problem, a broadband oscillation localization method based on the combination of compressed perception and graph attention network (GAT) is proposed. The method firstly uses the principle of compression perception to compress and transmit the oscillation time series data of the sub-station, reconstructs the compressed signal at the master station and aggregates the grid topology and node characteristic information to effectively reduce the redundancy of the oscillation data; reconstruction error is only 0.031, takes into account the balance of the samples and the effectiveness of the computation, and adopts the multi-attention mechanism and the cross-entropy loss function to improve the performance of the model training. Finally, the offline training and online evaluation model based on the GAT algorithm is constructed, and the accuracy of the model is up to 98.5%; and the results show that the method has a high positioning accuracy and a certain anti-noise ability at the same time. Full article
(This article belongs to the Special Issue Clean and Efficient Use of Energy: 2nd Edition)
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14 pages, 2364 KiB  
Article
A Multi-Mode Recognition Method for Broadband Oscillation Based on CS-OMP and Adaptive VMD
by Jinggeng Gao, Honglei Xu, Yong Yang, Xujun Zhang, Xiangde Mao and Haiying Dong
Energies 2024, 17(23), 5821; https://doi.org/10.3390/en17235821 - 21 Nov 2024
Viewed by 420
Abstract
Due to the application of power electronics and wind power generation equipment in power systems, broadband oscillation events constantly appear, which makes broadband oscillation difficult to detect due to the limitations of communication bandwidth and the sampling theorem. To ensure the safety and [...] Read more.
Due to the application of power electronics and wind power generation equipment in power systems, broadband oscillation events constantly appear, which makes broadband oscillation difficult to detect due to the limitations of communication bandwidth and the sampling theorem. To ensure the safety and stability of the system, and to detect and recognize the broadband oscillation information timely and accurately, this paper presents a multi-mode recognition method of broadband oscillation based on compressed sensing (CS) and the adaptive Variational Mode Decomposition (VMD) algorithm. Firstly, the high-dimensional oscillation signal data collected by the Phasor Measurement Unit (PMU) is compressed and sampled by a Gaussian random matrix, and the obtained low-dimensional data are uploaded to the main station. Secondly, the orthogonal matching pursuit (OMP) algorithm of the master station is used to reconstruct the low-dimension signal, and the original high-dimension signal data are recovered without losing the main features of the signal. Finally, an adaptive VMD algorithm with energy loss minimization as a threshold is used to decompose the reconstructed signal, and the Intrinsic Mode Function (IMF) components with broadband oscillation information are obtained. By constructing oscillating signals with different frequencies, Gaussian white noise with a signal-to-noise ratio of 10 dB to 30 dB is added successively. After the signal is compressed and reconstructed by the proposed method, the signal-to-noise ratio can reach 18.8221 dB to 40.0794 dB, etc., and the oscillation frequency and amplitude under each signal-to-noise ratio can be accurately identified. The results show that the proposed method not only has good robustness to noise, but also has good denoising effect to noise. By using the simulation measurement model, the original oscillation signal is compressed and reconstructed, and the reconstruction error is 0.1263. The basic characteristics of the signal are restored, and the frequency and amplitude of the oscillation mode are accurately identified, which proves that the method is feasible and accurate. Full article
(This article belongs to the Special Issue Clean and Efficient Use of Energy: 2nd Edition)
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17 pages, 3228 KiB  
Article
A Method for Fault Localization in Distribution Networks with High Proportions of Distributed Generation Based on Graph Convolutional Networks
by Xiping Ma, Wenxi Zhen, Haodong Ren, Guangru Zhang, Kai Zhang and Haiying Dong
Energies 2024, 17(22), 5758; https://doi.org/10.3390/en17225758 - 18 Nov 2024
Viewed by 571
Abstract
To address the issues arising from the integration of a high proportion of distributed generation (DG) into the distribution network, which has led to the transition from traditional single-source to multi-source distribution systems, resulting in increased complexity of the distribution network topology and [...] Read more.
To address the issues arising from the integration of a high proportion of distributed generation (DG) into the distribution network, which has led to the transition from traditional single-source to multi-source distribution systems, resulting in increased complexity of the distribution network topology and difficulties in fault localization, this paper proposes a fault localization method based on graph convolutional networks (GCNs) for distribution networks with a high proportion of distributed generation. By abstracting busbars and lines into graph structure nodes and edges, GCN captures spatial coupling relationships between nodes, using key electrical quantities such as node voltage magnitude, current magnitude, power, and phase angle as input features to construct a fault localization model. A multi-type fault dataset is generated using the Matpower toolbox, and model training is evaluated using K-fold cross-validation. The training process is optimized through early stopping mechanisms and learning rate scheduling. Simulations are conducted based on the IEEE 33-node distribution network benchmark, with photovoltaic generation, wind generation, and energy storage systems connected at specific nodes, validating the model’s fault localization capability under various fault types (single-phase ground fault, phase-to-phase short circuit, and line open circuit). Experimental results demonstrate that the proposed model can effectively locate fault nodes in complex distribution networks with high DG integration, achieving an accuracy of 98.5% and an AUC value of 0.9997. It still shows strong robustness in noisy environments and is significantly higher than convolutional neural networks and other methods in terms of model localization accuracy, training time, F1 score, AUC value, and single fault detection inference time, which has good potential for practical application. Full article
(This article belongs to the Special Issue Clean and Efficient Use of Energy: 2nd Edition)
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24 pages, 9184 KiB  
Article
Biomass-Driven Polygeneration Coupled to Power-to-X: An Energy and Economic Comparison Between On-Site Electric Vehicle Charging and Hydrogen Production
by Simona Di Fraia, Rafał Figaj, Musannif Shah and Laura Vanoli
Energies 2024, 17(21), 5479; https://doi.org/10.3390/en17215479 - 1 Nov 2024
Viewed by 870
Abstract
The power-to-X strategy for passenger car applications offers a viable solution for using the surplus electrical power from renewable energy sources instead of exporting it to the grid. The innovative system proposed in this study allocates surplus electrical power from a building-integrated biomass-based [...] Read more.
The power-to-X strategy for passenger car applications offers a viable solution for using the surplus electrical power from renewable energy sources instead of exporting it to the grid. The innovative system proposed in this study allocates surplus electrical power from a building-integrated biomass-based Combined Cooling Heating and Power (CCHP) system to on-site applications and evaluates the energetic and economic benefits. The system comprises two key components: a 50 kW electric vehicle (EV) charging station for EVs and a 50 kW alkaline electrolyzer system for on-site hydrogen production, which is later dispensed to fuel cell electric vehicles (FCEVs). The primary goal is to decrease the surplus of electricity exports while simultaneously encouraging sustainable transportation. The system’s economic viability is assessed through two scenarios of fuel (e.g., biomass) supply costs (e.g., with and without fuel market costs) and compared to the conventional approach of exporting the excess power. The key findings of this work include a substantial reduction in surplus electricity exports, with only 3.7% allocated for EV charging and 31.5% for hydrogen production. The simple payback period (SPB) is notably reduced, enhancing economic viability. Sensitivity analysis identifies the optimal hydrogen system, featuring a 120 kW electrolyzer and a 37 kg daily hydrogen demand. The results underscore the importance of prioritizing self-consumed energy over exports to the national grid, thereby supporting integrated renewable energy solutions that enhance local energy utilization and promote sustainable transportation initiatives. Full article
(This article belongs to the Special Issue Clean and Efficient Use of Energy: 2nd Edition)
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