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Application of Power System in Sustainable Energy Perspective
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Application of Power System in Sustainable Energy Perspective

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (2 April 2024) | Viewed by 3816

Special Issue Editors

Prof. Dr. Ling Xiang

E-Mail Website
Guest Editor
Department of Mechanical Engineering, North China Electric Power University, Baoding 071003, China
Interests: dynamics modelling; signal processing; intelligent fault diagnosis; condition monitoring; life prediction
Dr. Xiaoan Yan

E-Mail Website
Guest Editor
School of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing, China
Interests: mechanical equipment condition monitoring and fault diagnosis; damage mechanism of engineering structure, damage recognition/location; adaptive filtering, noise reduction, time-frequency analysis technology; health condition evaluation and life prediction of rolling bearing

Special Issue Information

Dear Colleagues,

The extensive and long-term use of non-renewable energy resources, such as coal, oil, and natural gas, not only leads to the gradual depletion of global energy, but also continuously pollutes the environment; therefore, renewable energy sources are receiving increasing attention. In recent years, as the main force of renewable energy, wind power has become increasingly important in the field of power generation. With the steady growth of the amount of energy generated by wind power, the failure of wind turbines has gradually become a  challenge for their development. Nowadays, not only university researchers in related fields but also large wind power system enterprises, including Goldwind, Mingyang, Envision Energy, Yunda, Siemens, and General Electric, are also committed to the research and development of condition monitoring and fault diagnosis technology of wind turbines. Researching effective methods for monitoring and diagnosing wind turbine conditions, in order to comprehensively improve the operational safety and stability of wind turbines and improve the quality and efficiency of wind power generation, is an important trend in line with the current development of renewable energy systems.

This Special Issue aims to gather and propagate the most recent research results and breakthroughs in condition monitoring and fault diagnosis of wind power systems, including the application of numerous theories and technologies, such as dynamics modeling, sensor layout, data acquisition, parameter measurement, signal analysis, feature extraction, fault diagnosis, anomaly detection, structural damage identification, early warning, health condition assessment, residual life prediction, and other related software, and even hardware technology.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  1. Dynamic modeling and simulation techniques;
  2. Sensor optimization layout strategy;
  3. Sensor network-based data acquisition and processing technology;
  4. Advanced signal processing and filtering technology;
  5. Multi-sensor information fusion technology;
  6. 4G/5G/ Internet of Things communication technology;
  7. Big data and artificial intelligence-driven fault diagnosis;
  8. Intelligent fault diagnosis of digital-analog linkage;
  9. Physics/statistics/machine learning model-based life prediction techniques;
  10. Prediction and health management (PHM) technology;
  11. Structural health monitoring (SHM) and damage recognition theory;
  12. Data-driven intelligent security management and control;
  13. Intelligent operation, maintenance, and monitoring system;
  14. System reliability analysis and evaluation.

We look forward to receiving your contributions.

Prof. Dr. Ling Xiang
Dr. Xiaoan Yan
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. Sustainability 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

  • system dynamics
  • sensor technology
  • signal processing
  • fault diagnosis
  • artificial intelligence
  • machine learning
  • prediction and health management (PHM)
  • structural health monitoring (SHM)
  • intelligent operation and management
  • system reliability

Published Papers (4 papers)

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Research

20 pages, 4584 KiB  
Article
Optimal Capacity Planning of Green Electricity-Based Industrial Electricity-Hydrogen Multi-Energy System Considering Variable Unit Cost Sequence
by Qinqin Xia, Yao Zou and Qianggang Wang
Sustainability 2024, 16(9), 3684; https://doi.org/10.3390/su16093684 - 28 Apr 2024
Viewed by 388
Abstract
Utilizing renewable energy sources (RESs), such as wind and solar, to convert electrical energy into hydrogen energy can promote the accommodation of green electricity. This paper proposes an optimal capacity planning approach for an industrial electricity-hydrogen multi-energy system (EHMES) aimed to achieve the [...] Read more.
Utilizing renewable energy sources (RESs), such as wind and solar, to convert electrical energy into hydrogen energy can promote the accommodation of green electricity. This paper proposes an optimal capacity planning approach for an industrial electricity-hydrogen multi-energy system (EHMES) aimed to achieve the local utilization of RES and facilitate the transition to carbon reduction in industrial settings. The proposed approach models the EHMES equipment in detail and divides the system’s investment and operation into producer and consumer sides with energy trading for effective integration. Through this effort, the specialized management for different operators and seamless incorporation of RES into industrial users can be achieved. In addition, the variations in investment and operating costs of equipment across different installed capacities are considered to ensure a practical alignment with real-world scenarios. By conducting a detailed case study, the influence of various factors on the capacity configuration outcomes within an EHMES is analyzed. The results demonstrate that the proposed method can effectively address the capacity configuration of equipment within EHMES based on the local accommodation of RES and variable unit cost sequence. Wind power serves as the primary source of green electricity in the system. Energy storage acts as crucial equipment for enhancing the utilization rate of RES. Full article
(This article belongs to the Special Issue Application of Power System in Sustainable Energy Perspective)
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13 pages, 2115 KiB  
Article
Anomaly Perception Method of Substation Scene Based on High-Resolution Network and Difficult Sample Mining
by Yunhai Song, Sen He, Liwei Wang, Zhenzhen Zhou, Yuhao He, Yaohui Xiao, Yi Zheng and Yunfeng Yan
Sustainability 2023, 15(18), 13721; https://doi.org/10.3390/su151813721 - 14 Sep 2023
Cited by 1 | Viewed by 688
Abstract
The perception of anomalies in power scenarios plays a crucial role in the safe operation and fault prediction of power systems. However, traditional anomaly detection methods face challenges in identifying difficult samples due to the complexity and uneven distribution of power scenarios. This [...] Read more.
The perception of anomalies in power scenarios plays a crucial role in the safe operation and fault prediction of power systems. However, traditional anomaly detection methods face challenges in identifying difficult samples due to the complexity and uneven distribution of power scenarios. This paper proposes a power scene anomaly perception method based on high-resolution networks and difficult sample mining. Firstly, a high-resolution network is introduced as the backbone for feature extraction, enhancing the ability to express fine details in power scenarios and capturing information on small target anomaly regions. Secondly, a strategy for mining difficult samples is employed to focus on learning and handling challenging and hard-to-recognize anomaly samples, thereby improving the overall anomaly detection performance. Lastly, the method incorporates GIOU loss and a flexible non-maximum suppression strategy to better adapt to the varying sizes and dense characteristics of power anomaly targets. This improvement enables higher adaptability in detecting anomalies in power scenarios. Experimental results demonstrate significant improvements in power scene anomaly perception and superior performance in handling challenging samples. This study holds practical value for fault diagnosis and safe operation in power systems. Full article
(This article belongs to the Special Issue Application of Power System in Sustainable Energy Perspective)
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17 pages, 7590 KiB  
Article
An Investigation of Real-Time Active Noise Control for 10 kV Substation Noise Suppression
by Jinshan Yu, Zhongyuan Zheng, Yamin Li, Haohui Wang, Ying Hao, Xiaoxia Liang and Jianzheng Gao
Sustainability 2023, 15(18), 13430; https://doi.org/10.3390/su151813430 - 7 Sep 2023
Viewed by 1062
Abstract
Substation noise is a crucial factor that influences residents’ quality of life, especially in the densely residential areas. Despite small- and medium-sized transformer facilities having relatively low noise levels, due to their proximity to residential areas, they generate considerable annoyance, rendering them a [...] Read more.
Substation noise is a crucial factor that influences residents’ quality of life, especially in the densely residential areas. Despite small- and medium-sized transformer facilities having relatively low noise levels, due to their proximity to residential areas, they generate considerable annoyance, rendering them a focal point among environmental noise complaints. The predominant noise emitted by these facilities falls within the medium- and low-frequency spectrum range, and the conventional passive noise reduction techniques exhibit limited efficacy in attenuating such low-frequency noise. This study develops a real-time active noise control (ANC) system based on a digital signal processor, TMS320F28335, and various ANC methods, including Filtered-X Least Mean Squares (FxLMS), Normalized Filter-X Least Mean Squares (FxNLMS), and variable step-size FxLMS (VS-FxLMS), are evaluated for the low-frequency noise reduction. In addition, the substation noises at a residential community are measured, analyzed, and used as noise source together with a series of sinusoidal waves for evaluation of the ANC algorithms. Results show the ANC system are effective in attenuating most low-frequency noises (within 600 Hz) and the average noise reduction for the substation noises has achieved by more than 12 dB. Full article
(This article belongs to the Special Issue Application of Power System in Sustainable Energy Perspective)
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16 pages, 3987 KiB  
Article
Simulation of Secondary Frequency Modulation Process of Wind Power with Auxiliary of Flywheel Energy Storage
by Run Qin, Juntao Chen, Zhong Li, Wei Teng and Yibing Liu
Sustainability 2023, 15(15), 11832; https://doi.org/10.3390/su151511832 - 1 Aug 2023
Viewed by 928
Abstract
With the rapid increase in the proportion of wind power, the frequency stability problem of power system is becoming increasingly serious. Based on MATLAB/Simulink simulation, the role and effect of secondary frequency modulation assisted by Flywheel Energy Storage System (FESS) in regional power [...] Read more.
With the rapid increase in the proportion of wind power, the frequency stability problem of power system is becoming increasingly serious. Based on MATLAB/Simulink simulation, the role and effect of secondary frequency modulation assisted by Flywheel Energy Storage System (FESS) in regional power grid with certain wind power penetration rates are studied. First, the linear frequency control of the power system is used to establish the primary frequency modulation control model of FESS assisting wind power, and the frequency characteristics of FESS participating in primary frequency modulation are analyzed according to the transfer function. Then, in the case of step disturbance and continuous disturbance of load power, the frequency characteristics of a regional power grid are simulated and demonstrated through time domain simulation, and conclusions are drawn through comparison; a certain proportion of FESS can quickly respond to the frequency deviation signal. During secondary frequency modulation simulation, the maximum frequency deviation of the system is reduced by 57.1% and the frequency fluctuation range is reduced by 53.8%, effectively improving the frequency quality of the power grid. Full article
(This article belongs to the Special Issue Application of Power System in Sustainable Energy Perspective)
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