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Theories and Applications of Sustainable Energy Systems and Smart Power...
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Theories and Applications of Sustainable Energy Systems and Smart Power Grids

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 4381

Special Issue Editors

Dr. Xinshan Zhu

E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Tianjin University, Tianjin, China
Interests: deep learning; image processing; power electronics applications
Dr. Yuenan Li

E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Tianjin University, Tianjin, China
Interests: signal processing; machine learning; deep neural network
Dr. Leijiao Ge

E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
Interests: RFID; intelligent distribution network situational awareness technology; renewable energy grid integration optimization control technology; artificial intelligence empowering distribution networks/microgrids; and intelligent distribution power big data cloud computing technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The world is facing increasingly serious energy and environmental crises. Sustainable energy systems and smart grids play vital roles in solving the non-renewable problem of traditional fossil energy and protecting the environment, as well as improving the efficiency of resource utilization. Research on the theories and applications of sustainable energy systems and smart power grids has attracted considerable attention. The Special Issue covers both new developments, recent advances, emerging trends, and the state-of-the-art technologies in related fields.

The main topics include 1) fundamentals, modeling, control, optimization, and simulation aspects of sustainable energy systems and smart grids; 2) grid integration of renewables; 3) micro-grids; 4) distribution networks; 5) low-inertia power systems; 6) planning and operation of smart grids; 7) energy storage technologies; 8) technologies and applications of superconductivity; and 9) intelligent operation and maintenance. Since sustainable energy resource and smart grid facilities are quite different in different countries and regions, a wide range of contributions are invited from all over the world.

Dr. Xinshan Zhu
Dr. Yuenan Li
Dr. Leijiao Ge
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

  • smart grid
  • power system
  • renewable
  • solar
  • wind
  • energy storage
  • superconductivity
  • maintenance
  • data driven
  • deep learning

Published Papers (4 papers)

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Research

19 pages, 7323 KiB  
Article
Photovoltaic Power Forecasting Approach Based on Ground-Based Cloud Images in Hazy Weather
by Zhiying Lu, Wenpeng Chen, Qin Yan, Xin Li and Bing Nie
Sustainability 2023, 15(23), 16233; https://doi.org/10.3390/su152316233 - 23 Nov 2023
Viewed by 565
Abstract
Haze constitutes a pivotal meteorological variable with notable implications for photovoltaic power forecasting. The presence of haze is anticipated to lead to a reduction in the output power of photovoltaic plants. Therefore, achieving precise forecasts of photovoltaic power in hazy conditions holds paramount [...] Read more.
Haze constitutes a pivotal meteorological variable with notable implications for photovoltaic power forecasting. The presence of haze is anticipated to lead to a reduction in the output power of photovoltaic plants. Therefore, achieving precise forecasts of photovoltaic power in hazy conditions holds paramount significance. This study introduces a novel approach to forecasting photovoltaic power under haze conditions, leveraging ground-based cloud images. Firstly, the aerosol scattering coefficient is introduced as a pivotal parameter for characterizing photovoltaic power fluctuations influenced by haze. Additionally, other features, such as sky cloud cover, color attributes, light intensity, and texture characteristics, are considered. Subsequently, the Spearman correlation coefficient is applied to calculate the correlation between feature sequences and photovoltaic power. Effective features are then selected as inputs and three models—LSTM, SVM, and XGBoost—are employed for training and performance analysis. After comparing with existing technologies, the predicted results have achieved the best performance. Finally, using actual data, the effectiveness of the aerosol scattering coefficient is confirmed, by exhibiting the highest correlation index, as a pivotal parameter for forecasting photovoltaic output under the influence of haze. The results demonstrate that the aerosol scattering coefficient enhances the forecast accuracy of photovoltaic power in both heavy and light haze conditions by 1.083% and 0.599%, respectively, while exerting minimal influence on clear days. Upon comprehensive evaluation, it is evident that the proposed forecasting method in this study offers substantial advantages for accurately predicting photovoltaic power output in hazy weather scenarios. Full article
(This article belongs to the Special Issue Theories and Applications of Sustainable Energy Systems and Smart Power Grids)
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18 pages, 2323 KiB  
Article
A Current Selective Tripping Protection Scheme for the Distribution Network with PV
by Yabo Liang, Lei Li, Jianan He, Jian Niu, Haitao Liu, Chao Li and Borui Li
Sustainability 2023, 15(17), 13109; https://doi.org/10.3390/su151713109 - 31 Aug 2023
Viewed by 676
Abstract
At present, the global energy demand keeps rising due to population growth. Therefore, large numbers of photovoltaics (PV) are being integrated with power systems. Solar PV’s installed power capacity is poised to surpass that of coal by 2027, becoming the largest in the [...] Read more.
At present, the global energy demand keeps rising due to population growth. Therefore, large numbers of photovoltaics (PV) are being integrated with power systems. Solar PV’s installed power capacity is poised to surpass that of coal by 2027, becoming the largest in the world. The integration of PV has changed the direction of the power flow. Under these circumstances, the changed magnitudes and directions of fault current may result in maloperations and non-operations of conventional relays. In this work, a simple and reliable current selective tripping protection scheme is proposed, which is based on the direct communication between overcurrent protective devices on both sides of the line. Through logical programming of the operation information of each protection, the fault location is detected, and the instantaneous trip is realized. The simulation analysis of PSCAD/EMTDC shows that the protection scheme can reliably detect and isolate faults happening at the feeder and bus under different fault conditions; besides, it has good performance in detecting certain resistance grounding faults. The proposed protection scheme can effectively solve the problems caused by PV systems penetration and improve system safety. Full article
(This article belongs to the Special Issue Theories and Applications of Sustainable Energy Systems and Smart Power Grids)
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16 pages, 2959 KiB  
Article
Multi-Source Information Fusion Technology and Its Application in Smart Distribution Power System
by Xi He, Heng Dong, Wanli Yang and Wei Li
Sustainability 2023, 15(7), 6170; https://doi.org/10.3390/su15076170 - 03 Apr 2023
Cited by 1 | Viewed by 1548
Abstract
Compared to traditional measurement devices, the micro-synchrophasor measurement unit (D-PMU or μPMU) in the distribution power system has great differences in data acquisition frequency, data format, data dimension, time-stamped information, etc. Hence, it is imperative to research the integration mechanism of heterogeneous data [...] Read more.
Compared to traditional measurement devices, the micro-synchrophasor measurement unit (D-PMU or μPMU) in the distribution power system has great differences in data acquisition frequency, data format, data dimension, time-stamped information, etc. Hence, it is imperative to research the integration mechanism of heterogeneous data from multiple sources. Based on the analysis of the current technology of multi-source information fusion, this paper proposes a novel approach, which considers two aspects: the interoperability of multi-source data and the real-time processing of large-scale streaming data. To solve the problem of data interoperability, we have modified the model of D-PMU data and established a unified information model. Meanwhile, an advanced distributed processing technology has been deployed to solve the problem of real-time processing of streaming data. Based on this approach, a smart distribution power system wide-area measurement and control station can be established, and the correctness and practicality of the proposed method are verified by an on-field project. Full article
(This article belongs to the Special Issue Theories and Applications of Sustainable Energy Systems and Smart Power Grids)
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21 pages, 3711 KiB  
Article
Two-Stage Robust Optimal Scheduling of Flexible Distribution Networks Based on Pairwise Convex Hull
by Haiyue Yang, Shenghui Yuan, Zhaoqian Wang and Dong Liang
Sustainability 2023, 15(7), 6093; https://doi.org/10.3390/su15076093 - 31 Mar 2023
Viewed by 876
Abstract
With distributed generation (DG) being continuously connected into distribution networks, the stochastic and fluctuating nature of its power generation brings ever more problems than before, such as increasing operating costs and frequent voltage violations. However, existing robust scheduling methods of flexible resources tend [...] Read more.
With distributed generation (DG) being continuously connected into distribution networks, the stochastic and fluctuating nature of its power generation brings ever more problems than before, such as increasing operating costs and frequent voltage violations. However, existing robust scheduling methods of flexible resources tend to make rather conservative decisions, resulting in high operation costs. In view of this, a two-stage robust optimal scheduling method for flexible distribution networks is proposed in this paper, based on the pairwise convex hull (PWCH) uncertainty set. A two-stage robust scheduling model is first formulated considering coordination among on-load tap changers, energy storage systems and flexible distribution switches. In the first stage, the temporal correlated OLTCs and energy storage systems are globally scheduled using day-ahead forecasted DG outputs. In the second stage, FDSs are scheduled in real time in each time period based on the first-stage decisions and accurate short-term forecasted DG outputs. The spatial correlation and uncertainties of the outputs of multiple DGs are modeled based on the PWCH, such that the decision conservativeness can be reduced by cutting regions in the box with low probability of occurrence. The improved column-and-constraint generation algorithm is then used to solve the robust optimization model. Through alternating iterations of auxiliary variables and dual variables, the nonconvex bilinear terms induced by the PWCH are eliminated, and the subproblem is significantly accelerated. Test results on the 33-bus distribution system and a realistic 104-bus distribution system validate that the proposed PWCH-based method can obtain much less conservative scheduling schemes than using the box uncertainty set. Full article
(This article belongs to the Special Issue Theories and Applications of Sustainable Energy Systems and Smart Power Grids)
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