Virtual synchronous generator (VSG) control addresses the issue of decreasing microgrid standby inertia caused by the rise in wind turbines and photovoltaic (PV) penetration. However, various types of perturbations occur frequently making the traditional constant parameter VSG control unable to meet the system performance requirements, and thus a two-parameters fuzzy VSG control is proposed to ensure that microgrid inertia and damping. Firstly, the device-level control of each generation unit in the microgrid is designed based on the wind-PV-battery alternating current (AC) microgrid architecture. Secondly, fuzzy VSG control uses fuzzy rules written in plain language to represent the relationship between the main VSG factors and the power and frequency. Then, the influence of virtual inertia and damping coefficient on the dynamic performance of the system is analyzed through the theory of small-signal model, and a reasonable variation range of VSG parameters are given. Finally, the simulation model of wind-PV-battery AC microgrid is built in MATLAB/Simulink, and compared with other improved VSG control strategies, the fuzzy VSG control proposed in this paper has better dynamic performance and safety stability. This research emphasizes the practicality and importance of utilizing fuzzy control to adjust VSG techniques for developing microgrid configurations incorporating more renewable energy sources to guarantee the reliability and efficiency of microgrid.
{"title":"Power stability control of wind-PV-battery AC microgrid based on two-parameters fuzzy VSG","authors":"Wenwei Zhou, Binjie Wang, Jipeng Gu, Youbing Zhang, Shuyi Wang, Yixuan Wu","doi":"10.3389/fenrg.2023.1298033","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1298033","url":null,"abstract":"Virtual synchronous generator (VSG) control addresses the issue of decreasing microgrid standby inertia caused by the rise in wind turbines and photovoltaic (PV) penetration. However, various types of perturbations occur frequently making the traditional constant parameter VSG control unable to meet the system performance requirements, and thus a two-parameters fuzzy VSG control is proposed to ensure that microgrid inertia and damping. Firstly, the device-level control of each generation unit in the microgrid is designed based on the wind-PV-battery alternating current (AC) microgrid architecture. Secondly, fuzzy VSG control uses fuzzy rules written in plain language to represent the relationship between the main VSG factors and the power and frequency. Then, the influence of virtual inertia and damping coefficient on the dynamic performance of the system is analyzed through the theory of small-signal model, and a reasonable variation range of VSG parameters are given. Finally, the simulation model of wind-PV-battery AC microgrid is built in MATLAB/Simulink, and compared with other improved VSG control strategies, the fuzzy VSG control proposed in this paper has better dynamic performance and safety stability. This research emphasizes the practicality and importance of utilizing fuzzy control to adjust VSG techniques for developing microgrid configurations incorporating more renewable energy sources to guarantee the reliability and efficiency of microgrid.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139263024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-16DOI: 10.3389/fenrg.2023.1283079
Zhongtang Xuan, Zhiheng Cheng, Chunyuan Li, Chaojun Fan, Hongyan Qin, Wenchen Li, Kai Guo, Haoyi Chen, Yifei Xie, Likai Yang
Influenced by the deep high-stress environment, geological structures, and mining disturbance in coal mines, the frequency of rockburst disasters in roadways is increasing. This research analyzed energy evolution characteristics during rockburst development in the elastic bearing zone and energy conversion in the plastic failure zone. The critical energy criteria for structural instability of roadway surrounding rocks were deduced. Numerical software was also applied to simulate the energy evolution during rockburst development in surrounding rocks of rockburst-prone roadways under conditions of different mining depths and coal pillar widths. The occurrence mechanism of rockburst deep in coal mines was analyzed from the perspective of energy in structures of deep roadway surrounding rock in coal mines. The research results show that the critical energy criteria are closely related to the elastic strain energy stored in deep roadway surrounding rocks and the energy absorbed by support systems. The impact energy in roadways is directly proportional to the square of the stress concentration factor k. Moreover, as the mining depth increases, the location of the peak point of maximum energy density gradually shifts to coal ahead of the working face. The larger the mining depth is, the more significantly the energy density is influenced by advanced abutment pressure of the working face and the wider the affected area is. With the increment of the coal pillar width, the distance from the peak point of energy density to the roadway boundary enlarges abruptly at first and then slowly, and the critical coal pillar width for gentle change in the distance is 30 m. Changes in the peak elastic energy density in coal pillars with the coal pillar width can be divided into four stages: the slow increase stage, abrupt increase stage, abrupt decrease stage, and slow decrease stage. The elastic energy density is distributed asymmetrically in deep roadway surrounding rocks in coal mines. Under the action of structures of roadway surrounding rocks, energy evolution in these structures differs greatly during rockburst development under conditions of different coal pillar widths. This research provides an important theoretical basis for the support of rockburst-prone roadways during deep coal mining.
{"title":"Energy evolution mechanism during rockburst development in structures of surrounding rocks of deep rockburst-prone roadways in coal mines","authors":"Zhongtang Xuan, Zhiheng Cheng, Chunyuan Li, Chaojun Fan, Hongyan Qin, Wenchen Li, Kai Guo, Haoyi Chen, Yifei Xie, Likai Yang","doi":"10.3389/fenrg.2023.1283079","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1283079","url":null,"abstract":"Influenced by the deep high-stress environment, geological structures, and mining disturbance in coal mines, the frequency of rockburst disasters in roadways is increasing. This research analyzed energy evolution characteristics during rockburst development in the elastic bearing zone and energy conversion in the plastic failure zone. The critical energy criteria for structural instability of roadway surrounding rocks were deduced. Numerical software was also applied to simulate the energy evolution during rockburst development in surrounding rocks of rockburst-prone roadways under conditions of different mining depths and coal pillar widths. The occurrence mechanism of rockburst deep in coal mines was analyzed from the perspective of energy in structures of deep roadway surrounding rock in coal mines. The research results show that the critical energy criteria are closely related to the elastic strain energy stored in deep roadway surrounding rocks and the energy absorbed by support systems. The impact energy in roadways is directly proportional to the square of the stress concentration factor k. Moreover, as the mining depth increases, the location of the peak point of maximum energy density gradually shifts to coal ahead of the working face. The larger the mining depth is, the more significantly the energy density is influenced by advanced abutment pressure of the working face and the wider the affected area is. With the increment of the coal pillar width, the distance from the peak point of energy density to the roadway boundary enlarges abruptly at first and then slowly, and the critical coal pillar width for gentle change in the distance is 30 m. Changes in the peak elastic energy density in coal pillars with the coal pillar width can be divided into four stages: the slow increase stage, abrupt increase stage, abrupt decrease stage, and slow decrease stage. The elastic energy density is distributed asymmetrically in deep roadway surrounding rocks in coal mines. Under the action of structures of roadway surrounding rocks, energy evolution in these structures differs greatly during rockburst development under conditions of different coal pillar widths. This research provides an important theoretical basis for the support of rockburst-prone roadways during deep coal mining.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139268546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-16DOI: 10.3389/fenrg.2023.1287743
H. B. Bacha, A. S. Abdullah, Umar Alqasir, Reda S. Salama, M. Abdelgaied, A. Kabeel
Middle East and North Africa (MENA) countries are experiencing rapid population growth, so water and electricity consumption plays a crucial role in the sustainable development of these countries. To overcome the water scarcity and electricity problems facing the MENA region, the developed cooling/preheating small PVT-RO desalination plants have been proposed as a practical solution. To achieve sustainable water and energy development in the MENA region, this study presents a commendable and highly efficient renewable energy project for freshwater production and electricity generation to solve the energy crisis and water scarcity in the MENA countries. Therefore, this study aims to develop a cooling/preheating small PVT-RO desalination plant to facilitate freshwater supply to remote regions and produce electricity. This was done by connecting photovoltaic/thermal (PVT) collectors with reverse osmosis (RO) desalination systems, where seawater is used as a medium to cool photovoltaic cells to increase electric power generation and at the same time recover thermal energy and use it in the initial heating of feed seawater before it is fed into the RO plants, thus increasing its productivity. The results indicate that using the photovoltaic thermal panels as preheating units will lead to a 0.135 kWh/m3 reduction in the rate of specific electricity consumption for the RO desalination plant, as well as increase the electricity generation from PVT panels by a rate of 8%. The economic feasibility presented that the proposed developed cooling/preheating small PVT-RO desalination plant represents an effective technology that reduced the freshwater cost by a rate of 49.5%.
{"title":"Performance analysis and techno-economic assessment of a developed cooling/preheating small PVT-RO desalination plant","authors":"H. B. Bacha, A. S. Abdullah, Umar Alqasir, Reda S. Salama, M. Abdelgaied, A. Kabeel","doi":"10.3389/fenrg.2023.1287743","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1287743","url":null,"abstract":"Middle East and North Africa (MENA) countries are experiencing rapid population growth, so water and electricity consumption plays a crucial role in the sustainable development of these countries. To overcome the water scarcity and electricity problems facing the MENA region, the developed cooling/preheating small PVT-RO desalination plants have been proposed as a practical solution. To achieve sustainable water and energy development in the MENA region, this study presents a commendable and highly efficient renewable energy project for freshwater production and electricity generation to solve the energy crisis and water scarcity in the MENA countries. Therefore, this study aims to develop a cooling/preheating small PVT-RO desalination plant to facilitate freshwater supply to remote regions and produce electricity. This was done by connecting photovoltaic/thermal (PVT) collectors with reverse osmosis (RO) desalination systems, where seawater is used as a medium to cool photovoltaic cells to increase electric power generation and at the same time recover thermal energy and use it in the initial heating of feed seawater before it is fed into the RO plants, thus increasing its productivity. The results indicate that using the photovoltaic thermal panels as preheating units will lead to a 0.135 kWh/m3 reduction in the rate of specific electricity consumption for the RO desalination plant, as well as increase the electricity generation from PVT panels by a rate of 8%. The economic feasibility presented that the proposed developed cooling/preheating small PVT-RO desalination plant represents an effective technology that reduced the freshwater cost by a rate of 49.5%.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139267981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-16DOI: 10.3389/fenrg.2023.1261268
Qihe Lou, Yanbin Li
Distributed energy resources (DER) is a prevalent technology in distribution grids. However, it poses challenges for distribution network operators to make optimal decisions, estimate total investment returns, and forecast future grid operation performance to achieve investment development objectives. Conventional methods mostly rely on current data to conduct a static analysis of distribution network investment, and fail to account for the impact of dynamic variations in relevant factors on a long-term scale on distribution network operation and investment revenue. Therefore, this paper proposes a techno-economic approach to distribution networks considering distributed generation. First, the analysis method of the relationship between each investment subject and distribution network benefit is established by using the system dynamics model, and the indicator system for distribution network investment benefit analysis is constructed. Next, the distribution network operation technology model based on the dist flow approach is employed. This model takes into account various network constraints and facilitates the comprehensive analysis of distribution network operation under dynamic changes in multiple factors. Consequently, the technical index parameters are updated to reflect these changes. This updated information is then integrated into the system dynamics model to establish an interactive simulation of the techno-economic model. Through rigorous verification using practical examples, the proposed method is able to obtain the multiple benefits of different investment strategies and be able to select the better solution. This can provide reference value for future power grid planning.
{"title":"Techno-economic model for long-term revenue prediction in distribution grids incorporating distributed energy resources","authors":"Qihe Lou, Yanbin Li","doi":"10.3389/fenrg.2023.1261268","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1261268","url":null,"abstract":"Distributed energy resources (DER) is a prevalent technology in distribution grids. However, it poses challenges for distribution network operators to make optimal decisions, estimate total investment returns, and forecast future grid operation performance to achieve investment development objectives. Conventional methods mostly rely on current data to conduct a static analysis of distribution network investment, and fail to account for the impact of dynamic variations in relevant factors on a long-term scale on distribution network operation and investment revenue. Therefore, this paper proposes a techno-economic approach to distribution networks considering distributed generation. First, the analysis method of the relationship between each investment subject and distribution network benefit is established by using the system dynamics model, and the indicator system for distribution network investment benefit analysis is constructed. Next, the distribution network operation technology model based on the dist flow approach is employed. This model takes into account various network constraints and facilitates the comprehensive analysis of distribution network operation under dynamic changes in multiple factors. Consequently, the technical index parameters are updated to reflect these changes. This updated information is then integrated into the system dynamics model to establish an interactive simulation of the techno-economic model. Through rigorous verification using practical examples, the proposed method is able to obtain the multiple benefits of different investment strategies and be able to select the better solution. This can provide reference value for future power grid planning.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139267067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-16DOI: 10.3389/fenrg.2023.1301828
Yan Jiang, Kaixiang Fu, Weizhi Huang, Jie Zhang, Xiangyong Li, Shuangquan Liu
As a clean energy source, solar power plays an important role in reducing the high carbon emissions of China’s electricity system. However, the intermittent nature of the system limits the effective use of photovoltaic power generation. This paper addresses the problem of low accuracy of ultra-short-term prediction of distributed PV power, compares various deep learning models, and innovatively selects the Informer model with multi-head probability sparse self-attention mechanism for prediction. The results show that the CEEMDAN-Informer model proposed in this paper has better prediction accuracy, and the error index is improved by 30.88% on average compared with the single Informer model; the Informer model is superior to other deep learning models LSTM and RNN models in medium series prediction, and its prediction accuracy is significantly better than the two. The power prediction model proposed in this study improves the accuracy of PV ultra-short-term power prediction and proves the feasibility and superiority of the deep learning model in PV power prediction. Meanwhile, the results of this study can provide some reference for the power prediction of other renewable energy sources, such as wind power.
{"title":"Ultra-short-term PV power prediction based on Informer with multi-head probability sparse self-attentiveness mechanism","authors":"Yan Jiang, Kaixiang Fu, Weizhi Huang, Jie Zhang, Xiangyong Li, Shuangquan Liu","doi":"10.3389/fenrg.2023.1301828","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1301828","url":null,"abstract":"As a clean energy source, solar power plays an important role in reducing the high carbon emissions of China’s electricity system. However, the intermittent nature of the system limits the effective use of photovoltaic power generation. This paper addresses the problem of low accuracy of ultra-short-term prediction of distributed PV power, compares various deep learning models, and innovatively selects the Informer model with multi-head probability sparse self-attention mechanism for prediction. The results show that the CEEMDAN-Informer model proposed in this paper has better prediction accuracy, and the error index is improved by 30.88% on average compared with the single Informer model; the Informer model is superior to other deep learning models LSTM and RNN models in medium series prediction, and its prediction accuracy is significantly better than the two. The power prediction model proposed in this study improves the accuracy of PV ultra-short-term power prediction and proves the feasibility and superiority of the deep learning model in PV power prediction. Meanwhile, the results of this study can provide some reference for the power prediction of other renewable energy sources, such as wind power.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139270123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-16DOI: 10.3389/fenrg.2023.1285190
V. Kiray
{"title":"An opinion on minimizing the need for agricultural and public areas while renewable energy production capacity is increasing rapidly","authors":"V. Kiray","doi":"10.3389/fenrg.2023.1285190","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1285190","url":null,"abstract":"","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139270065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-16DOI: 10.3389/fenrg.2023.1269041
Zheng Li, Chuan Li, Bao-Sheng Zhang, Qing Duan, Lu Liu, Guoqiang Zu, Qian Li
With the vigorous promotion of new energy policies, the large-scale charging of new energy vehicles has put forward higher requirements for the safety and stability of the distribution network. Based on the daily driving habits and charging patterns of new energy vehicles, a Monte Carlo sampling algorithm was used to establish a charging load model for new energy vehicles. The model analyzed the driving range, charging load, and time related parameters of new energy vehicles. By analyzing the law of daily charging power of new energy vehicles, the overall trend of charging load of new energy vehicles is obtained. Combined with the daily electricity consumption law of the distribution network, the total load of the distribution network is obtained, and the degree of impact on the distribution network is analyzed. This provides direction for the scheduling of future electric vehicle charging behavior and the construction of related supporting facilities, and provides strong guidance for the optimization and upgrading of the distribution network.
{"title":"Research on new energy vehicle charging prediction based on Monte Carlo algorithm and its impact on distribution network","authors":"Zheng Li, Chuan Li, Bao-Sheng Zhang, Qing Duan, Lu Liu, Guoqiang Zu, Qian Li","doi":"10.3389/fenrg.2023.1269041","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1269041","url":null,"abstract":"With the vigorous promotion of new energy policies, the large-scale charging of new energy vehicles has put forward higher requirements for the safety and stability of the distribution network. Based on the daily driving habits and charging patterns of new energy vehicles, a Monte Carlo sampling algorithm was used to establish a charging load model for new energy vehicles. The model analyzed the driving range, charging load, and time related parameters of new energy vehicles. By analyzing the law of daily charging power of new energy vehicles, the overall trend of charging load of new energy vehicles is obtained. Combined with the daily electricity consumption law of the distribution network, the total load of the distribution network is obtained, and the degree of impact on the distribution network is analyzed. This provides direction for the scheduling of future electric vehicle charging behavior and the construction of related supporting facilities, and provides strong guidance for the optimization and upgrading of the distribution network.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139269102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-16DOI: 10.3389/fenrg.2023.1296800
Yujiao Liu, Yan Li, Guoliang Li, Yuqing Lin, Ruiqi Wang, Yunpeng Fan
In order to further improve the efficiency of energy utilization, Integrated Energy Systems (IES) connect various energy systems closer, which has become an important energy utilization mode in the process of energy transition. Because the complex and variable multiple load is an important part of the new power system, the load forecasting is of great significance for the planning, operation, control, and dispatching of the new power system. In order to timely track the latest research progress of the load forecasting method and grasp the current research hotspot and the direction of load forecasting, this paper reviews the relevant research content of the forecasting methods. Firstly, a brief overview of Integrated Energy Systems and load forecasting is provided. Secondly, traditional forecasting methods based on statistical analysis and intelligent forecasting methods based on machine learning are discussed in two directions to analyze the advantages, disadvantages, and applicability of different methods. Then, the results of Integrated Energy Systemss multiple load forecasting for the past 5 years are compiled and analyzed. Finally, the Integrated Energy Systems load forecasting is summarized and looked forward.
{"title":"Review of multiple load forecasting method for integrated energy system","authors":"Yujiao Liu, Yan Li, Guoliang Li, Yuqing Lin, Ruiqi Wang, Yunpeng Fan","doi":"10.3389/fenrg.2023.1296800","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1296800","url":null,"abstract":"In order to further improve the efficiency of energy utilization, Integrated Energy Systems (IES) connect various energy systems closer, which has become an important energy utilization mode in the process of energy transition. Because the complex and variable multiple load is an important part of the new power system, the load forecasting is of great significance for the planning, operation, control, and dispatching of the new power system. In order to timely track the latest research progress of the load forecasting method and grasp the current research hotspot and the direction of load forecasting, this paper reviews the relevant research content of the forecasting methods. Firstly, a brief overview of Integrated Energy Systems and load forecasting is provided. Secondly, traditional forecasting methods based on statistical analysis and intelligent forecasting methods based on machine learning are discussed in two directions to analyze the advantages, disadvantages, and applicability of different methods. Then, the results of Integrated Energy Systemss multiple load forecasting for the past 5 years are compiled and analyzed. Finally, the Integrated Energy Systems load forecasting is summarized and looked forward.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139267840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the large-scale renewable energy integrated into the distribution grid, the grid’s regulating ability and disturbance tolerance are weakening. When partitioning demand-side resources, it is necessary to enhance resilience to ensure the reliability of electric power. This paper proposes a fast-partitioning method that considers resilience, structure, and functionality to adapt to the evolving requirements of the distribution system. Specifically, the comprehensive partition index system is constructed with the resilience assessment index reflecting the ability of partitions to withstand and mitigate the effects of faults, the modularity index based on electrical distance, and regional power balance indexes. Meanwhile, a modified genetic algorithm is proposed to calculate the comprehensive partition index. The modified algorithm first uses a sensitivity matrix to perform initial partitions and construct initial populations. Then, it utilizes a triangular network adjacency matrix for chromosome encoding, significantly reducing the algorithm’s search space and enhancing partitioning efficiency. Finally, the applicability and effectiveness of the proposed method are verified through simulation analysis of the IEEE 28-node system.
{"title":"A fast-partitioning decision method for demand side resources based on grid resilience assessment","authors":"Yueping Kong, Shihai Yang, Meimei Duan, Yuqi Zhou, Zecheng Ding, Tingquan Zhang, Ju Sheng","doi":"10.3389/fenrg.2023.1301175","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1301175","url":null,"abstract":"With the large-scale renewable energy integrated into the distribution grid, the grid’s regulating ability and disturbance tolerance are weakening. When partitioning demand-side resources, it is necessary to enhance resilience to ensure the reliability of electric power. This paper proposes a fast-partitioning method that considers resilience, structure, and functionality to adapt to the evolving requirements of the distribution system. Specifically, the comprehensive partition index system is constructed with the resilience assessment index reflecting the ability of partitions to withstand and mitigate the effects of faults, the modularity index based on electrical distance, and regional power balance indexes. Meanwhile, a modified genetic algorithm is proposed to calculate the comprehensive partition index. The modified algorithm first uses a sensitivity matrix to perform initial partitions and construct initial populations. Then, it utilizes a triangular network adjacency matrix for chromosome encoding, significantly reducing the algorithm’s search space and enhancing partitioning efficiency. Finally, the applicability and effectiveness of the proposed method are verified through simulation analysis of the IEEE 28-node system.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139269554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-16DOI: 10.3389/fenrg.2023.1267947
Muhammad Rameez Javed, M. Hussain, Mudassar Usman, Furqan Asghar, Muhammad Shahid, Waseem Amjad, Gwi Hyun Lee, A. Waleed
The recent trend of renewable energy has positioned solar cells as an excellent choice for energy production in today’s world. However, the performance of silicon photovoltaic (PV) panels can be influenced by various environmental factors such as humidity, light, rusting, temperature fluctuations and rain, etc. This study aims to investigate the potential impact of high voltage power transmission lines (HVTL) on the performance of solar cells at different distances from two high voltage levels (220 and 500 KV). In fact, HVTLs generate electromagnetic (EM) waves which may affect the power production and photocurrent density of solar cells. To analyze this impact, a real-time experimental setup of PV panel is developed (using both monocrystalline and polycrystalline solar cells), located in the vicinity of 220 and 500 KV HVTLs. In order to conduct this study systematically, the impact of HVTL on solar panel is being measured by varying the distance between the HVTL and the solar panels. However, it is important to understand that the obtained experimental values alone are insufficient for comprehensive verification under various conditions. To address this limitation, an Artificial Neural Network (ANN) is employed to generate HVTL impact curves for PV panels (particularly of voltage and current values) which are impractical to obtain experimentally. The inclusion of ANN approach enhances the understanding of the HVTL impact on solar cell performance across a wide range of conditions. Overall, this work presents the impact study of HVTL on two different types of solar cells at different distances from HVTL for two HV levels (i.e., 220 and 500 KV) and the comparison study of HVTL impact on both monocrystalline and polycrystalline solar cells.
{"title":"Experimental study on impact of high voltage power transmission lines on silicon photovoltaics using artificial neural network","authors":"Muhammad Rameez Javed, M. Hussain, Mudassar Usman, Furqan Asghar, Muhammad Shahid, Waseem Amjad, Gwi Hyun Lee, A. Waleed","doi":"10.3389/fenrg.2023.1267947","DOIUrl":"https://doi.org/10.3389/fenrg.2023.1267947","url":null,"abstract":"The recent trend of renewable energy has positioned solar cells as an excellent choice for energy production in today’s world. However, the performance of silicon photovoltaic (PV) panels can be influenced by various environmental factors such as humidity, light, rusting, temperature fluctuations and rain, etc. This study aims to investigate the potential impact of high voltage power transmission lines (HVTL) on the performance of solar cells at different distances from two high voltage levels (220 and 500 KV). In fact, HVTLs generate electromagnetic (EM) waves which may affect the power production and photocurrent density of solar cells. To analyze this impact, a real-time experimental setup of PV panel is developed (using both monocrystalline and polycrystalline solar cells), located in the vicinity of 220 and 500 KV HVTLs. In order to conduct this study systematically, the impact of HVTL on solar panel is being measured by varying the distance between the HVTL and the solar panels. However, it is important to understand that the obtained experimental values alone are insufficient for comprehensive verification under various conditions. To address this limitation, an Artificial Neural Network (ANN) is employed to generate HVTL impact curves for PV panels (particularly of voltage and current values) which are impractical to obtain experimentally. The inclusion of ANN approach enhances the understanding of the HVTL impact on solar cell performance across a wide range of conditions. Overall, this work presents the impact study of HVTL on two different types of solar cells at different distances from HVTL for two HV levels (i.e., 220 and 500 KV) and the comparison study of HVTL impact on both monocrystalline and polycrystalline solar cells.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139268330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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