Pub Date : 2024-08-02DOI: 10.3389/fenrg.2024.1419549
Jiahui Zhang, Tao Zhang, Yixuan Li, Xiang Bai, Longwen Chang
The global energy demand is increasing due to climate changes and carbon usages. Accumulating evidences showed energy sources using offshore wind from the sea can be added to increase our consumption capacity in long term. In addition, building offshore wind farms can also be environmentally advantageous compared to onshore farms. The assessment of wind energy resources is crucial for the site selection of wind farms. Currently, short-term wind forecast models have been developed to predict the wind power generation. However, methods are needed to improve the forecasting accuracy for ever-changing weather data. So, we try to use deep learning methods to predict long-term wind energy for identifying potential offshore wind farms. The experimental results indicate that PredRNN++ prediction model designed from the spatiotemporal perspective is feasible to evaluate long-term wind energy resources and has better performance than traditional LSTM.
{"title":"Study on mining wind information for identifying potential offshore wind farms using deep learning","authors":"Jiahui Zhang, Tao Zhang, Yixuan Li, Xiang Bai, Longwen Chang","doi":"10.3389/fenrg.2024.1419549","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1419549","url":null,"abstract":"The global energy demand is increasing due to climate changes and carbon usages. Accumulating evidences showed energy sources using offshore wind from the sea can be added to increase our consumption capacity in long term. In addition, building offshore wind farms can also be environmentally advantageous compared to onshore farms. The assessment of wind energy resources is crucial for the site selection of wind farms. Currently, short-term wind forecast models have been developed to predict the wind power generation. However, methods are needed to improve the forecasting accuracy for ever-changing weather data. So, we try to use deep learning methods to predict long-term wind energy for identifying potential offshore wind farms. The experimental results indicate that PredRNN++ prediction model designed from the spatiotemporal perspective is feasible to evaluate long-term wind energy resources and has better performance than traditional LSTM.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-02DOI: 10.3389/fenrg.2024.1383314
Costinela Fortea, Dragos Sebastian Cristea, Monica Laura Zlati, Valentin Marian Antohi, Mihaela Neculita, Nicoleta Cristache, Ioana Lazarescu
The current context of economic development requires paying close attention to the energy industry. Since 2022, European countries has been facing specific problems due to energy crises against the background of the geopolitical conflict and the measures provided by European forums in order to reduce dependence on energy imports from Russia. In this context, we aim to define a new model of energy consumption and the function of energy sustainability at the European level, aspects that will lead to highlighting the position of the 27 European member states in the period 2005–2022 in terms of their energy sustainability. The methodology used is based on the study of literature, the consolidation of databases, econometric modelling, and procedures for testing the validity of modelling results. The results of the study are useful to European energy policy decision-makers in view of the necessary adjustments to achieve the objectives of the 2030 and 2050 Agenda.
{"title":"Evaluation of the effectiveness of energy sustainability measures through the dynamic energy consumption model","authors":"Costinela Fortea, Dragos Sebastian Cristea, Monica Laura Zlati, Valentin Marian Antohi, Mihaela Neculita, Nicoleta Cristache, Ioana Lazarescu","doi":"10.3389/fenrg.2024.1383314","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1383314","url":null,"abstract":"The current context of economic development requires paying close attention to the energy industry. Since 2022, European countries has been facing specific problems due to energy crises against the background of the geopolitical conflict and the measures provided by European forums in order to reduce dependence on energy imports from Russia. In this context, we aim to define a new model of energy consumption and the function of energy sustainability at the European level, aspects that will lead to highlighting the position of the 27 European member states in the period 2005–2022 in terms of their energy sustainability. The methodology used is based on the study of literature, the consolidation of databases, econometric modelling, and procedures for testing the validity of modelling results. The results of the study are useful to European energy policy decision-makers in view of the necessary adjustments to achieve the objectives of the 2030 and 2050 Agenda.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141883000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-02DOI: 10.3389/fenrg.2024.1336016
Andreas Züttel, Christoph Nützenadel, Louis Schlapbach, Paul W. Gilgen
Graphical AbstractFuture supply of Switzerland with renewable energy. Assuming the volume of the hydroelectric storage lakes is doubled, the roof area is covered with photovoltaics, and eight power plant units are able to produce 1 GW on demand and are fueled with hydrogen or bio-oil. The reserves are the existing oil tanks, and the bio-oil is also used for aviation. Bio-oil can be produced in abundant places, e.g., Australia or Africa, where palm oil plantations are installed.
{"title":"Power plant units for CO2 neutral energy security in Switzerland","authors":"Andreas Züttel, Christoph Nützenadel, Louis Schlapbach, Paul W. Gilgen","doi":"10.3389/fenrg.2024.1336016","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1336016","url":null,"abstract":"Graphical Abstract<jats:fig><jats:caption>Future supply of Switzerland with renewable energy. Assuming the volume of the hydroelectric storage lakes is doubled, the roof area is covered with photovoltaics, and eight power plant units are able to produce 1 GW on demand and are fueled with hydrogen or bio-oil. The reserves are the existing oil tanks, and the bio-oil is also used for aviation. Bio-oil can be produced in abundant places, e.g., Australia or Africa, where palm oil plantations are installed.</jats:caption></jats:fig>","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.3389/fenrg.2024.1429295
Qun Li, Qiang Li, Weijia Tang, Chenggen Wang
The widespread integration of wind turbines poses voltage stability challenges to power systems. To enhance the ability of wind power systems to actively support grid voltage, grid-forming control techniques are increasingly being employed. However, current research primarily focuses on voltage stability challenges at the point of common coupling in wind power systems, lacking thorough investigation into system voltage response characterization. This paper establishes the voltage response model of a grid-forming wind power system. Based on this model, mathematical derivation and theoretical analysis are conducted, and the effect factors of the voltage at the point of common coupling are investigated. Furthermore, a voltage stabilization method is explored by adjusting the above effect factors. Finally, based on the MATLAB/Simulink platform, the simulation verification of each effect factor is carried out. The results indicate that voltage response characterization obtained by the theoretical analysis and simulation is similar and that the proposed method is valid.
{"title":"Voltage response characterization of grid-forming wind power systems","authors":"Qun Li, Qiang Li, Weijia Tang, Chenggen Wang","doi":"10.3389/fenrg.2024.1429295","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1429295","url":null,"abstract":"The widespread integration of wind turbines poses voltage stability challenges to power systems. To enhance the ability of wind power systems to actively support grid voltage, grid-forming control techniques are increasingly being employed. However, current research primarily focuses on voltage stability challenges at the point of common coupling in wind power systems, lacking thorough investigation into system voltage response characterization. This paper establishes the voltage response model of a grid-forming wind power system. Based on this model, mathematical derivation and theoretical analysis are conducted, and the effect factors of the voltage at the point of common coupling are investigated. Furthermore, a voltage stabilization method is explored by adjusting the above effect factors. Finally, based on the MATLAB/Simulink platform, the simulation verification of each effect factor is carried out. The results indicate that voltage response characterization obtained by the theoretical analysis and simulation is similar and that the proposed method is valid.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141883003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.3389/fenrg.2024.1428748
Xianshan Sun, Jinming Cai, Dongsheng Wang, Jinwei Lin, Kai Li
The virtual synchronous generator (VSG) has been widely used to improve the system inertia and damping in the renewable energy generation system. However, the in-depth understanding of VSG’s stability under disturbances on different control parameters is lacked. In order to solve the problem, the small-signal model of single-VSG is established at first. The influences of key control parameters on the stability of system are analyzed by using the eigenvalue analysis method in detail. On this basis, a novel optimization strategy for control parameters is proposed based on the Particle Swarm Optimization (PSO) algorithm. The control parameters are optimized to realize excellent damping and stability of VSG system. Finally, the simulation and experimental results verify the effectiveness of stability analysis and parameter optimization strategy.
{"title":"Small-disturbance stability analysis and control-parameter optimization of grid-connected virtual synchronous generator","authors":"Xianshan Sun, Jinming Cai, Dongsheng Wang, Jinwei Lin, Kai Li","doi":"10.3389/fenrg.2024.1428748","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1428748","url":null,"abstract":"The virtual synchronous generator (VSG) has been widely used to improve the system inertia and damping in the renewable energy generation system. However, the in-depth understanding of VSG’s stability under disturbances on different control parameters is lacked. In order to solve the problem, the small-signal model of single-VSG is established at first. The influences of key control parameters on the stability of system are analyzed by using the eigenvalue analysis method in detail. On this basis, a novel optimization strategy for control parameters is proposed based on the Particle Swarm Optimization (PSO) algorithm. The control parameters are optimized to realize excellent damping and stability of VSG system. Finally, the simulation and experimental results verify the effectiveness of stability analysis and parameter optimization strategy.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141883001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.3389/fenrg.2024.1407125
Davut Izci, Serdar Ekinci, Laith Abualigah, Mohammad Salman, Mostafa Rashdan
Solar energy has emerged as a key solution in the global transition to renewable energy sources, driven by environmental concerns and climate change. This is largely due to its cleanliness, availability, and cost-effectiveness. The precise assessment of hidden factors within photovoltaic (PV) models is critical for effectively exploiting the potential of these systems. This study employs a novel approach to parameter estimation, utilizing the electric eel foraging optimizer (EEFO), recently documented in the literature, to address such engineering issues. The EEFO emerges as a competitive metaheuristic methodology that plays a crucial role in enabling precise parameter extraction. In order to maintain scientific integrity and fairness, the study utilizes the RTC France solar cell as a benchmark case. We incorporate the EEFO approach, together with Newton-Raphson method, into the parameter tuning process for three PV models: single-diode, double-diode, and three-diode models, using a common experimental framework. We selected the RTC France solar cell for the single-diode, double-diode, and three-diode models because of its significant role in the field. It serves as a reliable evaluation platform for the EEFO approach. We conduct a thorough evaluation using statistical, convergence, and elapsed time studies, demonstrating that EEFO consistently achieves low RMSE values. This indicates that EEFO is capable of accurately estimating the current-voltage characteristics. The system’s smooth convergence behavior further reinforces its efficacy. Comparing the EEFO with competing methodologies reinforces its competitive advantage in optimizing solar PV model parameters, showcasing its potential to greatly enhance the usage of solar energy.
{"title":"Parameter extraction of photovoltaic cell models using electric eel foraging optimizer","authors":"Davut Izci, Serdar Ekinci, Laith Abualigah, Mohammad Salman, Mostafa Rashdan","doi":"10.3389/fenrg.2024.1407125","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1407125","url":null,"abstract":"Solar energy has emerged as a key solution in the global transition to renewable energy sources, driven by environmental concerns and climate change. This is largely due to its cleanliness, availability, and cost-effectiveness. The precise assessment of hidden factors within photovoltaic (PV) models is critical for effectively exploiting the potential of these systems. This study employs a novel approach to parameter estimation, utilizing the electric eel foraging optimizer (EEFO), recently documented in the literature, to address such engineering issues. The EEFO emerges as a competitive metaheuristic methodology that plays a crucial role in enabling precise parameter extraction. In order to maintain scientific integrity and fairness, the study utilizes the RTC France solar cell as a benchmark case. We incorporate the EEFO approach, together with Newton-Raphson method, into the parameter tuning process for three PV models: single-diode, double-diode, and three-diode models, using a common experimental framework. We selected the RTC France solar cell for the single-diode, double-diode, and three-diode models because of its significant role in the field. It serves as a reliable evaluation platform for the EEFO approach. We conduct a thorough evaluation using statistical, convergence, and elapsed time studies, demonstrating that EEFO consistently achieves low RMSE values. This indicates that EEFO is capable of accurately estimating the current-voltage characteristics. The system’s smooth convergence behavior further reinforces its efficacy. Comparing the EEFO with competing methodologies reinforces its competitive advantage in optimizing solar PV model parameters, showcasing its potential to greatly enhance the usage of solar energy.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141883004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.3389/fenrg.2024.1421865
Zhe Man, Zhe Xu, Zhonghua Gui, Wenfu Han, Yifeng Zhao, Fei Zhang, Lianchen Xu, Yuan Zheng, Kan Kan
In current engineering, the transition process of pump turbines from pump to turbine mode mainly includes the shutdown process of pump operating and the startup process of turbine operating, and the switching of working conditions mostly depends on the opening and closing of the ball valve. While, this article focuses on the transitional process of pump turbine from pump to turbine condition without relying on ball valve, which will significantly reduce the response time of the unit and enable quick switching of operating conditions in emergency situations. In this study, the torque balance equation is employed to analyze the transition process of the entire flow system from pump to turbine operation. Additionally, the entropy production theory is utilized to investigate the correlation between pressure, flow state, and energy loss in the pump-turbine, shedding light on the changes in external characteristics through the evolution of internal characteristics. Furthermore, the transition process from pump mode to turbine mode is segmented into five stages based on the variations in the guide vanes (GV). The findings reveal that the rotation of GV triggers sharp fluctuations in static pressure, torque, and axial force. During stage four, the initiation of all three GV positions results in an increase in flow rate and torque, accompanied by a decrease in axial force. In stage two, the closure of GV leads to a decrease in pressure within the spiral casing (SC) and stay vanes (SV) domains, coupled with an increase in pressure in the bladeless zone, runner, and draft tube domains. Simultaneously, the pressure difference between both sides of the runner decreases significantly, directly causing a drop in torque and axial force. In stage three, GV closure interrupts the flow in the pump-turbine, resulting in significant backflow in the SC, SV, and runner domains, alongside high-speed circulation in the bladeless area. Moreover, the location of the high entropy production rate (EPR) value within the unit aligns with the reflux zone, indicating considerable energy loss attributable to reflux. The above research results will provide reference for the rapid switching of operating conditions of pump turbines in emergency situations.
{"title":"Research on the performance of pump-turbine during the transition process from pump mode to turbine mode","authors":"Zhe Man, Zhe Xu, Zhonghua Gui, Wenfu Han, Yifeng Zhao, Fei Zhang, Lianchen Xu, Yuan Zheng, Kan Kan","doi":"10.3389/fenrg.2024.1421865","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1421865","url":null,"abstract":"In current engineering, the transition process of pump turbines from pump to turbine mode mainly includes the shutdown process of pump operating and the startup process of turbine operating, and the switching of working conditions mostly depends on the opening and closing of the ball valve. While, this article focuses on the transitional process of pump turbine from pump to turbine condition without relying on ball valve, which will significantly reduce the response time of the unit and enable quick switching of operating conditions in emergency situations. In this study, the torque balance equation is employed to analyze the transition process of the entire flow system from pump to turbine operation. Additionally, the entropy production theory is utilized to investigate the correlation between pressure, flow state, and energy loss in the pump-turbine, shedding light on the changes in external characteristics through the evolution of internal characteristics. Furthermore, the transition process from pump mode to turbine mode is segmented into five stages based on the variations in the guide vanes (GV). The findings reveal that the rotation of GV triggers sharp fluctuations in static pressure, torque, and axial force. During stage four, the initiation of all three GV positions results in an increase in flow rate and torque, accompanied by a decrease in axial force. In stage two, the closure of GV leads to a decrease in pressure within the spiral casing (SC) and stay vanes (SV) domains, coupled with an increase in pressure in the bladeless zone, runner, and draft tube domains. Simultaneously, the pressure difference between both sides of the runner decreases significantly, directly causing a drop in torque and axial force. In stage three, GV closure interrupts the flow in the pump-turbine, resulting in significant backflow in the SC, SV, and runner domains, alongside high-speed circulation in the bladeless area. Moreover, the location of the high entropy production rate (EPR) value within the unit aligns with the reflux zone, indicating considerable energy loss attributable to reflux. The above research results will provide reference for the rapid switching of operating conditions of pump turbines in emergency situations.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141883002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In DC transmission and distribution systems, both unipolar and bipolar transmission modes exist, and DC transformers used in these systems are also available in either unipolar or bipolar configurations. In actual systems, due to requirements such as economy, land occupation, and reliability, there is a tendency to use a system with unipolar input and bipolar output. However, the bipolar loads, if unbalanced, will lead to increased equipment costs and voltage imbalance, causing power quality problems. This paper defines the Power Unbalance Factor (PUF) to describe the power quality of the studied DC transmission system and presents an improved DC transformer topology based on a power balancing system. This topology realizes bipolar voltage balance and improves the power quality of the DC transmission system when the load is unbalanced. The influence of the proposed solution on the power design of the DC system is demonstrated through theoretical analysis, and its effectiveness for improving the DC power quality is verified by both simulations in MATLAB/Simulink environment and physical experiments. When the power electronic transformer needs to be overloaded, the proposed topology can reduce the design power of the two branches by using the difference power, which is economical.
{"title":"Power quality improvement of unipolar-input-bipolar-output DC transmission system via load power balancing","authors":"Zhuan Zhao, Haoran Li, Fei Sun, Shuhuai Shi, Di Wang, Jingxian Zhang, Chaoyang Wu","doi":"10.3389/fenrg.2024.1416785","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1416785","url":null,"abstract":"In DC transmission and distribution systems, both unipolar and bipolar transmission modes exist, and DC transformers used in these systems are also available in either unipolar or bipolar configurations. In actual systems, due to requirements such as economy, land occupation, and reliability, there is a tendency to use a system with unipolar input and bipolar output. However, the bipolar loads, if unbalanced, will lead to increased equipment costs and voltage imbalance, causing power quality problems. This paper defines the Power Unbalance Factor (PUF) to describe the power quality of the studied DC transmission system and presents an improved DC transformer topology based on a power balancing system. This topology realizes bipolar voltage balance and improves the power quality of the DC transmission system when the load is unbalanced. The influence of the proposed solution on the power design of the DC system is demonstrated through theoretical analysis, and its effectiveness for improving the DC power quality is verified by both simulations in MATLAB/Simulink environment and physical experiments. When the power electronic transformer needs to be overloaded, the proposed topology can reduce the design power of the two branches by using the difference power, which is economical.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141871084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.3389/fenrg.2024.1402566
Xiaoke Wang, Yan Ji, Zhongwang Sun, Chong Liu, Zhichun Jing
With advancements in communication systems and measurement technologies, smart grids have become more observable and controllable, evolving into cyber-physical-power systems (CPPS). The impact of network security and secondary equipment on power system stability has become more evident. To support the existing grid toward a smart grid scenario, smart metering plays a vital role at the customer end side. Cyber-Physical systems are vulnerable to cyber-attacks and various techniques have been evolved to detect a cyber attack in the smart grid. Weighted trust-based models are suggested as one of the most effective security mechanisms. A hardware-in-loop CPPS co-simulation platform is established to facilitate the theoretical study of CPPS and the formulation of grid operation strategies. This paper examines current co-simulation platform schemes and highlights the necessity for a real-time hard-ware-in-the-loop platform to accurately simulate cyber-attack processes. This consideration takes into account the fundamental differences in modeling between power and communication systems. The architecture of the co-simulation platform based on RT-LAB and OPNET is described, including detailed modeling of the power system, communication system, and security and stability control devices. Additionally, an analysis of the latency of the co-simulation is provided. The paper focuses on modeling and implementing methods for addressing DDOS attacks and man-in-the-middle at-tacks in the communication network. The results from simulating a 7-bus system show the effectiveness and rationality of the co-simulation platform that has been designed.
{"title":"Improving cyber-physical-power system stability through hardware-in-loop co-simulation platform for real-time cyber attack analysis","authors":"Xiaoke Wang, Yan Ji, Zhongwang Sun, Chong Liu, Zhichun Jing","doi":"10.3389/fenrg.2024.1402566","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1402566","url":null,"abstract":"With advancements in communication systems and measurement technologies, smart grids have become more observable and controllable, evolving into cyber-physical-power systems (CPPS). The impact of network security and secondary equipment on power system stability has become more evident. To support the existing grid toward a smart grid scenario, smart metering plays a vital role at the customer end side. Cyber-Physical systems are vulnerable to cyber-attacks and various techniques have been evolved to detect a cyber attack in the smart grid. Weighted trust-based models are suggested as one of the most effective security mechanisms. A hardware-in-loop CPPS co-simulation platform is established to facilitate the theoretical study of CPPS and the formulation of grid operation strategies. This paper examines current co-simulation platform schemes and highlights the necessity for a real-time hard-ware-in-the-loop platform to accurately simulate cyber-attack processes. This consideration takes into account the fundamental differences in modeling between power and communication systems. The architecture of the co-simulation platform based on RT-LAB and OPNET is described, including detailed modeling of the power system, communication system, and security and stability control devices. Additionally, an analysis of the latency of the co-simulation is provided. The paper focuses on modeling and implementing methods for addressing DDOS attacks and man-in-the-middle at-tacks in the communication network. The results from simulating a 7-bus system show the effectiveness and rationality of the co-simulation platform that has been designed.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141871082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.3389/fenrg.2024.1411654
Lu Jiangang, Zhao Ruifeng, Yu Zhiwen, Dai Yue, Shu Jiawei, Yang Ting
With the advancement of source-load interaction in the new power systems, data-driven approaches have provided a foundational support for aggregating and interacting between sources and loads. However, with the widespread integration of distributed energy resources, fine-grained perception of intelligent sensing devices, and the inherent stochasticity of source-load dynamics, a massive amount of raw data is being recorded and accumulated in the data center. Valuable information is often dispersed across different paragraphs of the raw data, making it challenging to extract effectively. Distribution substation inspection plays a crucial role in ensuring the safe operation of the power system. Traditional methods for inspection report text classification typically rely on manual judgment and accumulated experience, resulting in low efficiency and a significant misjudgment rate. Therefore, this paper proposes a text classification method for inspection reports based on the pre-trained BERT-TextRCNN model. By utilizing the dense connection between the BERT embedding layer and the neural network, the proposed method improves the accuracy of matching long texts. This article collected 2,831 maintenance data for the first quarter of 2023 from the distribution room, including approximately 58 environmental testing data, 738 environmental box testing data, approximately 672 distribution room testing data, and approximately 1,363 box type substation testing data. A text corpus was constructed for experiments. Experimental results demonstrate that the proposed model automatically classifies a large volume of manually recorded inspection report data based on time, location, and faults, achieving a classification accuracy of 94.7%, precision of 92%, recall of 92%, and F1 score of 90.3%.
{"title":"Text classification for distribution substation inspection based on BERT-TextRCNN model","authors":"Lu Jiangang, Zhao Ruifeng, Yu Zhiwen, Dai Yue, Shu Jiawei, Yang Ting","doi":"10.3389/fenrg.2024.1411654","DOIUrl":"https://doi.org/10.3389/fenrg.2024.1411654","url":null,"abstract":"With the advancement of source-load interaction in the new power systems, data-driven approaches have provided a foundational support for aggregating and interacting between sources and loads. However, with the widespread integration of distributed energy resources, fine-grained perception of intelligent sensing devices, and the inherent stochasticity of source-load dynamics, a massive amount of raw data is being recorded and accumulated in the data center. Valuable information is often dispersed across different paragraphs of the raw data, making it challenging to extract effectively. Distribution substation inspection plays a crucial role in ensuring the safe operation of the power system. Traditional methods for inspection report text classification typically rely on manual judgment and accumulated experience, resulting in low efficiency and a significant misjudgment rate. Therefore, this paper proposes a text classification method for inspection reports based on the pre-trained BERT-TextRCNN model. By utilizing the dense connection between the BERT embedding layer and the neural network, the proposed method improves the accuracy of matching long texts. This article collected 2,831 maintenance data for the first quarter of 2023 from the distribution room, including approximately 58 environmental testing data, 738 environmental box testing data, approximately 672 distribution room testing data, and approximately 1,363 box type substation testing data. A text corpus was constructed for experiments. Experimental results demonstrate that the proposed model automatically classifies a large volume of manually recorded inspection report data based on time, location, and faults, achieving a classification accuracy of 94.7%, precision of 92%, recall of 92%, and F1 score of 90.3%.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141871081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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