Pub Date : 2024-05-03DOI: 10.3389/frsgr.2024.1397380
Andrew D. Syrmakesis, Nikos D. Hatziargyriou
For a more efficient monitoring and control of electrical energy, the physical components of conventional power systems are continuously integrated with information and communication technologies, converting them into smart grids. However, energy digitalization exposes power systems into a wide range of digital risks. The term cyber resilience for electrical grids expands the conventional resilience of power systems, which mainly refers to extreme weather phenomena. Since this is a relatively new term, there is a need for the establishment of a solid conceptual framework. This paper analyzes and classifies the state-of-the-art research methodologies proposed for strengthening the cyber resilience of smart grids. To this end, the proposed work categorizes the cyberattacks against smart grids, identifies the vulnerable spots of power system automation and establishes a common ground about the cyber resilience. The paper concludes with a discussion about the limitations of the proposed methods in order to extract useful suggestions for future directions.
{"title":"Cyber resilience methods for smart grids against false data injection attacks: categorization, review and future directions","authors":"Andrew D. Syrmakesis, Nikos D. Hatziargyriou","doi":"10.3389/frsgr.2024.1397380","DOIUrl":"https://doi.org/10.3389/frsgr.2024.1397380","url":null,"abstract":"For a more efficient monitoring and control of electrical energy, the physical components of conventional power systems are continuously integrated with information and communication technologies, converting them into smart grids. However, energy digitalization exposes power systems into a wide range of digital risks. The term cyber resilience for electrical grids expands the conventional resilience of power systems, which mainly refers to extreme weather phenomena. Since this is a relatively new term, there is a need for the establishment of a solid conceptual framework. This paper analyzes and classifies the state-of-the-art research methodologies proposed for strengthening the cyber resilience of smart grids. To this end, the proposed work categorizes the cyberattacks against smart grids, identifies the vulnerable spots of power system automation and establishes a common ground about the cyber resilience. The paper concludes with a discussion about the limitations of the proposed methods in order to extract useful suggestions for future directions.","PeriodicalId":318725,"journal":{"name":"Frontiers in Smart Grids","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141015855","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 : 2023-08-17DOI: 10.3389/frsgr.2023.1241963
Daniel Zhang, Jingyang Fang, S. Goetz
With the proliferation of alternative energy sources, power grids are increasingly dominated by grid-tied power converters. With this development comes the requirement of grid-forming, but current architectures exclude high-voltage applications through serial connectivity. Lattice power grids allow for the generation of both higher voltages and currents than their individual modules by marrying the advantages of serial and parallel connectivity, which include reduced switching and conduction losses, sensorless voltage balancing, and multiport operation. We use graph theory to model lattice power grids and formalize lattice generation processes for square, triangular, and hexagonal lattice grids. This article proposes depth-first-search based algorithms for the control and efficient operation of lattice power grids, achieving voltage and current objectives while minimizing switching losses. Furthermore, we build upon previous algorithms by harnessing multiple input/output operation. The algorithm allows for sequential operation (in which loads are added one by one), simultaneous operation (in which several loads are added at the same time), and combined sequential-simultaneous operation. These methods were applied to a variety of lattice structures, and simulations of dc analysis and pulse train generation were performed. These modeled results validate the proposed algorithms and improve versatility in the operation of lattice power grids in both grid-connected and standalone applications. The potential of applying this method in transcranial magnetic stimulation (TMS) is discussed.
{"title":"Control and optimization algorithm for lattice power grids with multiple input/output operation for improved versatility","authors":"Daniel Zhang, Jingyang Fang, S. Goetz","doi":"10.3389/frsgr.2023.1241963","DOIUrl":"https://doi.org/10.3389/frsgr.2023.1241963","url":null,"abstract":"With the proliferation of alternative energy sources, power grids are increasingly dominated by grid-tied power converters. With this development comes the requirement of grid-forming, but current architectures exclude high-voltage applications through serial connectivity. Lattice power grids allow for the generation of both higher voltages and currents than their individual modules by marrying the advantages of serial and parallel connectivity, which include reduced switching and conduction losses, sensorless voltage balancing, and multiport operation. We use graph theory to model lattice power grids and formalize lattice generation processes for square, triangular, and hexagonal lattice grids. This article proposes depth-first-search based algorithms for the control and efficient operation of lattice power grids, achieving voltage and current objectives while minimizing switching losses. Furthermore, we build upon previous algorithms by harnessing multiple input/output operation. The algorithm allows for sequential operation (in which loads are added one by one), simultaneous operation (in which several loads are added at the same time), and combined sequential-simultaneous operation. These methods were applied to a variety of lattice structures, and simulations of dc analysis and pulse train generation were performed. These modeled results validate the proposed algorithms and improve versatility in the operation of lattice power grids in both grid-connected and standalone applications. The potential of applying this method in transcranial magnetic stimulation (TMS) is discussed.","PeriodicalId":318725,"journal":{"name":"Frontiers in Smart Grids","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122955125","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 : 2023-03-09DOI: 10.3389/frsgr.2023.1129541
Xiaoguang Hao, Fei Jin, Bin Wang, Qinghao Zhang, Chuan Wu, Hao Sun
Due to aging and deformation of the through-flow path and system modifications, the flow characteristics of the turbine inlet valve often deviate from the design value, which affects the unit load control accuracy and operational stability. In order to obtain the actual valve flow characteristics of the turbine and thus improve the FM performance, an FCMLSSVM model is proposed in this paper to identify the valve flow characteristics. First, FCM clustering is proposed to classify the historical operating data of the plant and obtain a wide range of variable operating conditions. Then, using least squares support vector machine (LSSVM), the relationship between turbine input and output variables was modeled in each condition cluster, with integrated valve position command, speed, and real power generated as input variables and actual steam inlet flow as output variables. Using a 330 MW turbine unit as an application example, the established FCM-LSSVM model was validated for the valve flow characteristics of the turbine. The results show that the model can obtain accurate valve flow characteristics without conducting tests on the turbine. The method can save a lot of labor and material resources in doing the characteristic test, and after comparison, the proposed method can identify the flow characteristics more accurately among the existing neural network identification methods, which can provide technical support to improve the unit frequency regulation characteristics and improve the accuracy of valve operation.
{"title":"Research on the flow characteristics identification of steam turbine valve based on FCM-LSSVM","authors":"Xiaoguang Hao, Fei Jin, Bin Wang, Qinghao Zhang, Chuan Wu, Hao Sun","doi":"10.3389/frsgr.2023.1129541","DOIUrl":"https://doi.org/10.3389/frsgr.2023.1129541","url":null,"abstract":"Due to aging and deformation of the through-flow path and system modifications, the flow characteristics of the turbine inlet valve often deviate from the design value, which affects the unit load control accuracy and operational stability. In order to obtain the actual valve flow characteristics of the turbine and thus improve the FM performance, an FCMLSSVM model is proposed in this paper to identify the valve flow characteristics. First, FCM clustering is proposed to classify the historical operating data of the plant and obtain a wide range of variable operating conditions. Then, using least squares support vector machine (LSSVM), the relationship between turbine input and output variables was modeled in each condition cluster, with integrated valve position command, speed, and real power generated as input variables and actual steam inlet flow as output variables. Using a 330 MW turbine unit as an application example, the established FCM-LSSVM model was validated for the valve flow characteristics of the turbine. The results show that the model can obtain accurate valve flow characteristics without conducting tests on the turbine. The method can save a lot of labor and material resources in doing the characteristic test, and after comparison, the proposed method can identify the flow characteristics more accurately among the existing neural network identification methods, which can provide technical support to improve the unit frequency regulation characteristics and improve the accuracy of valve operation.","PeriodicalId":318725,"journal":{"name":"Frontiers in Smart Grids","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123385114","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 : 2023-01-12DOI: 10.3389/frsgr.2022.1110871
Xin Tian, Long Zhao, Chen Tong, Xiangfei Meng, Qibin Bo, Yubing Chen, Nian Liu
The large-scale access of distributed sources to the grid has brought great challenges to the safe and stable operation of the grid. At the same time, energy storage equipment is of great importance to effectively enhance the consumption of renewable energy and ensure the safe and stable operation of the grid. This paper proposes a method for optimal allocation of grid-side energy storage considering static security, which is based on stochastic power flow analysis under semi-invariant method. Firstly,according to the load, wind power and photovoltaic probability model, a system stochastic power flow model is constructed. Furthermore, the fault probability and fault severity indicators are established from two dimensions of branch power flow and node voltage. And combine the fault probability and severity indicators to establish a static security assessment indicators system. Then, a grid-side energy storage planning model is constructed from the perspective of energy storage operators. Finally, an improved genetic algorithm is used to solve the two-stage planning and operation problem proposed in this paper, and simulation analysis is conducted based on the IEEE-30 node system. The results show that the energy storage configuration considering static security constraints can effectively reduce the fault probability and the severity of fault overlimit. The simulation and case study verify that the proposed energy storage allocation method can effectively improve the static security of the system.
{"title":"Optimal configuration of grid-side energy storage considering static security of power system","authors":"Xin Tian, Long Zhao, Chen Tong, Xiangfei Meng, Qibin Bo, Yubing Chen, Nian Liu","doi":"10.3389/frsgr.2022.1110871","DOIUrl":"https://doi.org/10.3389/frsgr.2022.1110871","url":null,"abstract":"The large-scale access of distributed sources to the grid has brought great challenges to the safe and stable operation of the grid. At the same time, energy storage equipment is of great importance to effectively enhance the consumption of renewable energy and ensure the safe and stable operation of the grid. This paper proposes a method for optimal allocation of grid-side energy storage considering static security, which is based on stochastic power flow analysis under semi-invariant method. Firstly,according to the load, wind power and photovoltaic probability model, a system stochastic power flow model is constructed. Furthermore, the fault probability and fault severity indicators are established from two dimensions of branch power flow and node voltage. And combine the fault probability and severity indicators to establish a static security assessment indicators system. Then, a grid-side energy storage planning model is constructed from the perspective of energy storage operators. Finally, an improved genetic algorithm is used to solve the two-stage planning and operation problem proposed in this paper, and simulation analysis is conducted based on the IEEE-30 node system. The results show that the energy storage configuration considering static security constraints can effectively reduce the fault probability and the severity of fault overlimit. The simulation and case study verify that the proposed energy storage allocation method can effectively improve the static security of the system.","PeriodicalId":318725,"journal":{"name":"Frontiers in Smart Grids","volume":"39 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130734190","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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