Pub Date : 2024-11-11DOI: 10.17775/CSEEJPES.2023.10060
Lin Yu;Shiyun Xu;Huadong Sun;Bing Zhao;Guanglu Wu;Xiaoxin Zhou
Inverter-based resources (IBRs), such as wind and photovoltaic generation, are characterized by low capacity and extensive distribution, which can exacerbate the weak properties of power systems. Precise identification of weak system status is essential for ensuring the security and economic efficiency of IBR integration. This paper proposes the index of the multiple renewable short-circuit ratio (MRSCR) and its critical value calculated by the voltage (CMRSCR) to provide a comprehensive assessment of power system strength in the presence of high IBR penetration, enhancing the accuracy and reliability of system strength evaluation. First, we introduce a single-infeed equivalent model of the power system integrating multiple IBRs. We examine the factors associated with system properties that are crucial in the strength assessment process. Subsequently, the MRSCR is derived from this analysis. The MRSCR describes the connection between system strength and voltage variation caused by power fluctuations. This implies that voltage variation caused by IBR power fluctuations is more pronounced under weak grid conditions. Following this, the CMRSCR is proposed to precisely evaluate the stability boundary. The disparity between MRSCR and CMRSCR is utilized to evaluate the stability margin of the power system. Unlike a fixed value, the CMRSCR exhibits higher sensitivity as the system approaches a critical state. These indexes have been implemented in the PSD power tools and power system analysis software package, facilitating engineering calculation and analysis of bulk power systems in China. Finally, simulation results validate the effectiveness of the proposed indexes and the research findings.
{"title":"Multiple Renewable Short-Circuit Ratio for Assessing Weak System Strength with Inverter-Based Resources","authors":"Lin Yu;Shiyun Xu;Huadong Sun;Bing Zhao;Guanglu Wu;Xiaoxin Zhou","doi":"10.17775/CSEEJPES.2023.10060","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.10060","url":null,"abstract":"Inverter-based resources (IBRs), such as wind and photovoltaic generation, are characterized by low capacity and extensive distribution, which can exacerbate the weak properties of power systems. Precise identification of weak system status is essential for ensuring the security and economic efficiency of IBR integration. This paper proposes the index of the multiple renewable short-circuit ratio (MRSCR) and its critical value calculated by the voltage (CMRSCR) to provide a comprehensive assessment of power system strength in the presence of high IBR penetration, enhancing the accuracy and reliability of system strength evaluation. First, we introduce a single-infeed equivalent model of the power system integrating multiple IBRs. We examine the factors associated with system properties that are crucial in the strength assessment process. Subsequently, the MRSCR is derived from this analysis. The MRSCR describes the connection between system strength and voltage variation caused by power fluctuations. This implies that voltage variation caused by IBR power fluctuations is more pronounced under weak grid conditions. Following this, the CMRSCR is proposed to precisely evaluate the stability boundary. The disparity between MRSCR and CMRSCR is utilized to evaluate the stability margin of the power system. Unlike a fixed value, the CMRSCR exhibits higher sensitivity as the system approaches a critical state. These indexes have been implemented in the PSD power tools and power system analysis software package, facilitating engineering calculation and analysis of bulk power systems in China. Finally, simulation results validate the effectiveness of the proposed indexes and the research findings.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 6","pages":"2271-2282"},"PeriodicalIF":6.9,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10748596","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142859061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-19DOI: 10.17775/CSEEJPES.2023.07130
Bin Deng;Xiaosheng Xu;Mengshi Li;Tianyao Ji;Q. H. Wu
Although integrated energy systems (IES) are currently modest in size, their scheduling faces strong challenges, stemming from both wind generation disturbances and the system's complexity, including intrinsic heterogeneity and pronounced non-linearity. For this reason, a two-stage algorithm called the Multi-Objective Group Search Optimizer with Pre-Exploration (MOGSOPE) is proposed to efficiently achieve the optimal solution under wind generation disturbances. The optimizer has an embedded trainable surrogate model, Deep Neural Networks (DNNs), to explore the common features of the multi-scenario search space in advance, guiding the population toward a more efficient search in each scenario. Furthermore, a multi-scenario Multi-Attribute Decision Making (MADM) approach is proposed to make the final decision from all alternatives in different wind scenarios. It reflects not only the decision-maker's (DM) interests in other indicators of IES but also their risk preference for wind generation disturbances. A case study conducted in Barry Island shows the superior convergence and diversity of MOGSOPE in comparison to other optimization algorithms. With respect to numerical performance metrics HV, IGD, and SI, the proposed optimizer exhibits improvements of 3.1036%, 4.8740%, and 4.2443% over MOGSO, and 4.2435%, 6.2479%, and 52.9230% over NSGAII, respectively. What's more, the effectiveness of the multi-scenario MADM in making final decisions under uncertainty is demonstrated, particularly in optimal scheduling of IES under wind generation disturbances.
虽然综合能源系统（IES）目前的规模不大，但由于风力发电的干扰和系统的复杂性，包括内在的异质性和明显的非线性，它们的调度面临着巨大的挑战。为此，提出了一种两阶段的多目标群搜索优化器预探索算法（multiobjective Group Search Optimizer with Pre-Exploration， MOGSOPE），以有效地实现风力发电扰动下的最优解。优化器具有嵌入式可训练代理模型深度神经网络（Deep Neural Networks, dnn），可以提前探索多场景搜索空间的共同特征，引导人群在每个场景中进行更有效的搜索。在此基础上，提出了一种多场景多属性决策（MADM）方法，对不同风场下的所有备选方案进行最终决策。它不仅反映了决策者对IES其他指标的兴趣，也反映了决策者对风力发电扰动的风险偏好。在巴里岛进行的实例研究表明，与其他优化算法相比，MOGSOPE具有更好的收敛性和多样性。在数值性能指标HV、IGD和SI方面，该优化器比MOGSO分别提高了3.1036%、4.8740%和4.2443%，比NSGAII分别提高了4.2435%、6.2479%和52.9230%。此外，还验证了多场景MADM在不确定条件下做出最终决策的有效性，特别是在风力发电干扰下IES最优调度的有效性。
{"title":"Two-Stage Multi-Objective Optimization and Decision-Making Method for Integrated Energy System Under Wind Generation Disturbances","authors":"Bin Deng;Xiaosheng Xu;Mengshi Li;Tianyao Ji;Q. H. Wu","doi":"10.17775/CSEEJPES.2023.07130","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.07130","url":null,"abstract":"Although integrated energy systems (IES) are currently modest in size, their scheduling faces strong challenges, stemming from both wind generation disturbances and the system's complexity, including intrinsic heterogeneity and pronounced non-linearity. For this reason, a two-stage algorithm called the Multi-Objective Group Search Optimizer with Pre-Exploration (MOGSOPE) is proposed to efficiently achieve the optimal solution under wind generation disturbances. The optimizer has an embedded trainable surrogate model, Deep Neural Networks (DNNs), to explore the common features of the multi-scenario search space in advance, guiding the population toward a more efficient search in each scenario. Furthermore, a multi-scenario Multi-Attribute Decision Making (MADM) approach is proposed to make the final decision from all alternatives in different wind scenarios. It reflects not only the decision-maker's (DM) interests in other indicators of IES but also their risk preference for wind generation disturbances. A case study conducted in Barry Island shows the superior convergence and diversity of MOGSOPE in comparison to other optimization algorithms. With respect to numerical performance metrics HV, IGD, and SI, the proposed optimizer exhibits improvements of 3.1036%, 4.8740%, and 4.2443% over MOGSO, and 4.2435%, 6.2479%, and 52.9230% over NSGAII, respectively. What's more, the effectiveness of the multi-scenario MADM in making final decisions under uncertainty is demonstrated, particularly in optimal scheduling of IES under wind generation disturbances.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 6","pages":"2564-2576"},"PeriodicalIF":6.9,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684463","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142870218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-19DOI: 10.17775/CSEEJPES.2023.04900
Lei Chen;Tianhao Wen;Yuqing Lin;Yang Liu;Q. H. Wu;Chao Hong;Yinsheng Su
Transient voltage stability analysis (TVSA) of power systems is one of the most computationally challenging tasks in dynamic security assessment. To reduce the complexity of TVSA, this paper proposes an improved expanding annular domain (improved EAD) algorithm to estimate the domain of attraction (DA) of power systems containing multiple induction motors (IMs), whose improvements are concerned with relaxing the restriction on critical value and simplifying iteration steps. The proposed algorithm can systematically construct Lyapunov function for lossy power systems with IMs and their slip constraints. First, the extended Lyapunov stability theory and sum of squares (SOS) programming are presented, which are powerful tools to construct Lyapunov function. Second, the internal node model of IM is developed by an analogy with that of a synchronous generator, and a multi-machine power system model by eliminating algebraic variables is derived. Then, an improved EAD algorithm with SOS programming is proposed to estimate the DA for a power system considering the slip constraint of IM. Finally, the superiority of our method is demonstrated on two modified IEEE test cases. Simulation results show that the proposed algorithm can provide a better estimated DA and critical clearing slip for power systems with multiple IMs.
{"title":"Improved EAD Algorithm to Estimate Domains of Attraction of Power Systems Including Induction Motors for Transient Voltage Stability Analysis","authors":"Lei Chen;Tianhao Wen;Yuqing Lin;Yang Liu;Q. H. Wu;Chao Hong;Yinsheng Su","doi":"10.17775/CSEEJPES.2023.04900","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.04900","url":null,"abstract":"Transient voltage stability analysis (TVSA) of power systems is one of the most computationally challenging tasks in dynamic security assessment. To reduce the complexity of TVSA, this paper proposes an improved expanding annular domain (improved EAD) algorithm to estimate the domain of attraction (DA) of power systems containing multiple induction motors (IMs), whose improvements are concerned with relaxing the restriction on critical value and simplifying iteration steps. The proposed algorithm can systematically construct Lyapunov function for lossy power systems with IMs and their slip constraints. First, the extended Lyapunov stability theory and sum of squares (SOS) programming are presented, which are powerful tools to construct Lyapunov function. Second, the internal node model of IM is developed by an analogy with that of a synchronous generator, and a multi-machine power system model by eliminating algebraic variables is derived. Then, an improved EAD algorithm with SOS programming is proposed to estimate the DA for a power system considering the slip constraint of IM. Finally, the superiority of our method is demonstrated on two modified IEEE test cases. Simulation results show that the proposed algorithm can provide a better estimated DA and critical clearing slip for power systems with multiple IMs.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 6","pages":"2321-2332"},"PeriodicalIF":6.9,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684526","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142859064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-19DOI: 10.17775/CSEEJPES.2024.00600
Hong Lu;Xianyong Xiao;Guangfu Tang;Zhiyuan He;Zhiguang Lin;Chong Gao;Zixuan Zheng
The participation of photovoltaic (PV) plants in supporting the transient voltage caused by commutation failure in the line-commutated-converter-based high voltage direct current (LCC-HVDC) system is of great significance, as it can enhance the DC transmission ability. However, it is found that the grid-following (GFL) PV converters face the problem of mismatch between reactive power response and transient voltage characteristic when the voltage converts from low voltage to overvoltage, further aggravating the overvoltage amplitude. Thus, this article proposes a transient voltage support strategy based on the grid-forming (GFM) medium voltage PV converter. The proposed strategy takes the advantage of the close equivalent electrical distance between the converter and grid, which can autonomously control the converter terminal voltage through GFM control with adaptive voltage droop coefficient. The simulation results show that the proposed strategy can ensure the output reactive power of the PV converter quickly matches the transient voltage characteristic at different stages, indicating that the proposed strategy can effectively support the transient voltage.
{"title":"Transient Voltage Support Strategy of Grid-Forming Medium Voltage Photovoltaic Converter in the LCC-HVDC System","authors":"Hong Lu;Xianyong Xiao;Guangfu Tang;Zhiyuan He;Zhiguang Lin;Chong Gao;Zixuan Zheng","doi":"10.17775/CSEEJPES.2024.00600","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2024.00600","url":null,"abstract":"The participation of photovoltaic (PV) plants in supporting the transient voltage caused by commutation failure in the line-commutated-converter-based high voltage direct current (LCC-HVDC) system is of great significance, as it can enhance the DC transmission ability. However, it is found that the grid-following (GFL) PV converters face the problem of mismatch between reactive power response and transient voltage characteristic when the voltage converts from low voltage to overvoltage, further aggravating the overvoltage amplitude. Thus, this article proposes a transient voltage support strategy based on the grid-forming (GFM) medium voltage PV converter. The proposed strategy takes the advantage of the close equivalent electrical distance between the converter and grid, which can autonomously control the converter terminal voltage through GFM control with adaptive voltage droop coefficient. The simulation results show that the proposed strategy can ensure the output reactive power of the PV converter quickly matches the transient voltage characteristic at different stages, indicating that the proposed strategy can effectively support the transient voltage.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 5","pages":"1849-1864"},"PeriodicalIF":6.9,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684468","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.17775/CSEEJPES.2023.08830
Huayi Wu;Zhao Xu;Jiaqi Ruan;Xianzhuo Sun
A centralized framework-based data-driven framework for active distribution system state estimation (DSSE) has been widely leveraged. However, it is challenged by potential data privacy breaches due to the aggregation of raw measurement data in a data center. A personalized federated learning-based DSSE method (PFL-DSSE) is proposed in a decentralized training framework for DSSE. Experimental validation confirms that PFL-DSSE can effectively and efficiently maintain data confidentiality and enhance estimation accuracy.
{"title":"PFL-DSSE: A Personalized Federated Learning Approach for Distribution System State Estimation","authors":"Huayi Wu;Zhao Xu;Jiaqi Ruan;Xianzhuo Sun","doi":"10.17775/CSEEJPES.2023.08830","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.08830","url":null,"abstract":"A centralized framework-based data-driven framework for active distribution system state estimation (DSSE) has been widely leveraged. However, it is challenged by potential data privacy breaches due to the aggregation of raw measurement data in a data center. A personalized federated learning-based DSSE method (PFL-DSSE) is proposed in a decentralized training framework for DSSE. Experimental validation confirms that PFL-DSSE can effectively and efficiently maintain data confidentiality and enhance estimation accuracy.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 5","pages":"2265-2270"},"PeriodicalIF":6.9,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10609318","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-03DOI: 10.17775/CSEEJPES.2022.08260
Wanning Zheng;Jiabing Hu;Li Chai;Bing Liu;Zixia Sang
The small-signal stability of multi-terminal high voltage direct current (HVDC) systems has become one of the vital issues in modern power systems. Interactions among voltage source converters (VSCs) have a significant impact on the stability of the system. This paper proposes an interaction quantification method based on the self-/en-stabilizing coefficients of the general $boldsymbol{N}-mathbf{terminal}$ HVDC system with a weak AC network connection. First, we derive the explicit formulae of self-/en-stabilizing coefficients for any $boldsymbol{N}-mathbf{terminal}$ HVDC system, which can quantify the interactions through different paths analytically. The relation between the self-/en-stabilizing coefficients and the poles of the system can be used to evaluate the impact of the interactions on the system stability effectively. Then, we employ the obtained formulae to analyze the parameter sensitivity and explain how a parameter affects the stability of the system through different paths of interactions. Finally, extensive examples are given to demonstrate the effectiveness of the proposed method.
{"title":"Interaction Quantification of MTDC Systems Connected with Weak AC Grids","authors":"Wanning Zheng;Jiabing Hu;Li Chai;Bing Liu;Zixia Sang","doi":"10.17775/CSEEJPES.2022.08260","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.08260","url":null,"abstract":"The small-signal stability of multi-terminal high voltage direct current (HVDC) systems has become one of the vital issues in modern power systems. Interactions among voltage source converters (VSCs) have a significant impact on the stability of the system. This paper proposes an interaction quantification method based on the self-/en-stabilizing coefficients of the general \u0000<tex>$boldsymbol{N}-mathbf{terminal}$</tex>\u0000 HVDC system with a weak AC network connection. First, we derive the explicit formulae of self-/en-stabilizing coefficients for any \u0000<tex>$boldsymbol{N}-mathbf{terminal}$</tex>\u0000 HVDC system, which can quantify the interactions through different paths analytically. The relation between the self-/en-stabilizing coefficients and the poles of the system can be used to evaluate the impact of the interactions on the system stability effectively. Then, we employ the obtained formulae to analyze the parameter sensitivity and explain how a parameter affects the stability of the system through different paths of interactions. Finally, extensive examples are given to demonstrate the effectiveness of the proposed method.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 5","pages":"2088-2099"},"PeriodicalIF":6.9,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520204","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-03DOI: 10.17775/CSEEJPES.2022.05990
Chenxi Fan;Kaishun Xiahou;Lei Wang;Q. H. Wu
This paper presents a long short-term memory (LSTM)-based fault detection method to detect the multiple open-circuit switch faults of modular multilevel converter (MMC) systems with full-bridge sub-modules (FB-SMs). Eighteen sensor signals of grid voltages, grid currents and capacitance voltages of MMC for single and multi-switch faults are collected as sampling data. The output signal characteristics of four types of single switch faults of FB-SM, as well as double switch faults in the same and different phases of MMC, are analyzed under the conditions of load variations and control command changes. A multi-layer LSTM network is devised to deeply extract the fault characteristics of MMC under different faults and operation conditions, and a Softmax layer detects the fault types. Simulation results have confirmed that the proposed LSTM-based method has better detection performance compared with three other methods: K-nearest neighbor (KNN), naive bayes (NB) and recurrent neural network (RNN). In addition, it is highly robust to model uncertainties and Gaussian noise. The validity of the proposed method is further demonstrated by experiment studies conducted on a hardware-in-the-loop (HIL) testing platform.
{"title":"Data-Driven Fault Detection of Multiple Open-Circuit Faults for MMC Systems Based on Long Short-Term Memory Networks","authors":"Chenxi Fan;Kaishun Xiahou;Lei Wang;Q. H. Wu","doi":"10.17775/CSEEJPES.2022.05990","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.05990","url":null,"abstract":"This paper presents a long short-term memory (LSTM)-based fault detection method to detect the multiple open-circuit switch faults of modular multilevel converter (MMC) systems with full-bridge sub-modules (FB-SMs). Eighteen sensor signals of grid voltages, grid currents and capacitance voltages of MMC for single and multi-switch faults are collected as sampling data. The output signal characteristics of four types of single switch faults of FB-SM, as well as double switch faults in the same and different phases of MMC, are analyzed under the conditions of load variations and control command changes. A multi-layer LSTM network is devised to deeply extract the fault characteristics of MMC under different faults and operation conditions, and a Softmax layer detects the fault types. Simulation results have confirmed that the proposed LSTM-based method has better detection performance compared with three other methods: K-nearest neighbor (KNN), naive bayes (NB) and recurrent neural network (RNN). In addition, it is highly robust to model uncertainties and Gaussian noise. The validity of the proposed method is further demonstrated by experiment studies conducted on a hardware-in-the-loop (HIL) testing platform.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 4","pages":"1563-1574"},"PeriodicalIF":6.9,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520155","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141966191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-03DOI: 10.17775/CSEEJPES.2022.07880
Shouqi Jiang;Huanyu Zhao;Guoqing Li;Yechun Xin;Lixin Wang;Weiru Wang
A DC grid based on half-bridge modular multilevel converters (HB-MMC) is a feasible means to realize the friendly grid connection of renewable energy. To solve problems such as the high cost and technical difficulty of DC circuit breakers (DCCB), a coordinated control method for fault current suppression of DC grid connecting wind power is proposed. The key influencing factors of DC fault current are revealed by fault characteristics analysis, and an adaptive current-limiting control method for MMC is proposed, whose parameter selection principles are designed to ensure the safe operation of equipment while achieving effective suppression of fault current. In addition, a novel configuration method of dissipative resistors with the current-limiting function is proposed, which can solve the problem of surplus power in the DC grid and reduce the current stress of converter valves. Based on this, a coordination scheme of dissipative resistors, the adaptive current-limiting control method, and DCCBs are proposed to block fault current, effectively reducing the manufacturing difficulty and cost of DCCB. Finally, a four-terminal DC grid simulation model is built based on the RTLAB OP5600 real-time digital simulation platform, and the effectiveness and feasibility of the proposed methods are verified.
{"title":"Coordinated Suppression Method of Fault Current for DC Grid with Novel Dissipative Resistors Topology","authors":"Shouqi Jiang;Huanyu Zhao;Guoqing Li;Yechun Xin;Lixin Wang;Weiru Wang","doi":"10.17775/CSEEJPES.2022.07880","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.07880","url":null,"abstract":"A DC grid based on half-bridge modular multilevel converters (HB-MMC) is a feasible means to realize the friendly grid connection of renewable energy. To solve problems such as the high cost and technical difficulty of DC circuit breakers (DCCB), a coordinated control method for fault current suppression of DC grid connecting wind power is proposed. The key influencing factors of DC fault current are revealed by fault characteristics analysis, and an adaptive current-limiting control method for MMC is proposed, whose parameter selection principles are designed to ensure the safe operation of equipment while achieving effective suppression of fault current. In addition, a novel configuration method of dissipative resistors with the current-limiting function is proposed, which can solve the problem of surplus power in the DC grid and reduce the current stress of converter valves. Based on this, a coordination scheme of dissipative resistors, the adaptive current-limiting control method, and DCCBs are proposed to block fault current, effectively reducing the manufacturing difficulty and cost of DCCB. Finally, a four-terminal DC grid simulation model is built based on the RTLAB OP5600 real-time digital simulation platform, and the effectiveness and feasibility of the proposed methods are verified.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 6","pages":"2371-2383"},"PeriodicalIF":6.9,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142859145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-03DOI: 10.17775/CSEEJPES.2022.07470
Haoyuan Yan;Tianyang Zhao;Zhanglei Guan
The rapid development of electric vehicles (EVs) is strengthening the bi-directional interactions between electric power networks (EPNs) and transportation networks (TNs) while providing opportunities to enhance the resilience of power systems towards extreme events. To quantify the temporal and spatial flexibility of EVs for charging and discharging, a novel dynamic traffic assignment (DTA) problem is proposed. The DTA problem is based on a link transmission model (LTM) with extended charging links, depicting the interaction between EVs and power systems. It models the charging rates as continuous variables by an energy boundary model. To consider the evacuation requirements of TNs and the uncertainties of traffic conditions, the DTA problem is extended to a two-stage distributionally robust version. It is further incorporated into a two-stage distributionally robust unit commitment problem to balance the enhancement of EPNs and the performance of TNs. The problem is reformulated into a mixed-integer linear programming problem and solved by off-the-shelf commercial solvers. Case studies are performed on two test networks. The effectiveness is verified by the numerical results, e.g., reducing the load shedding amount without increasing the unmet traffic demand.
{"title":"Proactive Resilience Enhancement of Power Systems with Link Transmission Model-Based Dynamic Traffic Assignment Among Electric Vehicles","authors":"Haoyuan Yan;Tianyang Zhao;Zhanglei Guan","doi":"10.17775/CSEEJPES.2022.07470","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.07470","url":null,"abstract":"The rapid development of electric vehicles (EVs) is strengthening the bi-directional interactions between electric power networks (EPNs) and transportation networks (TNs) while providing opportunities to enhance the resilience of power systems towards extreme events. To quantify the temporal and spatial flexibility of EVs for charging and discharging, a novel dynamic traffic assignment (DTA) problem is proposed. The DTA problem is based on a link transmission model (LTM) with extended charging links, depicting the interaction between EVs and power systems. It models the charging rates as continuous variables by an energy boundary model. To consider the evacuation requirements of TNs and the uncertainties of traffic conditions, the DTA problem is extended to a two-stage distributionally robust version. It is further incorporated into a two-stage distributionally robust unit commitment problem to balance the enhancement of EPNs and the performance of TNs. The problem is reformulated into a mixed-integer linear programming problem and solved by off-the-shelf commercial solvers. Case studies are performed on two test networks. The effectiveness is verified by the numerical results, e.g., reducing the load shedding amount without increasing the unmet traffic demand.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 3","pages":"1320-1330"},"PeriodicalIF":7.1,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520179","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-03DOI: 10.17775/CSEEJPES.2023.04990
Feng Hong;Yalei Pang;Weiming Ji;Lu Liang;Fang Fang;Junhong Hao;Jizhen Liu
Frequency stability and security have been a vital challenge as large-scale renewable energy is integrated into power systems. In contrast, the proportion of traditional thermal power units decreases during the decarbonization transformation process, resulting in poor frequency support. This paper aims to explore the potential of frequency regulation support, dynamic assessment, and capacity promotion of thermal power plants in the transition period. Considering the dynamic characteristics of the main steam working fluid under different working conditions, a nonlinear observer is constructed by extracting the main steam pressure and valve opening degree parameters. The real-time frequency modulation capacity of thermal power units can provide a dynamic state for the power grid. A dynamic adaptive modification for primary frequency control (PFC) of power systems, including wind power and thermal power, is proposed and improved. The power dynamic allocation factor is adaptively optimized by predicting the speed droop ratio, and the frequency modulation capability of the system is improved by more than 11% under extreme conditions. Finally, through the Monte Carlo simulation of unit states of the system under various working conditions, the promotion of the frequency regulation capacity with high wind power penetration (WPP) is verified.
{"title":"Assessment and Enhancement of FRC of Power Systems Considering Thermal Power Dynamic Conditions","authors":"Feng Hong;Yalei Pang;Weiming Ji;Lu Liang;Fang Fang;Junhong Hao;Jizhen Liu","doi":"10.17775/CSEEJPES.2023.04990","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.04990","url":null,"abstract":"Frequency stability and security have been a vital challenge as large-scale renewable energy is integrated into power systems. In contrast, the proportion of traditional thermal power units decreases during the decarbonization transformation process, resulting in poor frequency support. This paper aims to explore the potential of frequency regulation support, dynamic assessment, and capacity promotion of thermal power plants in the transition period. Considering the dynamic characteristics of the main steam working fluid under different working conditions, a nonlinear observer is constructed by extracting the main steam pressure and valve opening degree parameters. The real-time frequency modulation capacity of thermal power units can provide a dynamic state for the power grid. A dynamic adaptive modification for primary frequency control (PFC) of power systems, including wind power and thermal power, is proposed and improved. The power dynamic allocation factor is adaptively optimized by predicting the speed droop ratio, and the frequency modulation capability of the system is improved by more than 11% under extreme conditions. Finally, through the Monte Carlo simulation of unit states of the system under various working conditions, the promotion of the frequency regulation capacity with high wind power penetration (WPP) is verified.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 4","pages":"1371-1383"},"PeriodicalIF":6.9,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520152","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141966166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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