Pub Date : 2024-07-17DOI: 10.1109/TSTE.2024.3429781
Xueqian Fu;Chunyu Zhang;Xiurong Zhang;Hongbin Sun
The stochastic production simulation of photovoltaic (PV) power is crucial for the analysis of power balance in power planning, annual or monthly operational planning, and long-term transactions in the electricity market, especially in power systems with a high share of PVs. To model the uncertainty and temporal characteristics inherent in PV power, this letter introduces the style transfer and innovatively establishes bi-directional long short-term memory generative adversarial networks (GAN). Simulation results confirm the advantages of the proposed GAN over traditional convolutional neural network-based GANs in simulating the diversity and temporal characteristics of PV power.
光伏（PV）电力的随机生产模拟对于电力规划中的电力平衡分析、年度或月度运营规划以及电力市场中的长期交易至关重要，尤其是在光伏占比较高的电力系统中。为模拟光伏发电固有的不确定性和时间特性，本文引入了样式转移，并创新性地建立了双向长短期记忆生成式对抗网络（GAN）。仿真结果证实，与传统的基于卷积神经网络的 GAN 相比，所提出的 GAN 在模拟光伏发电的多样性和时间特性方面更具优势。
{"title":"A Novel GAN Architecture Reconstructed Using Bi-LSTM and Style Transfer for PV Temporal Dynamics Simulation","authors":"Xueqian Fu;Chunyu Zhang;Xiurong Zhang;Hongbin Sun","doi":"10.1109/TSTE.2024.3429781","DOIUrl":"10.1109/TSTE.2024.3429781","url":null,"abstract":"The stochastic production simulation of photovoltaic (PV) power is crucial for the analysis of power balance in power planning, annual or monthly operational planning, and long-term transactions in the electricity market, especially in power systems with a high share of PVs. To model the uncertainty and temporal characteristics inherent in PV power, this letter introduces the style transfer and innovatively establishes bi-directional long short-term memory generative adversarial networks (GAN). Simulation results confirm the advantages of the proposed GAN over traditional convolutional neural network-based GANs in simulating the diversity and temporal characteristics of PV power.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2826-2829"},"PeriodicalIF":8.6,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141740424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Synchronous condensers (SynCons) are widely used in supporting the integration of renewable power plants (RPPs) in weak grids. However, recent research suggests that a SynCon co-located with RPPs may be prone to transient rotor angle instability due to the excessive active power injected by nearby RPPs during metallic faults. This paper further discovers that the transient stability of the SynCon may be lost even it generates electrical power during high-resistance faults. This novel mechanism of instability is investigated by deriving power-angle characteristics in different fault scenarios, and then the effect of the system parameters on the stability is analyzed via a proposed index based on the critical clearance time (CCT). It reveals that inappropriate parameters of SynCons, weak grid, and voltage support during fault ride-through (FRT) all contribute to such transient instability. To mitigate such instability, an adaptive FRT strategy is proposed. The electromagnetic transient (EMT) simulations based on the PSCAD are carried out to validate the effectiveness of the theoretical analysis and the proposed adaptive control strategy.
{"title":"Transient Stability of Synchronous Condenser Co-Located With Renewable Power Plants Under High-Resistance Faults and Risk Mitigation","authors":"Xinyu Liu;Huanhai Xin;Yongpeng Shan;Di Zheng;Dong Chen","doi":"10.1109/TSTE.2024.3429210","DOIUrl":"10.1109/TSTE.2024.3429210","url":null,"abstract":"Synchronous condensers (SynCons) are widely used in supporting the integration of renewable power plants (RPPs) in weak grids. However, recent research suggests that a SynCon co-located with RPPs may be prone to transient rotor angle instability due to the excessive active power injected by nearby RPPs during metallic faults. This paper further discovers that the transient stability of the SynCon may be lost even it generates electrical power during high-resistance faults. This novel mechanism of instability is investigated by deriving power-angle characteristics in different fault scenarios, and then the effect of the system parameters on the stability is analyzed via a proposed index based on the critical clearance time (CCT). It reveals that inappropriate parameters of SynCons, weak grid, and voltage support during fault ride-through (FRT) all contribute to such transient instability. To mitigate such instability, an adaptive FRT strategy is proposed. The electromagnetic transient (EMT) simulations based on the PSCAD are carried out to validate the effectiveness of the theoretical analysis and the proposed adaptive control strategy.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2581-2593"},"PeriodicalIF":8.6,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141718532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-07-16DOI: 10.1109/tste.2024.3429152
Xuesong Gao, Zhihao Wang, Xianzhuo Sun, Lei Ding
{"title":"Reduced-dimensional Controllable Region-Assisted Optimal Rotor Current Control Strategy of DFIG-based WTGs during Asymmetrical Faults","authors":"Xuesong Gao, Zhihao Wang, Xianzhuo Sun, Lei Ding","doi":"10.1109/tste.2024.3429152","DOIUrl":"https://doi.org/10.1109/tste.2024.3429152","url":null,"abstract":"","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"30 1","pages":""},"PeriodicalIF":8.8,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141718612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-07-16DOI: 10.1109/TSTE.2024.3429310
Zhuoxin Lu;Xiaoyuan Xu;Zheng Yan;Mohammad Shahidehpour;Weiqing Sun;Dong Han
This paper proposes a pricing and scheduling method for shared mobile energy storage systems (SMSs) in coupled power distribution and transportation networks. Different from existing shared energy storage studies, which mostly focus on stationary resources, the paper investigates the SMS operation considering the negotiation of rental prices as well as mobility and charging/discharging among SMS owners and different users. Specifically, the SMS pricing and scheduling with variable renewable energy are established as a bilevel mixed-integer chance-constrained distributionally robust optimization problem. In the upper-level problem, the SMS owner determines pricing and day-ahead mobility strategy to maximize its payoff. In the lower-level problem, the SMS users, i.e., distribution grid operators, determine the SMS charging/discharging power according to the SMS day-ahead pricing results and intra-day distribution grid operation strategies for accommodating variable renewable energy. The distributionally robust chance constraint is designed to cope with the intra-day operational risk caused by the variability of renewable power generation. To cope with the solution difficulty in the proposed bilevel optimization problem, the chance constraint is reformulated as second-order cone constraints, which are further transformed into a set of linear constraints, and then the reformulated bilevel mixed-integer linear programming problem is decomposed and iteratively solved to avoid enumerating lower-level integer variables. Simulation results show that the utilization rate of SMS batteries is increased and the excess renewable power is fully consumed when SMSs are shared among different distribution grids. The proposed distributionally robust optimization achieves higher revenue for the SMS owner and smaller operating costs of distribution grids than robust optimization under uncertain environments.
{"title":"Distributionally Robust Chance Constrained Optimization Method for Risk-Based Routing and Scheduling of Shared Mobile Energy Storage System With Variable Renewable Energy","authors":"Zhuoxin Lu;Xiaoyuan Xu;Zheng Yan;Mohammad Shahidehpour;Weiqing Sun;Dong Han","doi":"10.1109/TSTE.2024.3429310","DOIUrl":"10.1109/TSTE.2024.3429310","url":null,"abstract":"This paper proposes a pricing and scheduling method for shared mobile energy storage systems (SMSs) in coupled power distribution and transportation networks. Different from existing shared energy storage studies, which mostly focus on stationary resources, the paper investigates the SMS operation considering the negotiation of rental prices as well as mobility and charging/discharging among SMS owners and different users. Specifically, the SMS pricing and scheduling with variable renewable energy are established as a bilevel mixed-integer chance-constrained distributionally robust optimization problem. In the upper-level problem, the SMS owner determines pricing and day-ahead mobility strategy to maximize its payoff. In the lower-level problem, the SMS users, i.e., distribution grid operators, determine the SMS charging/discharging power according to the SMS day-ahead pricing results and intra-day distribution grid operation strategies for accommodating variable renewable energy. The distributionally robust chance constraint is designed to cope with the intra-day operational risk caused by the variability of renewable power generation. To cope with the solution difficulty in the proposed bilevel optimization problem, the chance constraint is reformulated as second-order cone constraints, which are further transformed into a set of linear constraints, and then the reformulated bilevel mixed-integer linear programming problem is decomposed and iteratively solved to avoid enumerating lower-level integer variables. Simulation results show that the utilization rate of SMS batteries is increased and the excess renewable power is fully consumed when SMSs are shared among different distribution grids. The proposed distributionally robust optimization achieves higher revenue for the SMS owner and smaller operating costs of distribution grids than robust optimization under uncertain environments.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2594-2608"},"PeriodicalIF":8.6,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141722228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-07-12DOI: 10.1109/TSTE.2024.3426917
Pavlos G. Papageorgiou;Panagiotis T. Papafilippou;Konstantinos O. Oureilidis;Georgios C. Christoforidis
The volatility of grid-coupled photovoltaics can cause local voltage deviations, while the impact on frequency becomes obvious in isolated weak grids. Thus, a standalone battery is usually proposed for smoothing purposes. However, the frequent cycles and abrupt power variations shrink its life and impair control performance. To this end, this study introduces a controller for a hybrid system composed of a superconducting magnetic energy storage (SMES) and a battery. The proposed method establishes an idling zone for battery to eliminate its short-term activity, while SMES handles any power mismatch. The zone limits are dynamically adjusted in case of power balance detection, while an adaptive saturation is applied to them for maximal SMES utilization and minimal battery degradation. When SMES current deviates from this zone, battery operates with an adaptive ramp rate (i.e., di/dt) depending on the state of charge of SMES, to further optimize its life. Additionally, to prevent unnecessary power circulation among SMES and battery, supervisory control loops are implemented. Finally, to evaluate this scheme against preceding controllers regarding battery life extension, a real-time approach is followed using a dedicated simulator, while a hardware-in-the-loop verification is presented using an actual controller.
{"title":"An Adaptive Controller of a Hybrid Storage System for Power Smoothing With Enlarged Battery Lifetime","authors":"Pavlos G. Papageorgiou;Panagiotis T. Papafilippou;Konstantinos O. Oureilidis;Georgios C. Christoforidis","doi":"10.1109/TSTE.2024.3426917","DOIUrl":"10.1109/TSTE.2024.3426917","url":null,"abstract":"The volatility of grid-coupled photovoltaics can cause local voltage deviations, while the impact on frequency becomes obvious in isolated weak grids. Thus, a standalone battery is usually proposed for smoothing purposes. However, the frequent cycles and abrupt power variations shrink its life and impair control performance. To this end, this study introduces a controller for a hybrid system composed of a superconducting magnetic energy storage (SMES) and a battery. The proposed method establishes an idling zone for battery to eliminate its short-term activity, while SMES handles any power mismatch. The zone limits are dynamically adjusted in case of power balance detection, while an adaptive saturation is applied to them for maximal SMES utilization and minimal battery degradation. When SMES current deviates from this zone, battery operates with an adaptive ramp rate (i.e., di/dt) depending on the state of charge of SMES, to further optimize its life. Additionally, to prevent unnecessary power circulation among SMES and battery, supervisory control loops are implemented. Finally, to evaluate this scheme against preceding controllers regarding battery life extension, a real-time approach is followed using a dedicated simulator, while a hardware-in-the-loop verification is presented using an actual controller.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2567-2580"},"PeriodicalIF":8.6,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141614652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-07-10DOI: 10.1109/TSTE.2024.3426337
Xianbang Chen;Yikui Liu;Lei Wu
Generally, day-ahead unit commitment (UC) is conducted in a predict-then-optimize process: it starts by predicting the renewable energy source (RES) availability and system reserve requirements; given the predictions, the UC model is then optimized to determine the economic operation plans. In fact, predictions within the process are raw . In other words, if the predictions are further tailored to assist UC in making the economic operation plans against realizations of the RES and reserve requirements, UC economics will benefit significantly. To this end, this paper presents a cost-oriented tailor of RES-and-reserve predictions for UC, deployed as an add-on to the predict-then-optimize process. The RES-and-reserve tailor is trained by solving a bi-level mixed-integer programming model: the upper level trains the tailor based on its induced operating cost; the lower level, given tailored predictions, mimics the system operation process and feeds the induced operating cost back to the upper level; finally, the upper level evaluates the training quality according to the fed-back cost. Through this training, the tailor learns to customize the raw predictions into cost-oriented predictions. Moreover, the tailor can be embedded into the existing predict-then-optimize process as an add-on, improving the UC economics. Lastly, the presented method is compared to traditional, binary-relaxing, neural network-based, stochastic, and robust methods.
{"title":"Towards Improving Unit Commitment Economics: An Add-On Tailor for Renewable Energy and Reserve Predictions","authors":"Xianbang Chen;Yikui Liu;Lei Wu","doi":"10.1109/TSTE.2024.3426337","DOIUrl":"10.1109/TSTE.2024.3426337","url":null,"abstract":"Generally, day-ahead unit commitment (UC) is conducted in a predict-then-optimize process: it starts by predicting the renewable energy source (RES) availability and system reserve requirements; given the predictions, the UC model is then optimized to determine the economic operation plans. In fact, predictions within the process are \u0000<italic>raw</i>\u0000. In other words, if the predictions are further tailored to assist UC in making the economic operation plans against realizations of the RES and reserve requirements, UC economics will benefit significantly. To this end, this paper presents a cost-oriented tailor of RES-and-reserve predictions for UC, deployed as an add-on to the predict-then-optimize process. The RES-and-reserve tailor is trained by solving a bi-level mixed-integer programming model: the upper level trains the tailor based on its induced operating cost; the lower level, given tailored predictions, mimics the system operation process and feeds the induced operating cost back to the upper level; finally, the upper level evaluates the training quality according to the fed-back cost. Through this training, the tailor learns to customize the raw predictions into cost-oriented predictions. Moreover, the tailor can be embedded into the existing predict-then-optimize process as an add-on, improving the UC economics. Lastly, the presented method is compared to traditional, binary-relaxing, neural network-based, stochastic, and robust methods.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2547-2566"},"PeriodicalIF":8.6,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141587066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper introduces a model-free control strategy utilizing reinforcement learning (RL) to improve the electrical power generation of a point absorber wave energy converter (WEC). While model-based methods may suffer from control performance degradation due to modeling errors, such as inherent Coulomb-type friction, RL-based approaches are well-suited for the WEC environment, where system dynamics are complex or unknown. The strength lies in their ability to learn from interactions with the environment, bypassing the necessity for precise models. To enhance the control performance in electrical power generation, a control-oriented loss model is established, and a force penalty term is introduced into the reward function to avoid the WEC system operating in high-loss, low-efficiency regions. To further eliminate the reliance on wave information and improve applicability, an analysis is conducted to examine the contribution of each state feature to the training outcomes and a loss-considering and wave information-independent RL-based control scheme is developed. The RL-based controller is further validated on a point absorber WEC prototype in the wave tank experiment, demonstrating effective implementation and commendable performance in both regular and irregular waves.
{"title":"Design and Tank Testing of Reinforcement Learning Control for Wave Energy Converters","authors":"Kemeng Chen;Xuanrui Huang;Zechuan Lin;Yifei Han;Xi Xiao","doi":"10.1109/TSTE.2024.3425838","DOIUrl":"10.1109/TSTE.2024.3425838","url":null,"abstract":"This paper introduces a model-free control strategy utilizing reinforcement learning (RL) to improve the electrical power generation of a point absorber wave energy converter (WEC). While model-based methods may suffer from control performance degradation due to modeling errors, such as inherent Coulomb-type friction, RL-based approaches are well-suited for the WEC environment, where system dynamics are complex or unknown. The strength lies in their ability to learn from interactions with the environment, bypassing the necessity for precise models. To enhance the control performance in electrical power generation, a control-oriented loss model is established, and a force penalty term is introduced into the reward function to avoid the WEC system operating in high-loss, low-efficiency regions. To further eliminate the reliance on wave information and improve applicability, an analysis is conducted to examine the contribution of each state feature to the training outcomes and a loss-considering and wave information-independent RL-based control scheme is developed. The RL-based controller is further validated on a point absorber WEC prototype in the wave tank experiment, demonstrating effective implementation and commendable performance in both regular and irregular waves.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2534-2546"},"PeriodicalIF":8.6,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141588594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-07-08DOI: 10.1109/TSTE.2024.3424731
Dalia Yousri;Hany E. Z. Farag;Hatem Zeineldin;Ahmed Al-Durra;Ehab El-Saadany
The proliferation of unbalanced linear and nonlinear loads in microgrids degrades the voltage quality at the inverter terminals, and thus, load terminals receive unbalanced and distorted voltages. To alleviate these voltage quality issues, this paper proposes a per-phase unsymmetrical adaptive derivative optimized droop control scheme for unbalanced islanded microgrids (UIMG). The proposed controller is coupled with a per-phase unsymmetrical virtual impedance (UVI) to mitigate the unbalance of the inverter-based UIMG. Additionally, a proportional multi-resonant (PMR) controller is adopted to compensate for the voltage distortion. To improve the UIMG dynamics response while changing the loading states, derivative terms of active and reactive powers are added to the proposed control. The derivative gains are adaptively updated with the change in the microgrid loading to achieve the desired transient response. The proposed scheme is formulated as a multi-objective optimization problem to determine the per-phase unsymmetrical droop settings and UVI that fit different loading states simultaneously. Several case studies are designed to test the effectiveness of the proposed control scheme under different types of disturbances and operating conditions. The cases are conducted on the IEEE 34-bus benchmark power distribution feeder with a combination of unbalanced linear and nonlinear loads. Moreover, the proposed control is validated using real-time simulations carried out in OPAL-RT system. The results show that the proposed control scheme is capable of mitigating voltage quality issues by reducing the voltage unbalance factor and voltage distortion.
{"title":"Per-Phase Unsymmetrical Adaptive Derivative Optimized Droop for Mitigating Voltage Quality Issues of Unbalanced Islanded Microgrids","authors":"Dalia Yousri;Hany E. Z. Farag;Hatem Zeineldin;Ahmed Al-Durra;Ehab El-Saadany","doi":"10.1109/TSTE.2024.3424731","DOIUrl":"10.1109/TSTE.2024.3424731","url":null,"abstract":"The proliferation of unbalanced linear and nonlinear loads in microgrids degrades the voltage quality at the inverter terminals, and thus, load terminals receive unbalanced and distorted voltages. To alleviate these voltage quality issues, this paper proposes a per-phase unsymmetrical adaptive derivative optimized droop control scheme for unbalanced islanded microgrids (UIMG). The proposed controller is coupled with a per-phase unsymmetrical virtual impedance (UVI) to mitigate the unbalance of the inverter-based UIMG. Additionally, a proportional multi-resonant (PMR) controller is adopted to compensate for the voltage distortion. To improve the UIMG dynamics response while changing the loading states, derivative terms of active and reactive powers are added to the proposed control. The derivative gains are adaptively updated with the change in the microgrid loading to achieve the desired transient response. The proposed scheme is formulated as a multi-objective optimization problem to determine the per-phase unsymmetrical droop settings and UVI that fit different loading states simultaneously. Several case studies are designed to test the effectiveness of the proposed control scheme under different types of disturbances and operating conditions. The cases are conducted on the IEEE 34-bus benchmark power distribution feeder with a combination of unbalanced linear and nonlinear loads. Moreover, the proposed control is validated using real-time simulations carried out in OPAL-RT system. The results show that the proposed control scheme is capable of mitigating voltage quality issues by reducing the voltage unbalance factor and voltage distortion.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2518-2533"},"PeriodicalIF":8.6,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10589303","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141569938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-07-08DOI: 10.1109/TSTE.2024.3424405
Ali Azizi;Ali Hooshyar
Grid-forming (GFM) inverters are controlled to directly regulate the voltage. A major challenge stemming from this control model is that sustaining the voltage during faults would require high currents—beyond the levels that an inverter can withstand. Various fault current limiting (FCL) methods have been developed in recent years for GFM inverter-based resources (IBRs). The theoretical analysis supported by detailed simulation studies in Part I of this paper investigates whether existing FCL methods for GFM inverters can be deemed feasible solutions for future IBR-centric power grids. The challenges revealed for the first time in this paper are multifaceted and depend on the type of the FCL method. The focus is not only on a GFM inverter's internal operation, but also on its impact on the grid and the practical requirements for grid integration of an IBR considering most recent grid codes. Part II of this paper will address these challenges.
{"title":"Fault Current Limiting and Grid Code Compliance for Grid-Forming Inverters—Part I: Problem Statement","authors":"Ali Azizi;Ali Hooshyar","doi":"10.1109/TSTE.2024.3424405","DOIUrl":"10.1109/TSTE.2024.3424405","url":null,"abstract":"Grid-forming (GFM) inverters are controlled to directly regulate the voltage. A major challenge stemming from this control model is that sustaining the voltage during faults would require high currents—beyond the levels that an inverter can withstand. Various fault current limiting (FCL) methods have been developed in recent years for GFM inverter-based resources (IBRs). The theoretical analysis supported by detailed simulation studies in Part I of this paper investigates whether existing FCL methods for GFM inverters can be deemed feasible solutions for future IBR-centric power grids. The challenges revealed for the first time in this paper are multifaceted and depend on the type of the FCL method. The focus is not only on a GFM inverter's internal operation, but also on its impact on the grid and the practical requirements for grid integration of an IBR considering most recent grid codes. Part II of this paper will address these challenges.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2486-2499"},"PeriodicalIF":8.6,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141569936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-07-08DOI: 10.1109/TSTE.2024.3424389
Ali Azizi;Ali Hooshyar
Part I of this paper unveiled various shortcomings of existing fault current limiting (FCL) methods for grid-forming (GFM) inverters. Part II of this paper develops a new FCL method that overcomes these drawbacks. Additionally, the FCL method proposed in this paper follows the strict requirements of recent grid codes for the low-voltage ride-through mode of inverter-based resources (IBRs). This makes the exact response of GFM inverters during faults fully predictable. Such predictability is a prerequisite for the reliable design/setting of protection systems, operation, and planning of power grids with high penetration of IBRs. The paper uses PSCAD simulations to corroborate if the proposed method meets these objectives. It also uses simulation results to compare this new method with existing FCL solutions for GFM inverters.
{"title":"Fault Current Limiting and Grid Code Compliance for Grid-Forming Inverters — Part II: Solution","authors":"Ali Azizi;Ali Hooshyar","doi":"10.1109/TSTE.2024.3424389","DOIUrl":"10.1109/TSTE.2024.3424389","url":null,"abstract":"Part I of this paper unveiled various shortcomings of existing fault current limiting (FCL) methods for grid-forming (GFM) inverters. Part II of this paper develops a new FCL method that overcomes these drawbacks. Additionally, the FCL method proposed in this paper follows the strict requirements of recent grid codes for the low-voltage ride-through mode of inverter-based resources (IBRs). This makes the exact response of GFM inverters during faults fully predictable. Such predictability is a prerequisite for the reliable design/setting of protection systems, operation, and planning of power grids with high penetration of IBRs. The paper uses PSCAD simulations to corroborate if the proposed method meets these objectives. It also uses simulation results to compare this new method with existing FCL solutions for GFM inverters.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2500-2517"},"PeriodicalIF":8.6,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141569937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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