Pub Date : 2025-01-01DOI: 10.1109/TSTE.2024.3524720
Yi Wang;Goran Strbac
Large renewable penetration has been witnessed in power systems, resulting in reduced levels of system inertia and increasing requirements for frequency response services. There have been plenty of studies developing frequency-constrained models for power system security. However, most existing literature only considers uniform frequency security, while neglecting frequency spatial differences in different regions. To fill this gap, this paper proposes a novel planning model for the optimal sizing problem of power systems, capturing regional frequency security and inter-area frequency oscillations. Specifically, regional frequency constraints are first extracted via an enhanced input convex neural network (ICNN) and then embedded into the original optimisation for frequency security, where a principled weight initialisation strategy is adopted to deal with the gradient vanishing issues of non-negative weights in traditional ICNNs and enhance its fitting ability. An adaptive genetic algorithm with sparsity calculation and local search is developed to separate the planning model into two stages and effectively solve it iteratively. Case studies have been conducted on three different power systems to verify the effectiveness of the proposed frequency-constrained planning model in ensuring regional system security and obtaining realistic investment decisions.
{"title":"Regional Frequency-Constrained Planning for the Optimal Sizing of Power Systems via Enhanced Input Convex Neural Networks","authors":"Yi Wang;Goran Strbac","doi":"10.1109/TSTE.2024.3524720","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3524720","url":null,"abstract":"Large renewable penetration has been witnessed in power systems, resulting in reduced levels of system inertia and increasing requirements for frequency response services. There have been plenty of studies developing frequency-constrained models for power system security. However, most existing literature only considers uniform frequency security, while neglecting frequency spatial differences in different regions. To fill this gap, this paper proposes a novel planning model for the optimal sizing problem of power systems, capturing regional frequency security and inter-area frequency oscillations. Specifically, regional frequency constraints are first extracted via an enhanced input convex neural network (ICNN) and then embedded into the original optimisation for frequency security, where a principled weight initialisation strategy is adopted to deal with the gradient vanishing issues of non-negative weights in traditional ICNNs and enhance its fitting ability. An adaptive genetic algorithm with sparsity calculation and local search is developed to separate the planning model into two stages and effectively solve it iteratively. Case studies have been conducted on three different power systems to verify the effectiveness of the proposed frequency-constrained planning model in ensuring regional system security and obtaining realistic investment decisions.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1644-1658"},"PeriodicalIF":8.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331782","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 : 2024-12-26DOI: 10.1109/TSTE.2024.3522167
Haihan Ye;Wu Chen;Tao Li;Xingyu Liu;Guangyue Liu
This paper proposes a promising alternative for cost- effective high voltage direct current (HVDC) system that can realize the black start of offshore wind power plants (WPPs), active voltage build-up and harmonic suppression at the point of common coupling, AC fault ride-through and DC fault ride- through. A featured improvement is that the DC voltage reversal of the current source converter is fully explored and introduced into the offshore rectifier station (RS), based on which a special negative feedback is designed into the power circuit stage so that the short-circuit current under DC faults can be actively suppressed even in the absence of controls and protections. Comparing with the classic HVDC systems, the proposed system inherits the low-cost feature of the diode rectifier based HVDC system, but can remove the start-up cables and passive filters, and improve the performance under AC and DC faults. Finally, the feasibility of the analysis is demonstrated by simulation results.
{"title":"A Novel Cost-Effective HVDC System With Self Black-Start and Fault Ride-Through Capability","authors":"Haihan Ye;Wu Chen;Tao Li;Xingyu Liu;Guangyue Liu","doi":"10.1109/TSTE.2024.3522167","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3522167","url":null,"abstract":"This paper proposes a promising alternative for cost- effective high voltage direct current (HVDC) system that can realize the black start of offshore wind power plants (WPPs), active voltage build-up and harmonic suppression at the point of common coupling, AC fault ride-through and DC fault ride- through. A featured improvement is that the DC voltage reversal of the current source converter is fully explored and introduced into the offshore rectifier station (RS), based on which a special negative feedback is designed into the power circuit stage so that the short-circuit current under DC faults can be actively suppressed even in the absence of controls and protections. Comparing with the classic HVDC systems, the proposed system inherits the low-cost feature of the diode rectifier based HVDC system, but can remove the start-up cables and passive filters, and improve the performance under AC and DC faults. Finally, the feasibility of the analysis is demonstrated by simulation results.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1629-1643"},"PeriodicalIF":8.6,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329508","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 : 2024-12-25DOI: 10.1109/TSTE.2024.3521939
Zhipeng Yu;Jin Lin;Feng Liu;Jiarong Li;Yingtian Chi;Yonghua Song;Zhengwei Ren;Chengcheng Lu;Mengbo Ji
The further decarbonization of power systems with high renewable energy penetration faces the problem of inter-day intermittence of renewable energy sources (RES) and the seasonal imbalance between RES and load demand, due to the limited regulation ability of conventional units such as thermal generation. Regular solutions based on battery energy storage system (BESS) are too costly to be practical. To address issues above, hydrogen energy storage system (HESS) and ammonia energy storage system (AESS) are introduced to gradually replace thermal generation. Specifically, first, HESS and AESS are incorporated into the multi-stage capacity expansion planning (MSCEP) model with carbon emission reduction constraints. Yearly data with hourly time resolution are utilized for each stage to accurately describe the intermittence of RES. Then, an improved column generation (CG) with Dantzig-Wolfe decomposition (DWD) embedded solution approach is used to efficiently solve the large-scale MSCEP model. Finally, a real-life system in China is studied. The results indicate that the proposed method can guarantee high power supply reliability (PSR) under different renewable energy penetration levels, avoiding the low PSR problem that may be caused by the existing typical scenario-based method (TSM) under high penetration ($geq$30%). Moreover, HESS and AESS are essential to reduce the cost of decarbonization. Especially under the goal of carbon neutrality, the contribution of HESS and AESS in reducing levelized cost of energy (LCOE) reaches 12.28% and 14.59%, respectively, leading to a levelized cost of carbon reduction (LCOCr) of 998 RMB/t.
高可再生能源渗透率电力系统的进一步脱碳，面临着由于火力发电等常规机组调节能力有限，可再生能源的日间间歇性和可再生能源与负荷需求的季节性不平衡问题。基于电池储能系统（BESS）的常规解决方案成本过高，难以实现。为了解决上述问题，引入氢储能系统（HESS）和氨储能系统（AESS）逐步取代热发电。具体而言，首先将HESS和AESS纳入具有碳减排约束的多阶段产能扩张规划（MSCEP）模型。在此基础上，采用改进的柱生成（CG）和dantzigg - wolfe分解（DWD）嵌入式求解方法，有效求解大规模MSCEP模型。最后，研究了中国的一个现实系统。结果表明，本文提出的方法能够在不同可再生能源渗透水平下保证较高的供电可靠性（PSR），避免了现有典型基于场景的方法（TSM）在高渗透水平下可能导致的低PSR问题($geq$ 30%). Moreover, HESS and AESS are essential to reduce the cost of decarbonization. Especially under the goal of carbon neutrality, the contribution of HESS and AESS in reducing levelized cost of energy (LCOE) reaches 12.28% and 14.59%, respectively, leading to a levelized cost of carbon reduction (LCOCr) of 998 RMB/t.
{"title":"Joint Multi-Stage Planning of Renewable Generation, HESS, and AESS for Deeply Decarbonizing Power Systems With High-Penetration Renewables","authors":"Zhipeng Yu;Jin Lin;Feng Liu;Jiarong Li;Yingtian Chi;Yonghua Song;Zhengwei Ren;Chengcheng Lu;Mengbo Ji","doi":"10.1109/TSTE.2024.3521939","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3521939","url":null,"abstract":"The further decarbonization of power systems with high renewable energy penetration faces the problem of inter-day intermittence of renewable energy sources (RES) and the seasonal imbalance between RES and load demand, due to the limited regulation ability of conventional units such as thermal generation. Regular solutions based on battery energy storage system (BESS) are too costly to be practical. To address issues above, hydrogen energy storage system (HESS) and ammonia energy storage system (AESS) are introduced to gradually replace thermal generation. Specifically, first, HESS and AESS are incorporated into the multi-stage capacity expansion planning (MSCEP) model with carbon emission reduction constraints. Yearly data with hourly time resolution are utilized for each stage to accurately describe the intermittence of RES. Then, an improved column generation (CG) with Dantzig-Wolfe decomposition (DWD) embedded solution approach is used to efficiently solve the large-scale MSCEP model. Finally, a real-life system in China is studied. The results indicate that the proposed method can guarantee high power supply reliability (PSR) under different renewable energy penetration levels, avoiding the low PSR problem that may be caused by the existing typical scenario-based method (TSM) under high penetration (<inline-formula><tex-math>$geq$</tex-math></inline-formula>30%). Moreover, HESS and AESS are essential to reduce the cost of decarbonization. Especially under the goal of carbon neutrality, the contribution of HESS and AESS in reducing levelized cost of energy (LCOE) reaches 12.28% and 14.59%, respectively, leading to a levelized cost of carbon reduction (LCOCr) of 998 RMB/t.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1613-1628"},"PeriodicalIF":8.6,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331733","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}
The stability issue of high proportion variable renewable energy (VRE) when connected to the grid has become an important factor limiting the consumption of VRE and seriously threatening the stable operation of the power systems. However, there is still a lack of targeted discrimination theory and compensation mechanisms in areas where the stability margin undergoes drastic changes due to changes in the static operating point of the systems. To this end, based on the small signal stability analysis method, this paper proposes a vulnerable nodes localization method for the multiple grid-connected converter systems (MGCCS) that considers the dynamic response characteristics and static operating point offset of converters. Firstly, a frequency domain negative feedback model is established for MGCCS with passive busbars. Then the sensitivity function for the control parameters of active nodes and the quantitative indicators for identifying vulnerable nodes are derived. Finally, a comprehensive compensation scheme for both active nodes and passive busbars is proposed. Case analysis demonstrates that the proposed vulnerable nodes identification method and comprehensive compensation scheme offer substantial benefits in the realm of stability design and operation planning of MGCCS.
{"title":"Identification of Vulnerable Nodes and Sensitivity Analysis of Control Parameters for Multiple Grid-Connected Converter Systems","authors":"Zhenxiang Liu;Yanbo Chen;Zhi Zhang;Jiahao Ma;Tao Huang","doi":"10.1109/TSTE.2024.3521890","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3521890","url":null,"abstract":"The stability issue of high proportion variable renewable energy (VRE) when connected to the grid has become an important factor limiting the consumption of VRE and seriously threatening the stable operation of the power systems. However, there is still a lack of targeted discrimination theory and compensation mechanisms in areas where the stability margin undergoes drastic changes due to changes in the static operating point of the systems. To this end, based on the small signal stability analysis method, this paper proposes a vulnerable nodes localization method for the multiple grid-connected converter systems (MGCCS) that considers the dynamic response characteristics and static operating point offset of converters. Firstly, a frequency domain negative feedback model is established for MGCCS with passive busbars. Then the sensitivity function for the control parameters of active nodes and the quantitative indicators for identifying vulnerable nodes are derived. Finally, a comprehensive compensation scheme for both active nodes and passive busbars is proposed. Case analysis demonstrates that the proposed vulnerable nodes identification method and comprehensive compensation scheme offer substantial benefits in the realm of stability design and operation planning of MGCCS.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1602-1612"},"PeriodicalIF":8.6,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331744","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 : 2024-12-23DOI: 10.1109/TSTE.2024.3521384
Yongning Zhao;Shiji Pan;Yanxu Chen;Haohan Liao;Yingying Zheng;Lin Ye
The numerical weather prediction (NWP) is crucial to improve intraday wind power forecasting (WPF) accuracy. However, conventional WPF methods relied solely on a latest reported single NWP, overlooking hidden information from sequentially reported multiple historical NWPs that are partially overlapped over time. Additionally, it's challenging to tackle intraday WPF as it involves both ultra-short-term and short-term horizons with different characteristics. Therefore, a novel spatio-temporal representation learning network is proposed for intraday WPF by ensemble of overlapping historical NWPs. Initially, an integrated mask-reconstruction representation learning pretraining strategy is employed to extract hidden representations of historical wind power measurements and overlapping historical NWPs, providing contextual information for the subsequent intraday WPF task. Then, the output layer is trained and end-to-end fine-tuning of the entire network is conducted to adapt to the specific forecasting task. Moreover, a multi-task learning strategy based on hard parameter sharing is adopted to ensure balanced predictive accuracy across each of forecasted wind farms. Case study and detailed ablation tests based on 5 real-world wind farms demonstrate that the proposed method enhances the forecasting accuracy of most wind farms by leveraging spatio-temporal correlation, achieving the best average performance across all time horizons compared to the baseline models.
{"title":"Intraday Wind Power Forecasting by Ensemble of Overlapping Historical Numerical Weather Predictions","authors":"Yongning Zhao;Shiji Pan;Yanxu Chen;Haohan Liao;Yingying Zheng;Lin Ye","doi":"10.1109/TSTE.2024.3521384","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3521384","url":null,"abstract":"The numerical weather prediction (NWP) is crucial to improve intraday wind power forecasting (WPF) accuracy. However, conventional WPF methods relied solely on a latest reported single NWP, overlooking hidden information from sequentially reported multiple historical NWPs that are partially overlapped over time. Additionally, it's challenging to tackle intraday WPF as it involves both ultra-short-term and short-term horizons with different characteristics. Therefore, a novel spatio-temporal representation learning network is proposed for intraday WPF by ensemble of overlapping historical NWPs. Initially, an integrated mask-reconstruction representation learning pretraining strategy is employed to extract hidden representations of historical wind power measurements and overlapping historical NWPs, providing contextual information for the subsequent intraday WPF task. Then, the output layer is trained and end-to-end fine-tuning of the entire network is conducted to adapt to the specific forecasting task. Moreover, a multi-task learning strategy based on hard parameter sharing is adopted to ensure balanced predictive accuracy across each of forecasted wind farms. Case study and detailed ablation tests based on 5 real-world wind farms demonstrate that the proposed method enhances the forecasting accuracy of most wind farms by leveraging spatio-temporal correlation, achieving the best average performance across all time horizons compared to the baseline models.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 2","pages":"1315-1328"},"PeriodicalIF":8.6,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667508","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 : 2024-12-23DOI: 10.1109/TSTE.2024.3521509
Jinxin Ouyang;Jianfeng Yu;Shoudong Xu;Shuqi Bi
The operational states of wind turbines are different in large-scale wind farms, which presents serious challenges to the frequency control of power systems. The doubly fed induction generator-based wind turbine (DFIG) can be coordinated to participate in frequency control by altering the rotational kinetic energy. The coordinated control of wind farms is usually conditioned by the accurate assessment of the power support capability (PSC) of DFIG. However, the assessment mainly focuses on the influence of single variables such as wind speed and rotor speed. The coupling constraints of rotor speed, pitch angle and rotor current on the PSC are ignored. The PSC of wind farms is still difficult to accurately assess and fully utilize. Therefore, the power characteristics of DFIG under dynamic variations of mechanical power are analyzed. The PSC of DFIG considering the coupling constraints of multi-state variables is modeled. Then the assessment method of PSC considering the coupling constraints of rotor speed, pitch angle and rotor current is proposed. The allocation method of the contribution of DFIG considering different operational states of DFIG is proposed, and the frequency coordinated control method of DFIG-based wind farm is proposed. The effectiveness of the proposed method is verified by case studies.
{"title":"Modeling of Power Support Capability and Frequency Coordinated Control of DFIG-Based Wind Farm Considering Coupling Constraints of Multi-State Variables","authors":"Jinxin Ouyang;Jianfeng Yu;Shoudong Xu;Shuqi Bi","doi":"10.1109/TSTE.2024.3521509","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3521509","url":null,"abstract":"The operational states of wind turbines are different in large-scale wind farms, which presents serious challenges to the frequency control of power systems. The doubly fed induction generator-based wind turbine (DFIG) can be coordinated to participate in frequency control by altering the rotational kinetic energy. The coordinated control of wind farms is usually conditioned by the accurate assessment of the power support capability (PSC) of DFIG. However, the assessment mainly focuses on the influence of single variables such as wind speed and rotor speed. The coupling constraints of rotor speed, pitch angle and rotor current on the PSC are ignored. The PSC of wind farms is still difficult to accurately assess and fully utilize. Therefore, the power characteristics of DFIG under dynamic variations of mechanical power are analyzed. The PSC of DFIG considering the coupling constraints of multi-state variables is modeled. Then the assessment method of PSC considering the coupling constraints of rotor speed, pitch angle and rotor current is proposed. The allocation method of the contribution of DFIG considering different operational states of DFIG is proposed, and the frequency coordinated control method of DFIG-based wind farm is proposed. The effectiveness of the proposed method is verified by case studies.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1589-1601"},"PeriodicalIF":8.6,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329504","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 : 2024-12-20DOI: 10.1109/TSTE.2024.3520989
Huazhao Ding;Rabi Kar;Zhixin Miao;Lingling Fan
This paper presents the design of a novel grid-forming (GFM) control structure adapted from a typical grid-following (GFL) control structure with minimal edits, thereby enabling a switchable control structure for voltage sourced converters (VSCs) to operate in either GFL or GFM mode by simply switching a flag manually. The VSC is shown to be able to operate in the GFL control mode synchronizing to the main grid through a phase-locked-loop (PLL) and operate as a GFM controller with power-based synchronization for both grid-connected and islanded conditions. To guarantee smooth operation, the control schemes and the mode switching logic have been carefully designed and examined via a series of experiments. The experiment results show that the switchable control structure can fulfill the desired control and operation functions and enable smooth transition between control modes.
{"title":"A Novel Design for Switchable Grid-Following and Grid-Forming Control","authors":"Huazhao Ding;Rabi Kar;Zhixin Miao;Lingling Fan","doi":"10.1109/TSTE.2024.3520989","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3520989","url":null,"abstract":"This paper presents the design of a novel grid-forming (GFM) control structure adapted from a typical grid-following (GFL) control structure with minimal edits, thereby enabling a switchable control structure for voltage sourced converters (VSCs) to operate in either GFL or GFM mode by simply switching a flag manually. The VSC is shown to be able to operate in the GFL control mode synchronizing to the main grid through a phase-locked-loop (PLL) and operate as a GFM controller with power-based synchronization for both grid-connected and islanded conditions. To guarantee smooth operation, the control schemes and the mode switching logic have been carefully designed and examined via a series of experiments. The experiment results show that the switchable control structure can fulfill the desired control and operation functions and enable smooth transition between control modes.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 2","pages":"1301-1314"},"PeriodicalIF":8.6,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667490","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 focuses on the optimized and coordinated operation of a hybrid system comprising wind turbines, a hydrogen electrolyzer, and hydrogen storage. A day-ahead optimized schedule is developed for the hybrid wind-hydrogen system to provide flexibility in meeting the transmission system operator's needs, offering frequency control support through frequency containment reserves (FCR) and managing congestion on nearby transmission lines. The proposed operation strategy enables effective participation in three reserve markets (FCR-N, upward, and downward FCR-D) while robustly managing uncertainties in wind power forecasting by leveraging the flexibility of the hydrogen electrolyzer and hydrogen storage. Utilizing historical data on FCR activation during normal grid operation and disturbances, this strategy robustly addresses frequency-driven uncertainties. The effectiveness of the proposed method is demonstrated through two case studies using real-world data on frequency deviations and market prices in Finland. Additionally, the proposed strategy is compared with two alternative approaches: one based on spot market prices and another prioritizing self-sufficiency over financial gains.
{"title":"Optimized Operation of Hybrid Wind-Hydrogen System to Provide Flexibility for Transmission System Needs","authors":"Hosna Khajeh;Sahar Seyyedeh-Barhagh;Hannu Laaksonen","doi":"10.1109/TSTE.2024.3519953","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3519953","url":null,"abstract":"This paper focuses on the optimized and coordinated operation of a hybrid system comprising wind turbines, a hydrogen electrolyzer, and hydrogen storage. A day-ahead optimized schedule is developed for the hybrid wind-hydrogen system to provide flexibility in meeting the transmission system operator's needs, offering frequency control support through frequency containment reserves (FCR) and managing congestion on nearby transmission lines. The proposed operation strategy enables effective participation in three reserve markets (FCR-N, upward, and downward FCR-D) while robustly managing uncertainties in wind power forecasting by leveraging the flexibility of the hydrogen electrolyzer and hydrogen storage. Utilizing historical data on FCR activation during normal grid operation and disturbances, this strategy robustly addresses frequency-driven uncertainties. The effectiveness of the proposed method is demonstrated through two case studies using real-world data on frequency deviations and market prices in Finland. Additionally, the proposed strategy is compared with two alternative approaches: one based on spot market prices and another prioritizing self-sufficiency over financial gains.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1576-1588"},"PeriodicalIF":8.6,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10806878","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331700","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 : 2024-12-18DOI: 10.1109/TSTE.2024.3519721
Yi-Hua Liu;Yu-Shan Cheng;Yu-Chih Huang
When the photovoltaic generation system (PVGS) operates under partially shaded conditions (PSC), its output power versus voltage (P-V) characteristic curve becomes multimodal, which complicates the search for the global maximum power point (GMPP). This paper proposes a GMPP tracking (GMPPT) method based on machine learning (ML). In the first stage, the regression tree (RT) is used to predict the approximate location of the GMPP. In the second stage, the α-perturb and observe (α-P&O) method is used to obtain the precise GMPP. This study first establishes a PVGS simulation platform and generates the training data required for RT, then optimizes the obtained RT and integrates it into the simulation platform. Finally, this paper compares the proposed method with the state-of-the-art approaches. It can be seen from the results that the proposed method has an average tracking power loss of 2.13 W and an average tracking time of 0.11 seconds under 252 different shading patterns (SPs). It can correctly identify 244 intervals where the exact GMPP is located among the 252 test SPs. The experimental results show that the proposed method outperforms 5 state-of-the-art approaches in terms of tracking accuracy and tracking time under three shading patterns, thus confirming its excellence.
{"title":"A Machine Learning-Based Global Maximum Power Point Tracking Technique for a Photovoltaic Generation System Under Complicated Partially Shaded Conditions","authors":"Yi-Hua Liu;Yu-Shan Cheng;Yu-Chih Huang","doi":"10.1109/TSTE.2024.3519721","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3519721","url":null,"abstract":"When the photovoltaic generation system (PVGS) operates under partially shaded conditions (PSC), its output power versus voltage (P-V) characteristic curve becomes multimodal, which complicates the search for the global maximum power point (GMPP). This paper proposes a GMPP tracking (GMPPT) method based on machine learning (ML). In the first stage, the regression tree (RT) is used to predict the approximate location of the GMPP. In the second stage, the α-perturb and observe (α-P&O) method is used to obtain the precise GMPP. This study first establishes a PVGS simulation platform and generates the training data required for RT, then optimizes the obtained RT and integrates it into the simulation platform. Finally, this paper compares the proposed method with the state-of-the-art approaches. It can be seen from the results that the proposed method has an average tracking power loss of 2.13 W and an average tracking time of 0.11 seconds under 252 different shading patterns (SPs). It can correctly identify 244 intervals where the exact GMPP is located among the 252 test SPs. The experimental results show that the proposed method outperforms 5 state-of-the-art approaches in terms of tracking accuracy and tracking time under three shading patterns, thus confirming its excellence.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 3","pages":"1562-1575"},"PeriodicalIF":8.6,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331554","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}
The existing rotor current control methods, despite achieving simultaneous control on the positive and negative sequence rotor currents for the doubly-fed induction generator (DFIG)-based wind turbine, are still facing challenges. Specifically, some works introduce the sequence current decomposition into the classical control structure, which can deteriorate the dynamic performance. While others with high-order regulator embedded into the classical control structure can increase the risk of instability. To this end, this paper proposes a novel current reference transformation-based positive and negative sequence rotor current control method. Firstly, the negative sequence response of the DFIG under the classical single dq-PI rotor current control method is studied, pointing out its satisfactory dynamic performance but poor steady-state performance. Based on which, a transformation formula for the negative sequence rotor current reference is analytically derived to compensate for the steady-state performance. The corresponding analysis indicates that negative sequence rotor current static errors from parameter deviations can be well limited. Comparative simulations illustrated an improved dynamic performance and stability of the DFIG rotor current control with the proposed method. The experimental test of a prototype DFIG system has also been conducted to verify the feasibility of the proposed method in practical implementation.
{"title":"A Novel Current Reference Transformation-Based Positive and Negative Sequence Rotor Current Control Method of DFIGs","authors":"Xuesong Gao;Shiyao Qin;Xianzhuo Sun;Zhihao Wang;Rongde Cui;Shuai Xu;Lei Ding","doi":"10.1109/TSTE.2024.3520182","DOIUrl":"https://doi.org/10.1109/TSTE.2024.3520182","url":null,"abstract":"The existing rotor current control methods, despite achieving simultaneous control on the positive and negative sequence rotor currents for the doubly-fed induction generator (DFIG)-based wind turbine, are still facing challenges. Specifically, some works introduce the sequence current decomposition into the classical control structure, which can deteriorate the dynamic performance. While others with high-order regulator embedded into the classical control structure can increase the risk of instability. To this end, this paper proposes a novel current reference transformation-based positive and negative sequence rotor current control method. Firstly, the negative sequence response of the DFIG under the classical single dq-PI rotor current control method is studied, pointing out its satisfactory dynamic performance but poor steady-state performance. Based on which, a transformation formula for the negative sequence rotor current reference is analytically derived to compensate for the steady-state performance. The corresponding analysis indicates that negative sequence rotor current static errors from parameter deviations can be well limited. Comparative simulations illustrated an improved dynamic performance and stability of the DFIG rotor current control with the proposed method. The experimental test of a prototype DFIG system has also been conducted to verify the feasibility of the proposed method in practical implementation.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 2","pages":"1283-1300"},"PeriodicalIF":8.6,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143667240","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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