Pub Date : 2025-08-01DOI: 10.1016/j.gloei.2025.04.005
Konstantin Suslov , Andrey Kryukov , Aleksandr Cherepanov , Andrey Batukhtin , Yanhong. Luo
Modern electric traction networks (ETN) are equipped with automated systems for commercial accounting of power consumption (ASCAPC), which allows solving properly the problems of enhancing the energy efficiency of transportation processes. Energy efficiency of ETNs is defined as the amount of power losses in ETN components: overhead catenary systems and traction transformers. Due to the instability of traction loads and changes in their location in space, the electric traction network is different from the general network. It is necessary to develop an approach for loss analysis in traction networks and in transformers of traction substations. To solve this problem, a balance-based technique for power loss calculation in traction networks based on ASCAPC data is proposed. First, the balance-based technique presented here breaks down the power consumption of the train by source. Then, calculates technical power losses in 25 and 2 × 25 kV traction networks as well as in traction transformers. Last, the technique is implemented in the form of an algorithm tested on real-life data and it is ready for practical use.
{"title":"A novel balance method for determining the energy efficiency of electric traction networks","authors":"Konstantin Suslov , Andrey Kryukov , Aleksandr Cherepanov , Andrey Batukhtin , Yanhong. Luo","doi":"10.1016/j.gloei.2025.04.005","DOIUrl":"10.1016/j.gloei.2025.04.005","url":null,"abstract":"<div><div>Modern electric traction networks (ETN) are equipped with automated systems for commercial accounting of power consumption (ASCAPC), which allows solving properly the problems of enhancing the energy efficiency of transportation processes. Energy efficiency of ETNs is defined as the amount of power losses in ETN components: overhead catenary systems and traction transformers. Due to the instability of traction loads and changes in their location in space, the electric traction network is different from the general network. It is necessary to develop an approach for loss analysis in traction networks and in transformers of traction substations. To solve this problem, a balance-based technique for power loss calculation in traction networks based on ASCAPC data is proposed. First, the balance-based technique presented here breaks down the power consumption of the train by source. Then, calculates technical power losses in 25 and 2 × 25 kV traction networks as well as in traction transformers. Last, the technique is implemented in the form of an algorithm tested on real-life data and it is ready for practical use.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 4","pages":"Pages 640-656"},"PeriodicalIF":2.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01DOI: 10.1016/j.gloei.2025.06.004
Haniyeh Marefat, Francois Auger, Jean-Christophe Olivier, Mohammed Rharda
Proton Exchange Membrane Water Electrolyzers (PEMWE) are efficient and sustainable hydrogen production devices. This article analyzes their static and dynamic electrical models integrated with degradation mechanisms. Static models reveal steady-state behavior, while dynamic models capture transient responses to input variations. The developed modeling approach combines the activation and diffusion phenomena, resulting in a novel PEMWE model that closely reflects real-world conditions and enables fast simulations. The electrical model is integrated with the aging model through two key ratios, surface degradation ratio and membrane degradation ratio, which characterize degradation mechanisms affecting electrode and membrane performance. The linear model using second-order Taylor approximation enables the development of a diagnosis approach that can contribute to estimating the remaining useful life of PEMWEs. By associating aging models with electrical models through the proposed ratios, a deeper understanding is achieved regarding how degradation phenomena evolve and influence electrolyzer efficiency and durability. The integrated framework enables predictive maintenance strategies, making it valuable for industrial hydrogen production applications.
{"title":"Electrical and aging modeling of PEM water electrolyzers for sustainable hydrogen production: Insights into behavior, degradation, and reliability","authors":"Haniyeh Marefat, Francois Auger, Jean-Christophe Olivier, Mohammed Rharda","doi":"10.1016/j.gloei.2025.06.004","DOIUrl":"10.1016/j.gloei.2025.06.004","url":null,"abstract":"<div><div>Proton Exchange Membrane Water Electrolyzers (PEMWE) are efficient and sustainable hydrogen production devices. This article analyzes their static and dynamic electrical models integrated with degradation mechanisms. Static models reveal steady-state behavior, while dynamic models capture transient responses to input variations. The developed modeling approach combines the activation and diffusion phenomena, resulting in a novel PEMWE model that closely reflects real-world conditions and enables fast simulations. The electrical model is integrated with the aging model through two key ratios, surface degradation ratio and membrane degradation ratio, which characterize degradation mechanisms affecting electrode and membrane performance. The linear model using second-order Taylor approximation enables the development of a diagnosis approach that can contribute to estimating the remaining useful life of PEMWEs. By associating aging models with electrical models through the proposed ratios, a deeper understanding is achieved regarding how degradation phenomena evolve and influence electrolyzer efficiency and durability. The integrated framework enables predictive maintenance strategies, making it valuable for industrial hydrogen production applications.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 4","pages":"Pages 537-553"},"PeriodicalIF":2.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The advent of microgrids in modern energy systems heralds a promising era of resilience, sustainability, and efficiency. Within the realm of grid-tied microgrids, the selection of an optimal optimization algorithm is critical for effective energy management, particularly in economic dispatching. This study compares the performance of Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) in microgrid energy management systems, implemented using MATLAB tools. Through a comprehensive review of the literature and simulations conducted in MATLAB, the study analyzes performance metrics, convergence speed, and the overall efficacy of GA and PSO, with a focus on economic dispatching tasks. Notably, a significant distinction emerges between the cost curves generated by the two algorithms for microgrid operation, with the PSO algorithm consistently resulting in lower costs due to its effective economic dispatching capabilities. Specifically, the utilization of the PSO approach could potentially lead to substantial savings on the power bill, amounting to approximately $15.30 in this evaluation. The findings provide insights into the strengths and limitations of each algorithm within the complex dynamics of grid-tied microgrids, thereby assisting stakeholders and researchers in arriving at informed decisions. This study contributes to the discourse on sustainable energy management by offering actionable guidance for the advancement of grid-tied microgrid technologies through MATLAB-implemented optimization algorithms.
{"title":"Comparative analysis of GA and PSO algorithms for optimal cost management in on-grid microgrid energy systems with PV-battery integration","authors":"Mouna EL-Qasery , Ahmed Abbou , Mohamed Laamim , Lahoucine Id-Khajine , Abdelilah Rochd","doi":"10.1016/j.gloei.2025.05.003","DOIUrl":"10.1016/j.gloei.2025.05.003","url":null,"abstract":"<div><div>The advent of microgrids in modern energy systems heralds a promising era of resilience, sustainability, and efficiency. Within the realm of grid-tied microgrids, the selection of an optimal optimization algorithm is critical for effective energy management, particularly in economic dispatching. This study compares the performance of Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) in microgrid energy management systems, implemented using MATLAB tools. Through a comprehensive review of the literature and simulations conducted in MATLAB, the study analyzes performance metrics, convergence speed, and the overall efficacy of GA and PSO, with a focus on economic dispatching tasks. Notably, a significant distinction emerges between the cost curves generated by the two algorithms for microgrid operation, with the PSO algorithm consistently resulting in lower costs due to its effective economic dispatching capabilities. Specifically, the utilization of the PSO approach could potentially lead to substantial savings on the power bill, amounting to approximately $15.30 in this evaluation. The findings provide insights into the strengths and limitations of each algorithm within the complex dynamics of grid-tied microgrids, thereby assisting stakeholders and researchers in arriving at informed decisions. This study contributes to the discourse on sustainable energy management by offering actionable guidance for the advancement of grid-tied microgrid technologies through MATLAB-implemented optimization algorithms.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 4","pages":"Pages 572-580"},"PeriodicalIF":2.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01DOI: 10.1016/j.gloei.2025.02.004
Lei Dong , Kuang Zhang , Shiming Zhang , Tao Zhang , Ye Li , Ji Qiao
P2P trading is driving the decentralization of the electricity market, the autonomy and privacy requirements of prosumers may introduce safety risks such as voltage violations. Existing security management methods based on price guidance may face unsolvable situations in trading scenarios and have difficulty assessing the impact of P2P transactions on voltage security. To this end, this paper proposes a novel distribution system operator (DSO)-prosumers bi-level optimization framework incorporating the dynamic operating envelope (DOE) and risk coefficient-based network usage charge (RC-NUC). In the upper-level, the DOE is employed for dynamic voltage management to prevent violations while the RC-NUC further guides prosumers to engage in grid-friendly transactions. The lower-level decentralized market enables prosumers to optimize trading decisions autonomously. Only price signals and energy quantities are exchanged between the two levels, ensuring the privacy of both parties. Additionally, an alternating direction method of multipliers (ADMM) with adaptive penalty factor is introduced to improve computational efficiency. Case studies on a modified IEEE 33-bus system demonstrate that the proposed method reduces voltage violation risks by 18.31% and enhances trading efficiency by 32.3%. These results highlight the feasibility and effectiveness of the approach in advancing secure and efficient distributed energy transactions.
{"title":"Peer-to-peer transaction with voltage management strategy in distribution network considering trading risk","authors":"Lei Dong , Kuang Zhang , Shiming Zhang , Tao Zhang , Ye Li , Ji Qiao","doi":"10.1016/j.gloei.2025.02.004","DOIUrl":"10.1016/j.gloei.2025.02.004","url":null,"abstract":"<div><div>P2P trading is driving the decentralization of the electricity market, the autonomy and privacy requirements of prosumers may introduce safety risks such as voltage violations. Existing security management methods based on price guidance may face unsolvable situations in trading scenarios and have difficulty assessing the impact of P2P transactions on voltage security. To this end, this paper proposes a novel distribution system operator (DSO)-prosumers bi-level optimization framework incorporating the dynamic operating envelope (DOE) and risk coefficient-based network usage charge (RC-NUC). In the upper-level, the DOE is employed for dynamic voltage management to prevent violations while the RC-NUC further guides prosumers to engage in grid-friendly transactions. The lower-level decentralized market enables prosumers to optimize trading decisions autonomously. Only price signals and energy quantities are exchanged between the two levels, ensuring the privacy of both parties. Additionally, an alternating direction method of multipliers (ADMM) with adaptive penalty factor is introduced to improve computational efficiency. Case studies on a modified IEEE 33-bus system demonstrate that the proposed method reduces voltage violation risks by 18.31% and enhances trading efficiency by 32.3%. These results highlight the feasibility and effectiveness of the approach in advancing secure and efficient distributed energy transactions.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 4","pages":"Pages 685-699"},"PeriodicalIF":2.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01DOI: 10.1016/j.gloei.2025.04.004
Boaz Wadawa , Joseph Yves Effa
A novel robust diagnostic system based on a linear fractional transform (LFT) representation combined with a static redundancy approach is proposed to design a residual generator for fault detection and localization in a wind system using the doubly fed induction generator (DFIG). As a result, faults in DFIG-based grid-connected wind systems can be grouped into three classes of faults, namely, model uncertainty-related faults (FLMU), set point disturbance-related faults (FLDS) and parameter uncertainty-related faults (FLPU). Based on the parity-space residual generations, an artificial neural network (ANN) structure has been combined with the classification to enable the assessment of hidden, indistinguishable or small amplitude faults. The training validation with two data sizes of 1278*4 and 1278*1 respectively at the inputs and outputs of the proposed ANN, presents better performance for a mean squared error value (MSE = 3.0532e−9), and a good correlation between outputs and targets for a regression value (R = 1). It emerges that the proposed robust and complete diagnostic system for the optimal and sustainable integration of wind turbines into the grid, offers very great advantages, particularly with regard to the precise and rapid detection of faults, and the assessment of hidden faults and/or ambiguous fault states in the wind system based on DFIG. In addition, the proposed approach allows the use of a reduced number of data, sensors and actuators required. Consequently, the system maintenance difficulties, complexity and cost of the diagnostic system are reduced.
{"title":"New strategy for fault detection and classification in wind turbines based on doubly-fed induction generators","authors":"Boaz Wadawa , Joseph Yves Effa","doi":"10.1016/j.gloei.2025.04.004","DOIUrl":"10.1016/j.gloei.2025.04.004","url":null,"abstract":"<div><div>A novel robust diagnostic system based on a linear fractional transform (LFT) representation combined with a static redundancy approach is proposed to design a residual generator for fault detection and localization in a wind system using the doubly fed induction generator (DFIG). As a result, faults in DFIG-based grid-connected wind systems can be grouped into three classes of faults, namely, model uncertainty-related faults (FLMU), set point disturbance-related faults (FLDS) and parameter uncertainty-related faults (FLPU). Based on the parity-space residual generations, an artificial neural network (ANN) structure has been combined with the classification to enable the assessment of hidden, indistinguishable or small amplitude faults. The training validation with two data sizes of 1278*4 and 1278*1 respectively at the inputs and outputs of the proposed ANN, presents better performance for a mean squared error value (MSE = 3.0532e<sup>−9</sup>), and a good correlation between outputs and targets for a regression value (R = 1). It emerges that the proposed robust and complete diagnostic system for the optimal and sustainable integration of wind turbines into the grid, offers very great advantages, particularly with regard to the precise and rapid detection of faults, and the assessment of hidden faults and/or ambiguous fault states in the wind system based on DFIG. In addition, the proposed approach allows the use of a reduced number of data, sensors and actuators required. Consequently, the system maintenance difficulties, complexity and cost of the diagnostic system are reduced.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 4","pages":"Pages 668-684"},"PeriodicalIF":2.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Permanent Magnet Synchronous Motors (PMSMs) are widely employed in high-performance drive applications due to their superior efficiency and dynamic capabilities. However, their control remains challenging owing to nonlinear dynamics, parameter variations, and unmeasurable external disturbances, particularly load torque fluctuations. This study proposes an enhanced Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) scheme, formulated within the port-controlled Hamiltonian (PCH) framework, to address these limitations. A nonlinear disturbance observer is embedded to estimate and compensate, in real time, for lumped mismatched disturbances arising from parameter uncertainties and external loads. Additionally, a flatness-based control strategy is employed to generate the desired current references within the nonlinear drive system, ensuring accurate tracking of time-varying speed commands. This integrated approach preserves the system’s energy-based structure, enabling systematic stability analysis while enhancing robustness. The proposed control architecture also maintains low complexity with a limited number of tunable parameters, facilitating practical implementation. Simulation and experimental results under various operating conditions demonstrate the effectiveness and robustness of the proposed method. Comparative analysis with conventional proportional-integral (PI) control and standard IDA-PBC strategies confirms its capability to handle disturbances and maintain dynamic performance.
{"title":"Enhanced interconnection and damping assignment passivity-based control for PM synchronous motors","authors":"Mohamed Azzi , Lotfi Baghli , Ehsan Jamshidpour , Phatiphat Thounthong , Noureddine Takorabet","doi":"10.1016/j.gloei.2025.06.001","DOIUrl":"10.1016/j.gloei.2025.06.001","url":null,"abstract":"<div><div>Permanent Magnet Synchronous Motors (PMSMs) are widely employed in high-performance drive applications due to their superior efficiency and dynamic capabilities. However, their control remains challenging owing to nonlinear dynamics, parameter variations, and unmeasurable external disturbances, particularly load torque fluctuations. This study proposes an enhanced Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) scheme, formulated within the port-controlled Hamiltonian (PCH) framework, to address these limitations. A nonlinear disturbance observer is embedded to estimate and compensate, in real time, for lumped mismatched disturbances arising from parameter uncertainties and external loads. Additionally, a flatness-based control strategy is employed to generate the desired current references within the nonlinear drive system, ensuring accurate tracking of time-varying speed commands. This integrated approach preserves the system’s energy-based structure, enabling systematic stability analysis while enhancing robustness. The proposed control architecture also maintains low complexity with a limited number of tunable parameters, facilitating practical implementation. Simulation and experimental results under various operating conditions demonstrate the effectiveness and robustness of the proposed method. Comparative analysis with conventional proportional-integral (PI) control and standard IDA-PBC strategies confirms its capability to handle disturbances and maintain dynamic performance.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 4","pages":"Pages 657-667"},"PeriodicalIF":2.6,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01DOI: 10.1016/j.gloei.2025.05.001
Zehong Liu , Jinxuan Zhang , Zedong Zhang , Yuanbing Zhou , Jinyu Xiao , Jinming Hou , Yu Ni
China has abundant renewable energy resources. With the establishment of carbon peaking and carbon neutrality goals, renewable energy sources such as wind power and photovoltaics have undergone tremendous development. However, because of the randomness and volatility of wind and photovoltaic power, the large-scale development of renewable energy faces challenges with accommodation and transmission. At present, the bundling of wind–photovoltaic–thermal power with ultra-high voltage transmission projects is the main development approach for renewable energy bases in western and northern China. Nonetheless, solving the problems of high carbon dioxide emission, carbon dioxide capture, and the utilization of thermal power is still necessary. Based on power-to-hydrogen, power-to-methanol, and oxygen-enriched combustion power generation technologies, this article proposes a power-to-hydrogen-and-methanol model based on the collaborative optimization of energy flow and material flow, which is expected to simultaneously solve the problems of renewable energy accommodation and low-carbon transformation of thermal power. Models with different ways of linking power to hydrogen and methanol are established, and an 8760-hour-time-series operation simulation is incorporated into the planning model. A case study is then conducted on renewable energy bases in the deserts of western and northern China. The results show that the power-to-hydrogen-and-methanol model based on the collaborative optimization of energy flow and material flow can greatly reduce the demand for hydrogen storage and energy storage, reduce the cost of carbon capture, make full use of by-product oxygen and captured carbon dioxide, and produce high-value chemical raw materials, thus exhibiting significant economic advantages.
{"title":"Power-to-hydrogen-and-methanol model based on collaborative optimization of energy flow and material flow","authors":"Zehong Liu , Jinxuan Zhang , Zedong Zhang , Yuanbing Zhou , Jinyu Xiao , Jinming Hou , Yu Ni","doi":"10.1016/j.gloei.2025.05.001","DOIUrl":"10.1016/j.gloei.2025.05.001","url":null,"abstract":"<div><div>China has abundant renewable energy resources. With the establishment of carbon peaking and carbon neutrality goals, renewable energy sources such as wind power and photovoltaics have undergone tremendous development. However, because of the randomness and volatility of wind and photovoltaic power, the large-scale development of renewable energy faces challenges with accommodation and transmission. At present, the bundling of wind–photovoltaic–thermal power with ultra-high voltage transmission projects is the main development approach for renewable energy bases in western and northern China. Nonetheless, solving the problems of high carbon dioxide emission, carbon dioxide capture, and the utilization of thermal power is still necessary. Based on power-to-hydrogen, power-to-methanol, and oxygen-enriched combustion power generation technologies, this article proposes a power-to-hydrogen-and-methanol model based on the collaborative optimization of energy flow and material flow, which is expected to simultaneously solve the problems of renewable energy accommodation and low-carbon transformation of thermal power. Models with different ways of linking power to hydrogen and methanol are established, and an 8760-hour-time-series operation simulation is incorporated into the planning model. A case study is then conducted on renewable energy bases in the deserts of western and northern China. The results show that the power-to-hydrogen-and-methanol model based on the collaborative optimization of energy flow and material flow can greatly reduce the demand for hydrogen storage and energy storage, reduce the cost of carbon capture, make full use of by-product oxygen and captured carbon dioxide, and produce high-value chemical raw materials, thus exhibiting significant economic advantages.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 3","pages":"Pages 349-362"},"PeriodicalIF":1.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01DOI: 10.1016/j.gloei.2024.10.016
Changping Sun , Xiaodi Zhang , Wei Zhang , Jiahao Liu , Zubing Zou , Leying Li , Cheng Wang
The frequency regulation reserve setting of wind-PV-storage power stations is crucial. However, the existing grid codes set up the station reserve in a static manner, where the synchronous generator characteristics and frequency-step disturbance scenario are considered. Thus, the advantages of flexible regulation of renewable generations are wasted, resulting in excessive curtailment of wind and solar resources. In this study, a method for optimizing the frequency regulation reserve of wind PV storage power stations was developed. Moreover, a station frequency regulation model was constructed, considering the field dynamic response and the coupling between the station and system frequency dynamics. Furthermore, a method for the online evaluation of the station frequency regulation was proposed based on the benchmark governor fitting. This method helps in overcoming the capacity-based reserve static setting. Finally, an optimization model was developed, along with the proposal of the linearized solving algorithm. The field data from the JH4# station in China’s MX power grid was considered for validation. The proposed method achieves a 24.77 % increase in the station income while ensuring the system frequency stability when compared with the grid code-based method.
{"title":"Frequency regulation reserve optimization of wind-PV-storage power station considering online regulation contribution","authors":"Changping Sun , Xiaodi Zhang , Wei Zhang , Jiahao Liu , Zubing Zou , Leying Li , Cheng Wang","doi":"10.1016/j.gloei.2024.10.016","DOIUrl":"10.1016/j.gloei.2024.10.016","url":null,"abstract":"<div><div>The frequency regulation reserve setting of wind-PV-storage power stations is crucial. However, the existing grid codes set up the station reserve in a static manner, where the synchronous generator characteristics and frequency-step disturbance scenario are considered. Thus, the advantages of flexible regulation of renewable generations are wasted, resulting in excessive curtailment of wind and solar resources. In this study, a method for optimizing the frequency regulation reserve of wind PV storage power stations was developed. Moreover, a station frequency regulation model was constructed, considering the field dynamic response and the coupling between the station and system frequency dynamics. Furthermore, a method for the online evaluation of the station frequency regulation was proposed based on the benchmark governor fitting. This method helps in overcoming the capacity-based reserve static setting. Finally, an optimization model was developed, along with the proposal of the linearized solving algorithm. The field data from the JH4# station in China’s MX power grid was considered for validation. The proposed method achieves a 24.77 % increase in the station income while ensuring the system frequency stability when compared with the grid code-based method.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 3","pages":"Pages 433-446"},"PeriodicalIF":1.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01DOI: 10.1016/j.gloei.2025.03.002
Xinlan Deng , Youhan Deng , Liang Qin , Weiwei Yao , Min He , Kaipei Liu
Submodule capacitor aging poses significant challenges to the safe operation of modular multilevel converter (MMC) systems. Traditional detection methods rely predominantly on offline tests, lacking real-time evaluation capabilities. Moreover, existing online approaches require additional sampling channels, thereby increasing system complexity and costs. To address these issues, this paper proposes an online evaluation method for submodule capacitor aging based on CapAgingNet. Initially, an MMC system simulation platform is developed to examine the effects of submodule capacitor aging on system operational characteristics and to create a dataset of submodule capacitor switching states. Subsequently, the CapAgingNet model is introduced, incorporating key technical modules to enhance performance: the Deep Stem module, which extracts larger receptive fields through multiple convolution layers and mitigates the impact of data sparsity in capacitor aging on feature extraction; the efficient channel attention (ECA) module, utilizing one-dimensional convolution for dynamic weighting to adjust the importance of each channel, thereby enhancing the ability of the model to process high-dimensional features in capacitor aging data; and the multiscale feature fusion (MSF) module, which integrates capacitor aging information across different scales by combining fine-grained and coarse-grained features, thus improving the capacity of the model to capture high-frequency variation characteristics. The experimental results reveal that the CapAgingNet model achieves a TOP-1 accuracy of 95.32 % and a macro-averaged F1 score of 95.49 % on the test set, thereby providing effective technical support for online monitoring of submodule capacitor aging.
{"title":"Online evaluation method for MMC submodule capacitor aging based on CapAgingNet","authors":"Xinlan Deng , Youhan Deng , Liang Qin , Weiwei Yao , Min He , Kaipei Liu","doi":"10.1016/j.gloei.2025.03.002","DOIUrl":"10.1016/j.gloei.2025.03.002","url":null,"abstract":"<div><div>Submodule capacitor aging poses significant challenges to the safe operation of modular multilevel converter (MMC) systems. Traditional detection methods rely predominantly on offline tests, lacking real-time evaluation capabilities. Moreover, existing online approaches require additional sampling channels, thereby increasing system complexity and costs. To address these issues, this paper proposes an online evaluation method for submodule capacitor aging based on CapAgingNet. Initially, an MMC system simulation platform is developed to examine the effects of submodule capacitor aging on system operational characteristics and to create a dataset of submodule capacitor switching states. Subsequently, the CapAgingNet model is introduced, incorporating key technical modules to enhance performance: the Deep Stem module, which extracts larger receptive fields through multiple convolution layers and mitigates the impact of data sparsity in capacitor aging on feature extraction; the efficient channel attention (ECA) module, utilizing one-dimensional convolution for dynamic weighting to adjust the importance of each channel, thereby enhancing the ability of the model to process high-dimensional features in capacitor aging data; and the multiscale feature fusion (MSF) module, which integrates capacitor aging information across different scales by combining fine-grained and coarse-grained features, thus improving the capacity of the model to capture high-frequency variation characteristics. The experimental results reveal that the CapAgingNet model achieves a TOP-1 accuracy of 95.32 % and a macro-averaged F<sub>1</sub> score of 95.49 % on the test set, thereby providing effective technical support for online monitoring of submodule capacitor aging.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 3","pages":"Pages 420-432"},"PeriodicalIF":1.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research aims to improve the power output of a horizontal axis wind turbine (HAWT) by using an auxiliary rotor in front of the main rotor, this configuration is called a dual-rotor wind turbine (DRWT). The three-bladed main rotor has a diameter of 0.9 m and both rotors with NREL S826 airfoil. ANSYS Fluent CFD simulation was used to optimize the DRWT performance where the numerical model was solved using the Realizable k-ɛ turbulence model. Four parameters are used, diameter ratio between the auxiliary front rotor and the main rear rotor (DR = 0.25, DR = 0.5, and DR = 0.75), axial free stream velocity according to the normal wind speed range in Egypt (Vo = 5 m/s, Vo = 7.5 m/s, and Vo = 10 m/s), tip speed ratio which ranges from 2 to 8, and the number of blades of the front rotor (B = 2, B = 3 and B = 4). The results show that increasing the number of blades positively impacts performance but at lower tip speed ratios. Smaller diameter ratios yield better performance, while increasing wind speed results in higher power. The best performance was achieved at freestream velocity Vo = 10 m/s, diameter ratio DR = 0.25, front rotor number of blades B = 4, and tip speed ratio λ = 5 in which the overall maximum power coefficient Cp max = 0.552 with an increase with 36.75 % compared to the single rotor case.
本研究的目的是在水平轴风力机（HAWT）的主转子前面增加一个辅助转子来提高其功率输出，这种结构称为双转子风力机（DRWT）。三叶主旋翼直径0.9米，两个旋翼都采用NREL S826翼型。采用ANSYS Fluent CFD仿真对DRWT性能进行优化，采用Realizable k- ε湍流模型求解数值模型。采用辅助前转子与主后转子直径比（DR = 0.25, DR = 0.5, DR = 0.75），根据埃及正常风速范围的轴向自由流速度（Vo = 5m /s, Vo = 7.5 m/s, Vo = 10m /s），叶顶速比2 ~ 8，前转子叶片数（B = 2, B = 3, B = 4）四个参数。结果表明，增加叶片数量对性能有积极影响，但叶尖速比较低。较小的直径比产生更好的性能，而增加风速产生更高的功率。在自由流速度Vo = 10 m/s、直径比DR = 0.25、前旋翼叶数B = 4、叶尖速比λ = 5时，总最大功率系数Cp max = 0.552，比单转子情况提高36.75%。
{"title":"Study the effect of using a dual rotor system on the performance of horizontal axis wind turbines using CFD","authors":"Amr Mokhtar , Mahmoud Fouad , Mohamed Rashed , Mostafa Mokhtar","doi":"10.1016/j.gloei.2025.01.008","DOIUrl":"10.1016/j.gloei.2025.01.008","url":null,"abstract":"<div><div>This research aims to improve the power output of a horizontal axis wind turbine (HAWT) by using an auxiliary rotor in front of the main rotor, this configuration is called a dual-rotor wind turbine (DRWT). The three-bladed main rotor has a diameter of 0.9 m and both rotors with NREL S826 airfoil. ANSYS Fluent CFD simulation was used to optimize the DRWT performance where the numerical model was solved using the Realizable <em>k</em>-<em>ɛ</em> turbulence model. Four parameters are used, diameter ratio between the auxiliary front rotor and the main rear rotor (<em>D</em><sub>R</sub> = 0.25, <em>D</em><sub>R</sub> = 0.5, and <em>D</em><sub>R</sub> = 0.75), axial free stream velocity according to the normal wind speed range in Egypt (<em>V</em><sub>o</sub> = 5 m/s, <em>V</em><sub>o</sub> = 7.5 m/s, and <em>V</em><sub>o</sub> = 10 m/s), tip speed ratio which ranges from 2 to 8, and the number of blades of the front rotor (<em>B</em> = 2, <em>B</em> = 3 and <em>B</em> = 4). The results show that increasing the number of blades positively impacts performance but at lower tip speed ratios. Smaller diameter ratios yield better performance, while increasing wind speed results in higher power. The best performance was achieved at freestream velocity <em>V</em><sub>o</sub> = 10 m/s, diameter ratio <em>D</em><sub>R</sub> = 0.25, front rotor number of blades <em>B</em> = 4, and tip speed ratio <em>λ</em> = 5 in which the overall maximum power coefficient Cp max = 0.552 with an increase with 36.75 % compared to the single rotor case.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 3","pages":"Pages 497-509"},"PeriodicalIF":1.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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