Stephen Mossing;Oscar Amestegui;Michael Jonas;Fei Feng;Lizhi Wang;Qing Shen;Sina Zarrabian;Ziqian Liu;Peng Zhang
Modern shipboard microgrids (SMGs) incorporating distributed energy resources (DERs) enhance energy resilience and reduce carbon emissions. However, the hierarchical control schemes of DERs bring challenges to the traditional power flow methods. This paper devises a generalized three-phase power flow approach for SMGs that integrate hierarchically controlled DERs. The main contributions include: (1) a droop-controlled three-phase Newton power flow algorithm that automatically incorporates the droop characteristics of DERs; (2) a secondary-controlled three-phase power flow method for power sharing and voltage regulation; and (3) modified Jacobian matrices to incorporate various hierarchical control modes. Numerical results demonstrate the effectiveness of the devised approach in both balanced and unbalanced three-phase hierarchically controlled SMG systems with arbitrary configurations.
{"title":"Generalized shipboard microgrid power flow incorporating hierarchical control","authors":"Stephen Mossing;Oscar Amestegui;Michael Jonas;Fei Feng;Lizhi Wang;Qing Shen;Sina Zarrabian;Ziqian Liu;Peng Zhang","doi":"10.23919/IEN.2025.0018","DOIUrl":"https://doi.org/10.23919/IEN.2025.0018","url":null,"abstract":"Modern shipboard microgrids (SMGs) incorporating distributed energy resources (DERs) enhance energy resilience and reduce carbon emissions. However, the hierarchical control schemes of DERs bring challenges to the traditional power flow methods. This paper devises a generalized three-phase power flow approach for SMGs that integrate hierarchically controlled DERs. The main contributions include: (1) a droop-controlled three-phase Newton power flow algorithm that automatically incorporates the droop characteristics of DERs; (2) a secondary-controlled three-phase power flow method for power sharing and voltage regulation; and (3) modified Jacobian matrices to incorporate various hierarchical control modes. Numerical results demonstrate the effectiveness of the devised approach in both balanced and unbalanced three-phase hierarchically controlled SMG systems with arbitrary configurations.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"4 3","pages":"165-173"},"PeriodicalIF":5.1,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11125856","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144990215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a strength-constrained unit commitment (UC) model incorporating system strength constraints based on the weighted short-circuit ratio (WSCR) is proposed. This model facilitates the comprehensive assessment of area-wide system strength in power systems with high inverter-based resource (IBR) penetration, thereby contributing to the mitigation of weak grid issues. Unlike traditional models, this approach considers the interactions among multiple IBRs. The UC problem is initially formulated as a mixed-integer nonlinear programming (MINLP) model, reflecting WSCR and bus impedance matrix modification constraints. To enhance computational tractability, the model is transformed into a mixed-integer linear programming (MILP) form. The effectiveness of the proposed approach is validated through simulations on the IEEE 5-bus, IEEE 39-bus, and a modified Korean power system, demonstrating the ability of the proposed UC model enhancing system strength compared to the conventional methodologies.
{"title":"Strength-constrained unit commitment in IBR dominant power systems","authors":"Yong-Kyu Kim;Sang-Ho Lee;Gyu-Sub Lee","doi":"10.23919/IEN.2025.0011","DOIUrl":"https://doi.org/10.23919/IEN.2025.0011","url":null,"abstract":"In this paper, a strength-constrained unit commitment (UC) model incorporating system strength constraints based on the weighted short-circuit ratio (WSCR) is proposed. This model facilitates the comprehensive assessment of area-wide system strength in power systems with high inverter-based resource (IBR) penetration, thereby contributing to the mitigation of weak grid issues. Unlike traditional models, this approach considers the interactions among multiple IBRs. The UC problem is initially formulated as a mixed-integer nonlinear programming (MINLP) model, reflecting WSCR and bus impedance matrix modification constraints. To enhance computational tractability, the model is transformed into a mixed-integer linear programming (MILP) form. The effectiveness of the proposed approach is validated through simulations on the IEEE 5-bus, IEEE 39-bus, and a modified Korean power system, demonstrating the ability of the proposed UC model enhancing system strength compared to the conventional methodologies.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"4 2","pages":"121-131"},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11045319","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144323139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Grid-scale energy storage systems provide effective solutions to address challenges such as supply-load imbalances and voltage violations resulting from the non-coinciding nature of renewable energy generation and peak demand incidents. While battery and hydrogen storage are commonly used for peak shaving, ice-based thermal energy storage systems (TESSs) offer a direct way to reduce cooling loads without electrical conversion. This paper presents a multi-objective planning framework that optimizes TESS dispatch, network topology, and photovoltaic (PV) inverter reactive power support to address operational issues in active distribution networks. The objectives of the proposed scheme include minimizing peak demand, voltage deviations, and PV inverter VAr dependency. The mixed-integer nonlinear programming problem is solved using a Pareto-based multi-objective particle swarm optimization (MOPSO) method. The MATLAB-OpenDSS simulations for a modified IEEE-123 bus system show a 7.1% reduction in peak demand, a 13% reduction in voltage deviation, and a 52% drop in PV inverter VAr usage. The obtained solutions confirm minimal operational stress on control devices such as switches and PV inverters. Thus, unlike earlier studies, this work combines all three strategies to offer an effective solution for the operational planning of the active distribution network.
{"title":"Enhancing operational planning of active distribution networks considering effective topology selection and thermal energy storage","authors":"Vineeth Vijayan;Ali Arzani;Satish M. Mahajan","doi":"10.23919/IEN.2025.0013","DOIUrl":"https://doi.org/10.23919/IEN.2025.0013","url":null,"abstract":"Grid-scale energy storage systems provide effective solutions to address challenges such as supply-load imbalances and voltage violations resulting from the non-coinciding nature of renewable energy generation and peak demand incidents. While battery and hydrogen storage are commonly used for peak shaving, ice-based thermal energy storage systems (TESSs) offer a direct way to reduce cooling loads without electrical conversion. This paper presents a multi-objective planning framework that optimizes TESS dispatch, network topology, and photovoltaic (PV) inverter reactive power support to address operational issues in active distribution networks. The objectives of the proposed scheme include minimizing peak demand, voltage deviations, and PV inverter VAr dependency. The mixed-integer nonlinear programming problem is solved using a Pareto-based multi-objective particle swarm optimization (MOPSO) method. The MATLAB-OpenDSS simulations for a modified IEEE-123 bus system show a 7.1% reduction in peak demand, a 13% reduction in voltage deviation, and a 52% drop in PV inverter VAr usage. The obtained solutions confirm minimal operational stress on control devices such as switches and PV inverters. Thus, unlike earlier studies, this work combines all three strategies to offer an effective solution for the operational planning of the active distribution network.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"4 2","pages":"98-106"},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11045320","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144323257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Over the past two decades, the industry policy framework centered on the Renewable Energy Law has effectively facilitated the leapfrog development of China's new energy sector. During this period, policy incentives were primarily focused on promoting the rational scaling of the industry, thereby driving rapid technological upgrades and iterations. This, in turn, enabled a significant reduction in the cost of new energy power generation. In this process, policy played a pivotal role in two key areas: first, by providing per-kilowatt-hour subsidies to bridge the cost gap between new energy and conventional power sources; and second, by exempting the system cost of new energy grid-connected operation through a full guaranteed purchase system.
{"title":"Three key policy areas in urgent need of improvement for advancing China's energy transition","authors":"Peng Li;Jing Zhang","doi":"10.23919/IEN.2025.0014","DOIUrl":"https://doi.org/10.23919/IEN.2025.0014","url":null,"abstract":"Over the past two decades, the industry policy framework centered on the Renewable Energy Law has effectively facilitated the leapfrog development of China's new energy sector. During this period, policy incentives were primarily focused on promoting the rational scaling of the industry, thereby driving rapid technological upgrades and iterations. This, in turn, enabled a significant reduction in the cost of new energy power generation. In this process, policy played a pivotal role in two key areas: first, by providing per-kilowatt-hour subsidies to bridge the cost gap between new energy and conventional power sources; and second, by exempting the system cost of new energy grid-connected operation through a full guaranteed purchase system.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"4 2","pages":"77-78"},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11045317","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144323206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Renewable generation is rapidly increasing and transforming power systems toward “new-type power systems”. The integration of renewable energy resources necessitates a shift from conventional grid-following converters (GFLs) to advanced grid-forming controls. Although grid-forming converters (GFMs) provide grid support and enhance system stability under weak grid conditions, their deployment requires more robust hardware, complex control algorithms and system operation constraints, resulting in planning and operational trade-offs between system stability and cost efficiency. This paper studies the underexplored question of how many GFMs are needed from a techno-economic perspective. The holistic analysis integrates long-term planning, short-term operational strategies and dynamic stability considerations, thereby supporting large-scale renewable integration while ensuring system security and economic benefits.
{"title":"How many grid-forming converters are needed? — A techno-economic perspective","authors":"Guoxuan Cui;Hongyang Jia;Ning Zhang;Fei Teng","doi":"10.23919/IEN.2025.0012","DOIUrl":"https://doi.org/10.23919/IEN.2025.0012","url":null,"abstract":"Renewable generation is rapidly increasing and transforming power systems toward “new-type power systems”. The integration of renewable energy resources necessitates a shift from conventional grid-following converters (GFLs) to advanced grid-forming controls. Although grid-forming converters (GFMs) provide grid support and enhance system stability under weak grid conditions, their deployment requires more robust hardware, complex control algorithms and system operation constraints, resulting in planning and operational trade-offs between system stability and cost efficiency. This paper studies the underexplored question of how many GFMs are needed from a techno-economic perspective. The holistic analysis integrates long-term planning, short-term operational strategies and dynamic stability considerations, thereby supporting large-scale renewable integration while ensuring system security and economic benefits.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"4 2","pages":"79-85"},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11045318","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144323170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Active distribution network (ADN) planning is crucial for achieving a cost-effective transition to modern power systems, yet it poses significant challenges as the system scale increases. The advent of quantum computing offers a transformative approach to solve ADN planning. To fully leverage the potential of quantum computing, this paper proposes a photonic quantum acceleration algorithm. First, a quantum-accelerated framework for ADN planning is proposed on the basis of coherent photonic quantum computers. The ADN planning model is then formulated and decomposed into discrete master problems and continuous subproblems to facilitate the quantum optimization process. The photonic quantum-embedded adaptive alternating direction method of multipliers (PQA-ADMM) algorithm is subsequently proposed to equivalently map the discrete master problem onto a quantum-interpretable model, enabling its deployment on a photonic quantum computer. Finally, a comparative analysis with various solvers, including Gurobi, demonstrates that the proposed PQA-ADMM algorithm achieves significant speedup on the modified IEEE 33-node and IEEE 123-node systems, highlighting its effectiveness.
{"title":"Quantum-accelerated active distribution network planning based on coherent photonic quantum computers","authors":"Yu Xin;Haipeng Xie;Wei Fu","doi":"10.23919/IEN.2025.0009","DOIUrl":"https://doi.org/10.23919/IEN.2025.0009","url":null,"abstract":"Active distribution network (ADN) planning is crucial for achieving a cost-effective transition to modern power systems, yet it poses significant challenges as the system scale increases. The advent of quantum computing offers a transformative approach to solve ADN planning. To fully leverage the potential of quantum computing, this paper proposes a photonic quantum acceleration algorithm. First, a quantum-accelerated framework for ADN planning is proposed on the basis of coherent photonic quantum computers. The ADN planning model is then formulated and decomposed into discrete master problems and continuous subproblems to facilitate the quantum optimization process. The photonic quantum-embedded adaptive alternating direction method of multipliers (PQA-ADMM) algorithm is subsequently proposed to equivalently map the discrete master problem onto a quantum-interpretable model, enabling its deployment on a photonic quantum computer. Finally, a comparative analysis with various solvers, including Gurobi, demonstrates that the proposed PQA-ADMM algorithm achieves significant speedup on the modified IEEE 33-node and IEEE 123-node systems, highlighting its effectiveness.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"4 2","pages":"107-120"},"PeriodicalIF":0.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11036584","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144323218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wide-band oscillations have become a significant issue limiting the development of wind power. Both large-signal and small-signal analyses require extensive model derivation. Moreover, the large number and high order of wind turbines have driven the development of simplified models, whose applicability remains controversial. In this paper, a wide-band oscillation analysis method based on the average-value model (AVM) is proposed for wind farms (WFs). A novel linearization analysis framework is developed, leveraging the continuous-time characteristics of the AVM and MATLAB/Simulink's built-in linearization tools. This significantly reduces modeling complexity and computational costs while maintaining model fidelity. Additionally, an object-based initial value estimation method of state variables is introduced, which, when combined with steady-state point-solving tools, greatly reduces the computational effort required for equilibrium point solving in batch linearization analysis. The proposed method is validated in both doubly fed induction generator (DFIG)-based and permanent magnet synchronous generator (PMSG)-based WFs. Furthermore, a comprehensive analysis is conducted for the first time to examine the impact of the machine-side system on the system stability of the non-fully controlled PMSG-based WF.
{"title":"Facilitating wide-band oscillation analysis in wind farms with a novel linearization analysis framework based on the average-value model","authors":"Qiufang Zhang;Yin Xu;Jinghan He","doi":"10.23919/IEN.2025.0010","DOIUrl":"https://doi.org/10.23919/IEN.2025.0010","url":null,"abstract":"Wide-band oscillations have become a significant issue limiting the development of wind power. Both large-signal and small-signal analyses require extensive model derivation. Moreover, the large number and high order of wind turbines have driven the development of simplified models, whose applicability remains controversial. In this paper, a wide-band oscillation analysis method based on the average-value model (AVM) is proposed for wind farms (WFs). A novel linearization analysis framework is developed, leveraging the continuous-time characteristics of the AVM and MATLAB/Simulink's built-in linearization tools. This significantly reduces modeling complexity and computational costs while maintaining model fidelity. Additionally, an object-based initial value estimation method of state variables is introduced, which, when combined with steady-state point-solving tools, greatly reduces the computational effort required for equilibrium point solving in batch linearization analysis. The proposed method is validated in both doubly fed induction generator (DFIG)-based and permanent magnet synchronous generator (PMSG)-based WFs. Furthermore, a comprehensive analysis is conducted for the first time to examine the impact of the machine-side system on the system stability of the non-fully controlled PMSG-based WF.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"4 2","pages":"132-148"},"PeriodicalIF":0.0,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11029167","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144323256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Boyu Qin;Jialing Liu;Hongzhen Wang;Zhaojian Wang;Ziming Xiong;Mingyang Wang;Qihu Qian
Within the transition process of urban rail transit systems, the challenges of high energy consumption, increasing carbon emissions, limited economic viability, and intricate risks emerge as significant hurdles. This paper proposes a novel energy utilization framework for the urban rail transit system that incorporates underground energy storage systems characterized by high resilience and low carbon. First, existing methods employed in urban rail transit are comprehensively reviewed. Then, a novel framework and strategic significance of the urban rail transit system incorporating underground energy storage systems are introduced. This integration effectively utilizes and manages diverse renewable energy sources and the available space resources. The viability is demonstrated through a case study by combining Nanjing metro. Finally, suggestions for research in pivotal areas are summarized.
{"title":"Energy-efficient and reliable urban rail transit: A new framework incorporating underground energy storage systems","authors":"Boyu Qin;Jialing Liu;Hongzhen Wang;Zhaojian Wang;Ziming Xiong;Mingyang Wang;Qihu Qian","doi":"10.23919/IEN.2025.0008","DOIUrl":"https://doi.org/10.23919/IEN.2025.0008","url":null,"abstract":"Within the transition process of urban rail transit systems, the challenges of high energy consumption, increasing carbon emissions, limited economic viability, and intricate risks emerge as significant hurdles. This paper proposes a novel energy utilization framework for the urban rail transit system that incorporates underground energy storage systems characterized by high resilience and low carbon. First, existing methods employed in urban rail transit are comprehensively reviewed. Then, a novel framework and strategic significance of the urban rail transit system incorporating underground energy storage systems are introduced. This integration effectively utilizes and manages diverse renewable energy sources and the available space resources. The viability is demonstrated through a case study by combining Nanjing metro. Finally, suggestions for research in pivotal areas are summarized.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"4 2","pages":"86-97"},"PeriodicalIF":0.0,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11023174","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144323220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rapid advancement of artificial intelligence (AI) has significantly increased the computational load on data centers. AI-related computational activities consume considerable electricity and result in substantial carbon emissions. To mitigate these emissions, future data centers should be strategically planned and operated to fully utilize renewable energy resources while meeting growing computational demands. This paper aims to investigate how much carbon emission reduction can be achieved by using a carbon-oriented demand response to guide the optimal planning and operation of data centers. A carbon-oriented data center planning model is proposed that considers the carbon-oriented demand response of the AI load. In the planning model, future operation simulations comprehensively coordinate the temporal-spatial flexibility of computational loads and the quality of service (QoS). An empirical study based on the proposed models is conducted on real-world data from China. The results from the empirical analysis show that newly constructed data centers are recommended to be built in Gansu Province, Ningxia Hui Autonomous Region, Sichuan Province, Inner Mongolia Autonomous Region, and Qinghai Province, accounting for 57% of the total national increase in server capacity. 33% of the computational load from Eastern China should be transferred to the West, which could reduce the overall load carbon emissions by 26%.
{"title":"Estimating the carbon emission reduction potential of using carbon-oriented demand response for data centers: A case study in China","authors":"Bojun Du;Hongyang Jia;Yaowang Li;Ershun Du;Ning Zhang;Dong Liang","doi":"10.23919/IEN.2025.0007","DOIUrl":"https://doi.org/10.23919/IEN.2025.0007","url":null,"abstract":"The rapid advancement of artificial intelligence (AI) has significantly increased the computational load on data centers. AI-related computational activities consume considerable electricity and result in substantial carbon emissions. To mitigate these emissions, future data centers should be strategically planned and operated to fully utilize renewable energy resources while meeting growing computational demands. This paper aims to investigate how much carbon emission reduction can be achieved by using a carbon-oriented demand response to guide the optimal planning and operation of data centers. A carbon-oriented data center planning model is proposed that considers the carbon-oriented demand response of the AI load. In the planning model, future operation simulations comprehensively coordinate the temporal-spatial flexibility of computational loads and the quality of service (QoS). An empirical study based on the proposed models is conducted on real-world data from China. The results from the empirical analysis show that newly constructed data centers are recommended to be built in Gansu Province, Ningxia Hui Autonomous Region, Sichuan Province, Inner Mongolia Autonomous Region, and Qinghai Province, accounting for 57% of the total national increase in server capacity. 33% of the computational load from Eastern China should be transferred to the West, which could reduce the overall load carbon emissions by 26%.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"4 1","pages":"54-64"},"PeriodicalIF":0.0,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10938040","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143688099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cross-regional high voltage direct current (HVDC) systems bring remarkable renewable power injections to the receiver side of power grids. However, HVDC failures result in large disturbances to receivers and cause critical frequency security problems. High renewable energy penetration also reduces the system inertia and damping coefficients. Thus, some nodal frequency nadirs may be much lower than those calculated by the center-of-inertia (COI) and may trigger low-frequency protection. Energy storage is a promising solution for frequency-related problems. In this study, we build an energy storage planning model considering both COI and nodal frequency security constraints. The energy storage capacities and locations are determined in the planning scheme based on year-round operations. First, we carry out a year-round COI-frequency-constrained unit commitment to obtain comprehensive operation modes. Next, we propose a hybrid data-model driven approach to generate nodal frequency security constraints for extensive operation modes effectively. Finally, we achieve optimal energy storage planning with both COI and nodal frequency constraints. Case studies on a modified RTS-79 test system and a 1089-bus power system in practical in Jiangsu, China, verify the effectiveness of the proposed methods.
{"title":"Nodal frequency-constrained energy storage planning via hybrid data-model driven methods","authors":"Jiaxin Wang;Jiawei Zhang;Min Yang;Yating Wang;Ning Zhang","doi":"10.23919/IEN.2025.0005","DOIUrl":"https://doi.org/10.23919/IEN.2025.0005","url":null,"abstract":"Cross-regional high voltage direct current (HVDC) systems bring remarkable renewable power injections to the receiver side of power grids. However, HVDC failures result in large disturbances to receivers and cause critical frequency security problems. High renewable energy penetration also reduces the system inertia and damping coefficients. Thus, some nodal frequency nadirs may be much lower than those calculated by the center-of-inertia (COI) and may trigger low-frequency protection. Energy storage is a promising solution for frequency-related problems. In this study, we build an energy storage planning model considering both COI and nodal frequency security constraints. The energy storage capacities and locations are determined in the planning scheme based on year-round operations. First, we carry out a year-round COI-frequency-constrained unit commitment to obtain comprehensive operation modes. Next, we propose a hybrid data-model driven approach to generate nodal frequency security constraints for extensive operation modes effectively. Finally, we achieve optimal energy storage planning with both COI and nodal frequency constraints. Case studies on a modified RTS-79 test system and a 1089-bus power system in practical in Jiangsu, China, verify the effectiveness of the proposed methods.","PeriodicalId":100648,"journal":{"name":"iEnergy","volume":"4 1","pages":"43-53"},"PeriodicalIF":0.0,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10938039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143688170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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