CSEE Journal of Power and Energy Systems最新文献_第5页

Voltage-Dependent Modeling of Electromechanical Wave Propagation for Power System Dynamic Stability Analysis 电力系统动态稳定性分析中机电波传播的电压相关建模

IF 5.6 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2026-07-01 Epub Date: 2026-07-03 DOI: 10.17775/CSEEJPES.2025.10010

Somayeh Yarahmadi;Parastoo Sadat Hosseinian;Daniel Adrian Maldonado;Lamine Mili;Junbo Zhao;Mihai Anitescu

{"title":"Voltage-Dependent Modeling of Electromechanical Wave Propagation for Power System Dynamic Stability Analysis","authors":"Somayeh Yarahmadi;Parastoo Sadat Hosseinian;Daniel Adrian Maldonado;Lamine Mili;Junbo Zhao;Mihai Anitescu","doi":"10.17775/CSEEJPES.2025.10010","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2025.10010","url":null,"abstract":"Accurate dynamic modeling of power systems is essential to assess the stability of electrical power systems when faced with disturbances, which can trigger cascading failures leading to blackouts. A continuum model proves to be effective in capturing Electromechanical Wave (EMW) propagation characteristics, including its velocity, arrival time, and deviations. Analyzing these characteristics enables the assessment of the impacts of EMW on the performance of the protection system. Prior research has often modeled nonlinear EMW propagation through Partial Differential Equations (PDEs) within a homogeneous and uniform frame structure, assuming constant bus voltages across the entire power system. However, this assumption can produce inaccurate results. In this paper, we relax this assumption by introducing a second-order nonlinear hyperbolic EMW propagation equation model that accounts for voltage variations. Additionally, we present numerical solutions for the EMW propagation equation using the Lax-Wendroff integration method. To validate our approach, we conduct simulations on two test systems, namely, a 5-bus 5-machine system and the New England 39-bus 10-machine system. The simulation results demonstrate the effectiveness of our proposed model and emphasize the importance of including the bus voltage equations in the analysis.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"12 4","pages":"1754-1765"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11595370","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148749317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Operational Range Assessment of Volt-VAR Security for Preventing Initial Commutation Failures of Multi-Infeed HVDCs 防止多馈入高压直流系统初始换相故障的电压无功安全性工作范围评估

IF 5.6 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2026-07-01 Epub Date: 2023-06-27 DOI: 10.17775/CSEEJPES.2022.05750

Yinhong Lin;Bin Wang;Qinglai Guo;Huaichang Ge;Haotian Zhao;Yanzhen Zhou;Hongbin Sun

{"title":"Operational Range Assessment of Volt-VAR Security for Preventing Initial Commutation Failures of Multi-Infeed HVDCs","authors":"Yinhong Lin;Bin Wang;Qinglai Guo;Huaichang Ge;Haotian Zhao;Yanzhen Zhou;Hongbin Sun","doi":"10.17775/CSEEJPES.2022.05750","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.05750","url":null,"abstract":"High-voltage direct current (HVDC) technology has been applied in many countries. Due to power imported via HVDCs, many synchronous generators have been shut down in receiving-end grids. Under this circumstance, simultaneous commutation failures (CFs) of multi-infeed HVDCs are likely to occur under AC faults that may cause a blackout. Thus, it is crucial to enhance dynamic var support in receiving-end grids. Many studies mainly focus on fast action of power electronic dynamic var sources and synchronous machine (SM) AVRs' control, while spontaneous var output (SVO) of SMs may be underestimated. However, due to time delay of power electronic and AVR control, initial CFs are still likely to occur under short-circuit faults. To address this problem, this paper analyzes the mechanism of SVO and its impact on initial CFs. Then, the concept of Volt-VAR secure operational range (VVSOR) is proposed to ensure sufficiency of SVOs for preventing initial CFs. An optimization model for evaluating the VVSOR is established accurately without iteration with time-domain simulations. A heuristic solution method based on the decomposition algorithm is proposed. Finally, validity and efficiency of the evaluation method are verified based on a modified IEEE 39-bus system and a real system in eastern China.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"12 4","pages":"1809-1819"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10165675","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148749204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transmission Power-Oriented Forecasting Towards Stability-Constrained Operation of Renewable Energy Power Plants with Energy Storages 带储能的可再生能源电厂稳定约束运行的输电功率导向预测

IF 5.6 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2026-07-01 Epub Date: 2025-07-03 DOI: 10.17775/CSEEJPES.2024.06200

Feilong Fan;Chuanqing Pu;Jun Wang;Nengling Tai;Hongqiao Peng;Qifen Li

{"title":"Transmission Power-Oriented Forecasting Towards Stability-Constrained Operation of Renewable Energy Power Plants with Energy Storages","authors":"Feilong Fan;Chuanqing Pu;Jun Wang;Nengling Tai;Hongqiao Peng;Qifen Li","doi":"10.17775/CSEEJPES.2024.06200","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2024.06200","url":null,"abstract":"Forecasts of renewable energy generation are crucial to enhance the transmission power of renewable energy power plants (REPPs) with energy storage systems (ESSs). Existing forecasting methods mainly focus on reducing statistical errors and neglect the impact of forecast results on the transmission power of REPPs under stability constraints. This paper proposes a stability-constrained transmission power-oriented forecasting (TPOF) method to maximize the transmission power of REPP. To quantify the relationship between forecast errors and transmission power, a customized loss function is designed, embedding the operational dynamics of the REPP. A training algorithm based on implicit differentiation is developed to ensure the loss back-propagation of the forecasting method. Simulation results based on the model of REPP in the USA demonstrate that the proposed method significantly enhances the transmission power of REPP by precisely mitigating forecast errors during periods of lower stability margins.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"12 4","pages":"1704-1715"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11069389","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148749590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bi-Level Optimal Allocation of Virtual Power Plants Under Grid Strength via Integrated Short-Circuit Ratio 基于综合短路比的电网强度下虚拟电厂双级优化配置

IF 5.6 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2026-07-01 Epub Date: 2024-03-03 DOI: 10.17775/CSEEJPES.2022.08040

Dashuang Li;Qiuye Sun;Jie Hu

{"title":"Bi-Level Optimal Allocation of Virtual Power Plants Under Grid Strength via Integrated Short-Circuit Ratio","authors":"Dashuang Li;Qiuye Sun;Jie Hu","doi":"10.17775/CSEEJPES.2022.08040","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.08040","url":null,"abstract":"The integration of a virtual power plant (VPP) into a weak grid may cause system unreliability and instability. Different allocations of renewable energy sources (RERs) and flexible power-adjustable devices (FPADs) in VPP have different impacts on system strength. Short circuit ratio (SCR) is an important index used to assess the grid strength. First, this paper proposes an integrated short circuit ratio (ISCR) index based on the network structure characteristics of the VPP grid-connected system (VPPGCS). The ISCR considers the interactions among FPADs in addition to the interactions of the RESs in VPP to assess system strength accurately. Then, a bi-level optimal allocation method for RESs and FPADs is proposed based on the proposed ISCR to enhance system strength and increase the output capacity of VPP. In the upper level, the location and capacity of RESs are optimized. It guarantees the maximum value of ISCR at connection points (CP). In the lower level, the location and capacity of FPADs are optimized. It ensures the ISCR value is above the critical short-circuit ratio (CSCR) to maintain the system strength. Location optimization is determined by the ISCR value at CP. Capacity optimization is solved using linear programming. Finally, case studies verify the effectiveness of the proposed optimization method in increasing VPP output capacity while maintaining VPPGCS strength.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"12 4","pages":"1940-1951"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520147","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148746925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dominant Instability Mechanism and Stability Stationary Points of Grid-Forming Converter Under Stiff Grid 刚性网格下成网转炉的优势失稳机理及稳定平稳点

IF 5.6 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2026-07-01 Epub Date: 2026-01-07 DOI: 10.17775/CSEEJPES.2025.02310

Tianming Gu;Puyu Wang;Jianyu Wang;Wei Yao;Xiao-Ping Zhang

引用次数: 0

Unreliability Tracing of Power Systems with High Penetration of Wind Power Based on Temporal Decomposition Model 基于时间分解模型的风电高渗透电力系统不可靠性跟踪

IF 5.6 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2026-07-01 Epub Date: 2023-04-20 DOI: 10.17775/CSEEJPES.2022.03950

Yunjie Bai;Kaigui Xie;Changzheng Shao;Bo Hu;Xueying Yu;Yinzhe Hu

{"title":"Unreliability Tracing of Power Systems with High Penetration of Wind Power Based on Temporal Decomposition Model","authors":"Yunjie Bai;Kaigui Xie;Changzheng Shao;Bo Hu;Xueying Yu;Yinzhe Hu","doi":"10.17775/CSEEJPES.2022.03950","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.03950","url":null,"abstract":"An unreliability tracing model for power systems assigns responsibility for unreliability to each component by quantifying its impact on the power system's reliability. This paper extends the concept of unreliability tracing to power systems with high penetration of wind power, to realize unified allocation of load shedding to conventional generating units and wind power. First, a quantitative evaluation model for load shedding is established, which considers unreliable factors, such as failures of components, fluctuation, and intermittence of wind power. Then, load shedding at a certain time is decomposed into the part due to remaining unreliable factors that happened before the last time and the part due to unreliable factors that happened between the last time and the certain time, by decomposing the load shedding formula. Next, for parameters of the second part of the load shedding formula, unreliable factors that caused the value of these parameters to be located in regions leading to load shedding are decomposed into two parts in time sequence. The second part of load shedding is also decomposed into two parts corresponding to the decomposed unreliable factors. According to the decomposition of unreliable factors, two criteria for judging whether the component is responsible are extracted. Finally, the last two parts of load shedding are allocated to each component based on assumed baseline values of these criteria for each component, and the first part of load shedding is allocated, recursively. Several systems, including a modified provincial power system, are used to validate the rationality and validity of the model.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"12 4","pages":"1874-1886"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10106202","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148749029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Coordinated Optimal Dispatching Approach for Integrated Energy System Cluster Based on Improved Deep Reinforcement Learning 基于改进深度强化学习的综合能源系统集群协调优化调度方法

IF 5.6 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2026-07-01 Epub Date: 2023-06-27 DOI: 10.17775/CSEEJPES.2022.05510

Suyang Zhou;Wennan Zhuang;Wei Gu;Kaiyu Sun;Gaoyan Han;Kang Zhang;Hongkun Lyu

{"title":"Coordinated Optimal Dispatching Approach for Integrated Energy System Cluster Based on Improved Deep Reinforcement Learning","authors":"Suyang Zhou;Wennan Zhuang;Wei Gu;Kaiyu Sun;Gaoyan Han;Kang Zhang;Hongkun Lyu","doi":"10.17775/CSEEJPES.2022.05510","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2022.05510","url":null,"abstract":"Integrated energy system (IES) is becoming a mainstream form of energy system decarbonization benefiting from efficient use of multi-energy carriers and user-friendliness to distributed energy resources. Along with development of IES, coordinated operation is necessary to further improve general efficiency of the IES cluster. Conventional distributed optimization methods are difficult to coordinate to optimize IES cluster operation, considering the balance of computational time, convergence performance, and initial value determination. This paper proposes a coordinated optimal dispatching approach for the IES cluster based on improved deep reinforcement learning. First, a distributed scheduling framework of the IES cluster with a cluster energy coordination center (CECC) as the upper coordinator and several area energy management centers (AEMCs) as the lower managers is introduced. Then, the energy interaction model and pricing strategy in the IES cluster that can facilitate multi-energy transactions are established. Finally, an improved multi-agent deep deterministic policy gradient (MADDPG) algorithm with a compression mechanism of initial state space is proposed for the model solution. Results show that compared with the conventional distributed algorithm of the alternating direction method of multipliers (ADMM), the improved MADDPG increases solving speed by 40 times while guaranteeing convergence and optimality of the solution. Besides, after considering energy transactions among IESs in the cluster, the total operating cost is reduced by 9.74%, and the self-sufficient ratio is raised to 0.92, reflecting the necessity of energy complementarity.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"12 4","pages":"2086-2105"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10165673","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148746970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-Driven Convex Optimal Power Flow Approximation for Uncertainty-Aware Static Voltage Stability Margin Calculation 不确定性感知静态电压稳定裕度计算的数据驱动凸最优潮流逼近

IF 5.6 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2026-07-01 Epub Date: 2024-09-19 DOI: 10.17775/CSEEJPES.2023.03410

Wanbin Liu;Shunjiang Lin;Qifeng Li

{"title":"Data-Driven Convex Optimal Power Flow Approximation for Uncertainty-Aware Static Voltage Stability Margin Calculation","authors":"Wanbin Liu;Shunjiang Lin;Qifeng Li","doi":"10.17775/CSEEJPES.2023.03410","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2023.03410","url":null,"abstract":"When taking the uncertainty of the renewable energy source (RES) output in a power system into account, the uncertain fluctuation of RES will lead to the deviation of the power system responses' evolution. This evolution further affects the static voltage stability (SVS) margin value determined by the maximum load growth parameter. The SVS margin (SVSM) can be calculated based on the optimal power flow (OPF) method. The uncertain injected bus power and non-convex extended power flow equation constraints make the OPF model of SVSM calculation difficult to solve. To address these problems, an uncertainty-aware model (UaM) is established to identify the convex relationship represented by the uncertain non-convex extended power flow equations when the load growth parameter reaches SVSM. Based on historical data samples of the system, the UaM model establishes a training model to obtain a new convex relationship. By proposing an improved relaxed least absolute shrinkage and selection operator (LASSO) regression, the calculation efficiency and accuracy of the UaM-based training model are improved. Case studies on IEEE 14, 39 and 118-bus systems indicate that the UaM-based training model can capture the uncertainties of injected bus power to reduce the influence of RES power's predicted errors on the calculation results. The proposed improved relaxed LASSO regression can increase the calculation efficiency of the SVSM result compared with the regular regressions.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"12 4","pages":"1778-1790"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684472","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148747091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transient Stability Enhancement of Grid-forming Inverters with Controllable Frequency Deviation via Acceleration Power Control 利用加速度功率控制提高频率偏差可控并网逆变器的暂态稳定性

IF 5.6 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2026-07-01 Epub Date: 2026-03-20 DOI: 10.17775/CSEEJPES.2025.04940

Xu Wu;Huafeng Xiao;Cunwen Tang;Wei Wang;Ming Cheng

{"title":"Transient Stability Enhancement of Grid-forming Inverters with Controllable Frequency Deviation via Acceleration Power Control","authors":"Xu Wu;Huafeng Xiao;Cunwen Tang;Wei Wang;Ming Cheng","doi":"10.17775/CSEEJPES.2025.04940","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2025.04940","url":null,"abstract":"Promoted by the extensive integration of distributed power resources, grid-connected inverters are progressively expected to function as grid-forming units. This requires them to not only regulate grid voltage and frequency but also provide inertia to compensate for the decline in traditional synchronous generation. Current studies on grid-forming inverters (GFMIs) have primarily focused on small-signal stability. However, the transient stability during voltage sags has not been adequately addressed. In this paper, the transient stability of GFMI is analyzed with the phase portrait, and an acceleration power control scheme is first proposed, which effectively constrains frequency deviations during both fault occurrence and clearance processes without requiring the estimation of voltage sag depth or line impedance. Remarkably, the proposed method ensures maintained synchronization stability of GFMIs even under severe grid faults. Finally, a 500W experimental platform is constructed in our lab to verify the effectiveness of the transient stability enhancement method.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"12 4","pages":"2007-2018"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11449502","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148748237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Economic Dispatch in Microgrids with Photovoltaic and Load Communication Failures Using Deep Reinforcement Learning with Relative Entropy Regularized Asynchronous Update 基于相对熵正则化异步更新深度强化学习的光伏和负载通信故障微电网经济调度

IF 5.6 2区工程技术

CSEE Journal of Power and Energy Systems Pub Date : 2026-07-01 Epub Date: 2025-11-05 DOI: 10.17775/CSEEJPES.2024.05320

Wencheng Liu;Zhizhong Mao

{"title":"Economic Dispatch in Microgrids with Photovoltaic and Load Communication Failures Using Deep Reinforcement Learning with Relative Entropy Regularized Asynchronous Update","authors":"Wencheng Liu;Zhizhong Mao","doi":"10.17775/CSEEJPES.2024.05320","DOIUrl":"https://doi.org/10.17775/CSEEJPES.2024.05320","url":null,"abstract":"Microgrids are a crucial component of modern energy internet, offering reliable distributed generation solutions. However, communication failures in data acquisition terminals, caused by long-distance transmission and electromagnetic interference, can lead to data loss and negatively impact economic dispatch accuracy. This study introduces a novel deep reinforcement learning algorithm, the Relative Entropy Regularized Asynchronous Update Soft Actor-Critic algorithm, to address these challenges. First, the algorithm compensates for missing data during communication interruptions using predictive modeling techniques, thereby ensuring continuous and accurate system operation. Then, to handle the challenges posed by prediction errors, a relative entropy regularization strategy is applied during training to maintain policy stability. Finally, upon communication restoration, the algorithm asynchronously updates the reward function using actual historical data to correct cumulative errors introduced by the predictive model. Results demonstrate that this method significantly enhances economic efficiency under photovoltaic and load communication failures.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"12 4","pages":"1716-1727"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11230284","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148749228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0