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Coordinated Flexibility Provision Strategy for Multi-Area Interconnected IEHS

IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2025年第1期61卷 1675-1682页

作者： Jiao, Min Li, Peng Yang, Ming Wang, Qiushi Han, Longxiao Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China

To enhance the flexibility support and uncertainty mitigation capability of power system, a novel coordination framework is developed to efficiently manage the operational flexibility in a multi-area interconnected energy system that is integrated the electricity system and heating system. This presented approach introduces the term "credible flexibility capacity" to characterize the available flexibility shared to other systems, which considers the transmission time delays, heat losses of district heating system (DHS), and uncertainty from renewable energy generation. Meanwhile, to improve renewable energy accommodation benefit, the operational risk resulting from wind power uncertainty is also identified to make a tradeoff between the operational costs and wind power accommodation risk in interconnected systems. And a decentralized coordinated robust dispatch model is then established based on the alternating direction multiplier method to coordinate operational flexibility capacity among multi-area interconnected energy systems, which significantly improve the flexibility capacity utilization efficiency and effectively enhance the uncertainty mitigation capability. Finally, case studies are carried out to verify the validity of the proposed coordinated dispatch strategy.

关键词： Heating systems Wind power generation Pipelines Delay effects Costs Wind farms Uncertainty Coordinated dispatch credible flexibility capacity dynamic characteristics flexibility sharing multi-area interconnected energy system

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Optimizing battery deployment: Aging trajectory prediction enabling homogenous performance grouping

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Journal of Energy Chemistry 2025年第1期100卷 565-577页

作者： Shuquan Wang Feng Gao Zhan Ma Hao Tian Yusen Zhang School of Control Science and Engineering Shandong UniversityJinan 250061ShandongChina Key Lab of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan 250061ShandongChina

As battery deployments in electric vehicles and energy storage systems grow, ensuring homogeneous performance across units is crucial. We propose a multi-derivative imaging fusion(MDIF) model, employing advanced imaging and machine learning to predict battery aging trajectories from minimal initial data, thus facilitating effective performance grouping before deployment. Utilizing a derivative strategy and Gramian Angular Difference Field for dimensional enhancement, the MDIF model uncovers subtle predictive features from discharge curve data after only ten cycles. The architecture includes a parallel convolutional neural network with lateral connections to enhance feature integration and *** on a self-developed dataset, the model achieves an average root-mean-square error of 0.047 Ah and an average mean absolute percentage error of 1.60%, demonstrating high precision and *** robustness is further validated through transfer learning on two publicly available datasets, adapting with minimal retraining. This approach significantly reduces the testing cycles required, lowering both time and costs associated with battery testing. By enabling precise battery behavior predictions with limited data, the MDIF model optimizes battery utilization and deployment strategies, enhancing system efficiency and sustainability.

关键词： Lithium-ion battery Battery prognostics Fusion model Convolutional neural network Transfer learning

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A Short-Term Voltage Stability Evaluation Method Combining Data-Driven and Mechanism Criterion

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IEEE TRANSACTIONS ON power systemS 2025年第2期40卷 1891-1902页

作者： Li, Baoluo Xu, Shiyun Li, Zonghan Sun, Huadong Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250014 Peoples R China China Elect Power Res Inst Beijing 100192 Peoples R China

In order to accurately and quickly assess the short-term voltage stability (STVS) of a power system, this paper utilizes a data-driven method to enhance the power current criterion (PCC) to form a real-time assessment method for STVS. First, the fixed voltage threshold adopted by PCC is taken as the parameter to be enhanced, and the labeling method of dynamic threshold and the data set generation scheme are proposed. Then, Gate recurrent unit (GRU) network is utilized to establish the mapping relationship between the voltage trajectory and the dynamic threshold, and a penalty loss function is designed based on the classification principle of the criterion to enhance the usability of the prediction threshold. Finally, a set of time-adaptive evaluation scheme for online applications is proposed. The scheme first utilizes PCC to monitor the system, and then combines the dynamic threshold provided by GRU to complete the evaluation. Compared with traditional methods, the proposed method has good accuracy, timeliness and interpretability. In particular, the method is directly oriented to the measurement data, and its monitoring scope can adapt to the observability of the power grid. Test results in CSEE-VC(88-2023) and actual power grid validate the effectiveness of the proposed method.

关键词： power system stability Indexes Stability criteria Accuracy Threshold voltage Circuit faults Monitoring Short term voltage stability power current criterion data-driven model-free

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Partial Solution Operator Discretization-Based Methods for Efficiently Computing Least-Damped Eigenvalues of Large Time Delayed power systems

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CSEE Journal of power and Energy systems 2025年第2期11卷 671-682页

作者： Hua Ye Xiaofan Jia Muyang Liu Yutian Liu Sicong Zhang Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of EducationShandong UniversityJinan 250061China School of Electrical Engineering Xinjiang UniversityUrumqi 830046China State Grid Jiangsu Electric Power Research Institute Nanjing 211103China

To investigate impact of time delays on the small signal stability of power systems, the least-damped eigenvalues with the smallest damping ratios have been calculated by eigen-analysis methods based on Solution Operator Discretization (SOD) with Pseudo-Spectral collocation (PS) and Implicit Runge-Kutta (IRK) methods. This paper evolves SOD-PSIIRK into their partial counterparts, i.e., PSOD-PSIIRK, with greatly enhanced efficiency and reliability in analyzing large-scale time delayed power systems. Compared with SOD-PSIIRK, PSOD-PSIIRK are characterized in constructing low order discretization matrices of solution operator as well as efficiently and directly solving the embedded Matrix-Inverse-Vector Products (MIVPs). The dimensions of the discretization matrices of solution operator are largely reduced as only the retarded state variables are discretized, rather than all state variables as in SOD-PSIIRK. Meanwhile, the proposed PSOD-PSIIRK optimize the most computationally expensive operations in SOD-PSIIRK by avoiding the iterative solutions to the two embedded MIVPs. PSOD-PS/IRK directly and efficiently compute the MIVPs via factorizing the Kronecker product-like discretization matrices of the solution operator into Schur complements. The Central China-North China ultra-high-voltage power grid with 80577 state variables serves to validate the proposed PSOD-PSIIRK and shows that compared with SOD-PSIIRK, the computational time consumed by PSOD-PSIIRK is cut down by 49.96 times without loss of any accuracy.

关键词： Eigenvalue analysis low frequency oscillation Schur complement decomposition small signal stability solution operator discretization spectral discretization time delay wide-area measurement system

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Cooperative optimal operation of multi-microgrids and shared energy storage for voltage regulation of distribution networks based on improved Nash bargaining

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2025年 166卷

作者： Zhang, keyu Chen, Jian Qi, Xianglong Zhang, Wen Wei, Meijia Lin, Da Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China State Grid Zhejiang Elect Power Res Inst Hangzhou 310004 Peoples R China

The increasing penetration rate of distributed generation will bring serious voltage violation issues to the distribution networks (DNs). As an effective organization form of distributed generation, microgrids (MGs) have flexible adjustment ability, which can provide voltage support for DNs. To enhance the energy economy and scheduling flexibility of MGs, shared energy storage system (SESS) has received widespread attention as a new type of energy storage technology. To this end, this paper proposes a cooperative optimal operation strategy of MGs and SESS aimed at voltage regulation in DNs. A two-stage cooperative optimization model based on Nash bargaining theory is established for MGs and SESS. In the first stage, the DN is partitioned using an improved electrical distance approach that incorporates voltage regulation incentives, with the objective of minimizing the cooperation costs for MGs and SESS. The second stage involves quantifying the contributions of each participant through a nonlinear energy mapping function, followed by the development of the trading price based on asymmetric bargaining informed by improved Nash bargaining. The goal of this approach is to ensure that MGs and SESS share cooperative benefits fairly. The alternating direction method of the multiplier (ADMM) is used to solve the problems, effectively protecting the privacy of each participating subject. Finally, the effectiveness of the proposed method is demonstrated through an analysis of the improved IEEE 33-node system.

关键词： Distribution network partition Multi-microgrids Shared energy storage system Voltage regulation incentives Asymmetric Nash bargaining

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Integrated dispatching Model for power system Incorporating Multiple Modules 5

Integrated Dispatching Model for Power System Incorporating ...

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5th International Conference on Advances in Electrical, Electronics and Computing Technology, EECT 2025

作者： Xu, Chang Wang, Mingqiang Wang, Zihan Zhang, Yizhe Wang, Jialiang Sun, Fengbin Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

ISBN: (纸本)9798331541545

The widespread integration of renewable energy presents significant challenges for power system scheduling. Traditional power system scheduling is mainly based on the concept of "coordinating on a multi-time-level and gradually refining at each level," using a sequential scheduling framework. However, with the growing integration of renewable energy, the uncertainty in power systems has significantly increased, leading to severe issues such as conflicts in the coordination between different modules. This paper first introduces the scheduling framework of the traditional sequential scheduling model. Then, addressing the problems of module coordination and insufficient flexibility, an integrated multi-time-scale scheduling model is proposed. This model combines day-ahead and intraday scheduling models, optimizing decision variables including unit start/shut states, operation points, and reserves simultaneously to maximize the collaborative potential between different scheduling modules. After linearization, the proposed model is converted into a mixed-integer linear programming (MILP) model, which can be solved directly using commercial optimization solvers. Finally, case analyses demonstrate the effectiveness and superiority of the proposed integrated model compared to the traditional sequential scheduling model. © 2025 IEEE.

关键词： Integer programming

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Two-layer multi-timescale rolling optimization of electric-hydrogen hybrid energy storage systems considering renewable energy uncertainties

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2025年 106卷 305-317页

作者： Wei, Meijia Chen, Jian Zhang, Wen Chen, Yang Zhang, keyu Lin, Da Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China State Grid Zhejiang Elect Power Res Inst Hangzhou 310004 Peoples R China

To address the variability in the scheduling timescale of electric and hydrogen energy and the high uncertainties caused by the high proportion of renewable energy, this paper proposes a two-layer multi-timescale rolling optimization method for electric-hydrogen hybrid energy storage systems (EH-HESS) considering renewable energy uncertainties. In the upper-layer long-timescale optimization, a fuzzy set of wind turbine (WT) and photovoltaic (PV) generation forecast errors is established based on the Wasserstein distance, and a distribution robust optimization (DRO) model is proposed for energy scheduling. In the lower-layer short-timescale optimization, typical scenarios are generated for the potential distribution of WT and PV generation. After receiving the upper-layer scheduling results, a short-timescale power scheduling model is established. The lower-layer scheduling results are passed back to the upper-layer to achieve a two-layer multi-timescale rolling optimization. Simulations show that the proposed method can achieve inter-day transfer of hydrogen energy, reduce the daily imbalanced electric energy and effectively suppress the fluctuation of WT and PV generation. Moreover, the method demonstrates notable economic benefits, higher by 21.71% and 18.87% respectively, than singletimescale energy storage and robust optimization (RO), enabling a balance between economy and robustness. Finally, a detailed sensitivity analysis is conducted to show the effect of the fuzzy set radius on the scheduling results.

关键词： Electric-hydrogen hybrid energy storage systems (EH-HESS) Two-layer multi-timescale rolling optimization Distribution robust optimization (DRO) Typical scenarios generation Uncertainties

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Optimal Scheduling Considering Multiple Reserves Based on Active power Curtailment Operation of Wind power 5

Optimal Scheduling Considering Multiple Reserves Based on Ac...

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5th International Conference on Advances in Electrical, Electronics and Computing Technology, EECT 2025

作者： Wang, Zihan Wang, Mingqiang Xu, Chang Wang, Jialiang Zhang, Yizhe Liang, Caishuai Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

ISBN: (纸本)9798331541545

Under the current general trend of the power industry's transformation towards clean energy, wind power generation, as an important form of renewable energy utilization, is steadily increasing its proportion in the power system. However, the inherent volatility and uncertainty of wind power bring numerous challenges to the stable operation of the power system. Firstly, based on the traditional unit commitment model, this paper comprehensively considers the capacity reserve and ramping reserve of the power system, and constructs a unit commitment model that considers the supply and demand constraints of both types of reserves simultaneously. Then, on the basis of this model, an in-depth and comprehensive discussion is carried out, focusing on the key operation strategy of the active power curtailment operation of wind power. This not only helps to improve the power system's ability to accommodate wind power, but also enables a better response to the challenges of volatility and uncertainty brought by wind power to the power system, thus ensuring the safe, stable and economic operation of the power system. Finally, the model is transformed into a mixed-integer linear programming model that can be directly called by the commercial solver CPLEX, and the effectiveness of the model is verified by a modified IEEE 26-node distribution network. © 2025 IEEE.

关键词： Integer programming

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Grid Strength Assessment Method for Evaluating Small-signal Synchronization Stability of Grid-following and Grid-forming Converters Integrated systems

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Journal of Modern power systems and Clean Energy 2025年第1期13卷 55-65页

作者： Qianhong Shi Wei Dong Guanzhong Wang Junchao Ma Chenxu Wang Xianye Guo Vladimir Terzija Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical EngineeringShandong UniversityJinan 250061China Electric Power Research Institute State Grid Zhejiang Electric Power Co.Ltd.Hangzhou 310014China School of Engineering Newcastle UniversityNewcastle upon TyneUK

Oscillations caused by small-signal instability have been widely observed in AC grids with grid-following(GFL)and grid-forming(GFM)*** generalized short-circuit ratio is commonly used to assess the strength of GFL converters when integrated with weak AC systems at risk of *** paper provides the grid strength assessment method to evaluate the small-signal synchronization stability of GFL and GFM converters integrated ***,the admittance and impedance matrices of the GFL and GFM converters are analyzed to identify the frequency bands associated with negative damping in oscillation modes dominated by heterogeneous synchronization ***,based on the interaction rules between the short-circuit ratio and the different oscillation modes,an equivalent circuit is proposed to simplify the grid strength assessment through the topological transformation of the AC *** risk of sub-synchronization and low-frequency oscillations,influenced by GFL and GFM converters,is then reformulated as a semi-definite programming(SDP)model,incorporating the node admittance matrix and grid-connected device *** effectiveness of the proposed method is demonstrated through a case analysis.

关键词： Grid-following converter grid-forming converter grid strength assessment small-signal stability

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A correction method for wind power forecast considering the dynamic process of wind turbine icing

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ELECTRIC power systemS RESEARCH 2025年 246卷

作者： Yang, Ming Zhou, Haoyang Li, Menglin Wang, Bo Wang, Fei Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China Shandong Univ Shandong Key Lab Digital Smart Energy Jinan 250061 Peoples R China China Elect Power Res Inst State Key Lab Operat & Control Renewable Energy & Beijing 100192 Peoples R China

In order to improve the accuracy of wind power forecast (WPF) in wind turbine icing scenarios, this paper proposes a methodology for the correction of WPF that takes into account the impact of dynamic ice accumulation processes. Firstly, the icing calculation formula applicable to wind turbine blades is derived based on the Makkonen model. Concurrently, multiple sets of simulations are performed by FENSAP-ICE software to obtain the key parameters of icing calculation formula under discrete weather conditions. Then, the Kriging interpolation algorithm is introduced to construct continuous mapping functions from weather conditions to icing parameters, allowing real-time icing degree can be calculated using the icing formula derived from numerical weather prediction (NWP) data, thereby describing the dynamic icing process. Finally, an additional correction model based on few-shot learning is proposed, which can maintain good forecast performance with sparse ice cover samples. By forecasting wind power loss under varying icing conditions, the model corrects the WPF results, and the case studies demonstrate that after applying the proposed methodology, the accuracy of WPF under icing conditions is significantly improved.

关键词： Wind turbine blade ice cover Numerical simulation Kriging interpolation Wind power forecast Few-shot learning

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