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9th Purple Mountain Form on Smart Grid Protection and control, PMF 2024

作者： Wei, Xiaoqiang Liu, Naiyuan He, Zhifeng Yang, Hao Sun, Zhenglong State Grid Heilongjiang Electric Power Company Limited Harbin150000 China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132000 China

ISBN: (纸本)9789819616701

There is an urgent need to address the transient synchronization stability (TSS) problem caused by the increasing penetration of renewable resources into the power network through grid-following converters (GFL-VSCs). It is challenging to analyze the TSS in power systems with high penetration of renewable resources due to the complex interaction between a large number of GFL-VSCs and power network. Although some research has been carried out on TSS assessment of GFL-VSC systems, its application is limited because measuring the numerous internal parameters of distributed converters is hard. To fill this gap, this paper proposes a TSS analysis method using local network measurements. The present study first constructs a port energy function for PLL-controlled converters, establishing the relationship between the internal control and the transient energy of the converter. Secondly, the branch energy function is constructed using the law of energy conservation. Due to transient energy interactions between the converters and the branches, the transient instability characteristics of the converters are mapped into the network. Transient instability characteristics are extracted through PMUs in the network. On this basis, the TSS of the GFL-VSC systems is analyzed through the identified critical branches. Finally, the effectiveness of the proposed method is validated through simulations on the modified IEEE 39-BUS system and a practical power system. © State Grid Electric power 2025.

关键词： Transient stability

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Master-Slave Game Strategy for Electric Heating Load Group Considering Differences of Heterogeneous Household Types and Aggregation Structure

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Dianli Xitong Zidonghua/Automation of Electric power systems 2025年第10期49卷 58-66页

作者： Yang, Mao Wang, Jinxin Fang, Guozhong Zhu, Yidan Wang, Yuxin Su, Xin Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Northeast Branch of State Grid Corporation of China Shenyang110179 China

The regulation capability of the new power system dominated by renewable energy at the source side is gradually deteriorating. Exploiting the load-side regulation potential to participate in demand response has become an important approach to enhance grid regulation capacity. Firstly, taking distributed residential electric heating clusters as the research object, a dynamic model of temperature-varying power is established for electric heating rooms based on the building thermodynamics theory. Secondly, the impacts of household type differences and aggregated household proportions on the regulation capability of heating load clusters are investigated. A refined aggregation model for heating load clusters considering the differences of heterogeneous household types and aggregation structure is established, with adjustable electricity quantified as an indicator to measure the regulation potential of heating load clusters. Then, a master-slave game model is constructed with the load aggregator (LA) as the leader and cluster users as followers. The quantified adjustable electricity of load clusters is incorporated into the game model as flexible resources to participate in demand response. The upper-level game model establishes an LA pricing model to formulate electricity scheduling plans and optimal heating electricity prices within the system, while the lower-level develops a user payment cost model where users determine their heating schedules based on the electricity prices. Finally, case studies verify that the proposed game model can effectively stimulate the demand response potential of users with the differences of heterogeneous household type, achieving economic benefits for both LA and users. © 2025 Automation of Electric power systems Press. All rights reserved.

关键词： Cooling

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Analysis of Frequency Dynamic Distribution Characteristics in Chain-structured power system with renewable energy Integration

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Dianli Xitong Zidonghua/Automation of Electric power systems 2025年第10期49卷 49-57页

作者： An, Jun Shi, Yan Cao, Shuai Zhou, Yibo Li, Kexin Zhang, Wanxiang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Northeast Branch of State Grid Corporation of China Shenyang110179 China

The integration of renewable energy generation, represented by wind power, into the power system has a significant impact on frequency security, and the characteristics of frequency distribution have gradually become a focal point of attention. To study the influence of wind power integration into multi-machine systems on frequency distribution characteristics, based on the frequency response characteristics of the"grid, source, and load"sides, this paper constructs an analytical model of the frequency response distribution characteristics of a multi-machine system with wind power, and analyzes the impact mechanism of wind power integration on the frequency distribution characteristics. Then a multi-dimensional quantification index system is developed to describe the relative dispersion and absolute differences in frequency response. Next, the validity of the mechanism model is verified using a simple chain-structured power system with"generation-transmission-reception", and the influence rules of electrical distance, wind power integration location, and disturbance location on the frequency distribution characteristic indices are analyzed. Finally, the influence rules of distribution characteristics are analyzed and verified in an actual large-scale power system with a high proportion of renewable energy. © 2025 Automation of Electric power systems Press. All rights reserved.

关键词： Wind power integration

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Bi-level Optimization Strategy of Grid-side Multiple energy Storage Stations Considering Available Capacity and Frequency Regulation Cost

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Dianli Xitong Zidonghua/Automation of Electric power systems 2025年第10期49卷 101-111页

作者： Li, Junhui Song, Qinglong Guo, Qi Yan, Jun Li, Cuiping Hao, Qianpeng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Co. Ltd. Hohhot010020 China School of Future Technology Tianjin University Tianjin300350 China

Aiming at the problem that some energy storage stations in the region lose charging/discharging capability in advance due to uneven distribution of frequency regulation instructions, resulting in insufficient response ability of subsequent frequency regulation demand, a bi-level optimization strategy of grid-side multiple energy storage stations considering available capacity and frequency regulation cost is proposed. The proposed strategy includes the frequency regulation power distribution layers of energy storage stations and energy storage units. The upper layer introduces the available capacity state coefficient and the adaptive coefficient about the adjustment ability of energy storage resources, and designs the optimal distribution model of frequency regulation power partition of energy storage station to realize the balanced distribution of frequency regulation power in each energy storage station. The lower layer takes into account the state of health (SOH), the resistance coefficient, and the balanced recovery of the state of charge (SOC) for the energy storage unit to construct the objective function, so as to prioritize the recovery of SOC for energy storage units with high SOH. The simulation results show that the proposed strategy can improve the response ability of the energy storage resources in the region and realize the maximum utilization of energy storage resources while ensuring a certain economy. © 2025 Automation of Electric power systems Press. All rights reserved.

关键词： Electric power utilization

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Aggregation Modeling of system Frequency Response Under Inertia control of Grid-following Direct-drive Wind Turbine

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Dianli Xitong Zidonghua/Automation of Electric power systems 2025年第10期49卷 39-48页

作者： Jiang, Chao Yang, Dongfeng Guo, Shujia Liu, Xiaojun Zhou, Shuyu Cao, Zhichong Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China School of Automation and Electrical Engineering Zhejiang University of Science and Technology Hangzhou310023 China State Grid Jilin Electric Power Research Institute Changchun130000 China

The inertia control of grid-following direct-drive wind turbines significantly influences the system frequency response pattern afrer disturbances. However, current research has not clearly identified the dominant response link of direct-drive wind turbines in frequency regulation, while the modeling is too complicated to be suitable for frequency characteristic analysis. Therefore, the linearized models under inertia control are derived for two typical types of direct-drive wind turbines according to the aerodynamic equations, generator models, power control link, and control circuit structure. The fast physical process of current control-boost circuit/stator voltage dynamic loop is clearly understood and reasonably ignored. It is revealed that the two types of direct-drive wind turbines have a common frequency response mechanism which can be described as the cascade effect of the speed regulator-wind rotor motion equation. Furthermore, combined with the frequency response model of synchronous unit, the aggregation model of system frequency response under the inertia control of grid-following direct-drive wind turbines is constructed, and the aggregation model is reduced to a second-order model by the balance truncation method for analytical calculation of frequency extremes. The accuracy and applicability of the aggregation model and its reduced-order model are verified by MATLAB/Simulink simulation, and the influence of control parameters and system states on frequency dynamic characteristics and stability margin is analyzed. © 2025 Automation of Electric power systems Press. All rights reserved.

关键词： Electric power system control

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Adaptive Adjustment Method for Grid-forming energy Storage Parameters Based on Buffer Functions and Damping Switching

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Dianli Xitong Zidonghua/Automation of Electric power systems 2025年第10期49卷 77-86页

作者： Cui, Yang Ma, Boyu Dai, Hanyang Ma, Xin Zhao, Yuting Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China China Electric Power Research Institute Beijing100192 China Electric Power Research Institute of State Grid Ningxia Electric Power Ltd. Co. Yinchuan750002 China

In the development tendency of high penetration of renewable energy and power electronic devices in new power systems, the grid-forming control technology for renewable energy integration mitigates the system stability issues caused by insufficient inertia and damping. However, it also reduces the dynamic regulation performance of the system. This paper proposes an adaptive adjustment method for grid-forming energy storage parameters based on buffer functions and steady-state/transient-state damping switching, to improve the dynamic regulation performance of the system. Firstly, the buffer functions are used in inertia adjustment to enhance the regulation smoothness of the system. Secondly, a steady-state/transient-state damping switching link is introduced in the damping adjustment to reduce the steady-state error of active power output during the frequency reduction process. Thirdly, the fuzzy control is employed to introduce correction terms for inertia and damping, and the stability of the proposed method is analyzed. Finally, simulations validate the effectiveness of the proposed method in enhancing small-signal stability and power response dynamic performance of the system. © 2025 Automation of Electric power systems Press. All rights reserved.

关键词： Electric power transmission networks

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Optimized Strategies for Peak Shaving and BESS Efficiency Enhancement through Cycle-Based control and Cluster-Level power Allocation

arXiv

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arXiv 2025年

作者： Gan, Guo Junhui, Li Gang, Mu Gangui, Yan Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China

Battery energy Storage systems (BESS) are essential for peak shaving, balancing power supply and demand while enhancing grid efficiency. This study proposes a cycle-based control strategy for charging and discharging, which optimizes capture rate (CR), release rate (RR), and capacity utilization rate (CUR), improving BESS performance. Compared to traditional day-ahead methods, the cycle-based approach enhances operational accuracy and reduces capacity waste, achieving a CUR increase from 75.1% to 79.9%. An innovative cluster-level power allocation method, leveraging an improved Particle Swarm Optimization (PSO) algorithm, is introduced. This strategy reduces daily energy loss by 174.21 kWh (3.7%) and increases BESS efficiency by 0.4%. Transient and steady-state energy loss components are analyzed, revealing that transient loss proportion decreases significantly as power depth increases, from 27.2% at 1 MW to 1.3% at 10 MW. simulations based on a detailed Simulink/Simscape model validate these methods, demonstrating enhanced peak shaving effectiveness and prolonged BESS lifespan by reducing equivalent cycles. The study provides a robust framework for optimizing BESS performance and efficiency in real-world applications. Copyright © 2025, The Authors. All rights reserved.

关键词： Charge storage

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A framework of day-ahead wind supply power forecasting by risk scenario perception

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IEEE Transactions on Sustainable energy 2025年

作者： Yang, Mao Huang, Yutong Wang, Zhao Wang, Bo Su, Xin Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Jilin132012 China China Electric Power Research Institute State Key Laboratory of Operation and Contr Ol of Renewable Energy & Storage Systems Beijing100912 China

Wind power forecasting (WPF) systems are essential to maintain the safe and stable operation of the power system in case of large-scale grid-connected wind farms. However, the current forecasting has the problem of disunity between statistical value and application value, that is, it only pays attention to its forecasting accuracy and ignores the risks caused by it in the power system. In order to solve the above problems, this study proposes a framework of wind supply power forecasting (WSPF) for wind farm cluster, which takes into account the risk scenario perception. First of all, aiming at the predicted risk phenomenon in WPF, TimesNet combined with the fluctuation information of Numerical Weather Prediction (NWP) wind speed is used to identify the corresponding risk scenarios. Secondly, the effective consumption area and power supply risk area evaluation index, as well as the accuracy of WSPF are defined, and the optimal forecasting curve correction scheme is fitted according to the index. Thirdly, taking into account the correction scheme and identification results, a variety of predictors are used to verify the WSPF according to the above framework. Finally, the proposed method is applied to a wind farm cluster in Inner Mongolia Autonomous region of China, the average accuracy of WSPF has increased by 37%, which verifies the effectiveness and universality of this method. © 2010-2012 IEEE.

关键词： Wind forecasting

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Extraction and application of intrinsic predictable component in day-ahead power prediction for wind farm cluster

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energy 2025年 328卷

作者： Yang, Mao Jiang, Renxian Yu, Xinnan Wang, Bo Su, Xin Ma, Chenglian The Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing100912 China

With the continuous updating and iteration of artificial intelligence algorithms, prediction models emerge one after another, but the research and utilization of the predictability of wind power is still less. Therefore, this paper proposed a day-ahead power prediction method for Wind Farm Cluster (WFC) based on intrinsic predictable component extraction. Firstly, based on the difference of power distribution between wind farm and WFC, a method of Wind power Curve (WPC) modeling for WFC is proposed, which provides the basis for establishing the Final Set of Wind power Curve (FSWPC). Secondly, the Intrinsic Predictable Component (IPC) of wind power is extracted based on the FSWPC, and the Interference Component (IC) of wind power is separated to eliminate the influence of IC on IPC in the process of prediction. Thirdly, the historical similarity matching method with large threshold is used to predict the IC to make up for the numerical deficiency of the IPC. Finally, the proposed method was applied to a WFC in China to verify its effectiveness. Compared with the traditional prediction strategy, the NRMSE, NMAE and MAPE are reduced by 1.59 %, 1.15 % and 6.42 %, respectively. © 2025 Elsevier Ltd

关键词： Iterative methods

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A Short-Term power Prediction Method for Wind Farm Cluster Based on Time Dynamic Graph Network and Improved Transformer Model

A Short-Term Power Prediction Method for Wind Farm Cluster B...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Chao Han Zihang Chen Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China Jiangmen Power Supply Bureau of Guangdong Power Grid Co. Ltd Jiangmen China

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

In recent years, wind power has gradually replaced thermal power as the main source of new energy generation. Wind power prediction in advance can help formulate scheduling strategies and improve the stability of the power system. With the advent of the Industry 4.0 and the widespread application of artificial intelligence technology, artificial algorithms have been extensively used in the field of wind power prediction. To further explore the spatiotemporal correlation of every wind farm in the wind farm cluster, a temporal dynamic graph network is used to divide the wind farm farm into several sub-clusters. Then, the KAN-BiLSTM-Transformer algorithm is used to predict wind power of each wind sub-cluster. Finally, the wind power of each sub-cluster is added to attain the final predicted power of the wind farm cluster. After verification, the RMSE and MAE of the proposed method is 0.06849 and 0.05805 respectively, with an accuracy of 93.15%, which is superior to the compared algorithms. Proposed method can provide more accurate prediction results.

关键词： Accuracy Heuristic algorithms Clustering algorithms Wind power generation Wind farms Predictive models Prediction algorithms Transformers Spatiotemporal phenomena Wind forecasting

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