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检索条件"机构=State Key Laboratory of Intelligent Power Grid Protection and Operation Control"

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Effect of Battery Energy Storage System Frequency Regulation on Frequency Characteristic of power Systems

Effect of Battery Energy Storage System Frequency Regulation...

引用

2022 IEEE International Conference on power Systems and Electrical Technology, PSET 2022

作者： Deng, Lijun Huang, Libin Cai, Haiqing Hu, Yun Liao, Mengjun Huang, Yunhui China Southern Power Grid Research Institute Co. Ltd Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China Wuhan University of Technology Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Wuhan China

ISBN: (纸本)9781665489157

This paper investigates the impact of battery energy storage system (BESS) frequency regulation on frequency characteristic of power systems. To begin with, a model of BESS participating in frequency regulation of power systems is established for analyzing effects of BESS control dynamics on grid frequency characteristic. And the analysis model is proved by comparison with time domain model. Furthermore, grid frequency characteristic analysis with including BESS frequency regulation is studied. Virtual inertia control and virtual inertia frequency control of BESS are investigated for Participate in power grid frequency regulation. Finally, Influence of energy storage inertia and primary frequency regulation control on system frequency characteristics are investigated in Matlab/Simulink. © 2022 IEEE.

关键词： Battery storage

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Participation of wind-storage combined system in the secondary frequency regulation control strategy of power grid 2

Participation of wind-storage combined system in the seconda...

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2024 2nd International Conference on power, grid and Energy Storage, PGES 2024

作者： Cheng, Yan Dong, Cun Sun, Shumin Wang, Chenglong Song, Yu Wu, Shouyuan Huan, Jiafei Liu, Yu State Grid Shandong Electric Power Company Electric Power Research Institute China National Electric Power Dispatching and Control Center Xicheng District Beijing100031 China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Shandong Province Jinan250061 China North China Branch of State Grid Corporation of China China

The secondary frequency modulation of the unit, that is, the automatic generation control (AGC), is the process of increasing or decreasing the power of the power generation unit by the power plant unit according to the dispatching command issued by the power grid dispatching center, and then using the frequency modulator to restore the frequency. Based on the principle of AGC, this paper establishes a frequency dynamic response model of the secondary frequency modulation of the traditional unit and the wind storage participation system including load frequency control (LFC) and traditional proportional-integral-derivative (PID) controllers, determines the frequency modulation control strategy of wind storage, and uses the distribution mode based on Area control Error (ACE) signal to assist in the secondary frequency modulation. In order to solve the parameter optimization problem of the classical PID controller when the wind-storage combined system participates in the secondary frequency modulation under the large load disturbance, a parameter optimization model of the controller with PID was established, and the ITAE evaluation index was finally selected as the fitness function by comparing different fitness evaluation indexes. To overcome the problem that the conventional Particle Swarm Optimization (PSO) is prone to local extremum, the inertia weights and learning factors are adjusted nonlinearly to balance and optimize the global and local optimization capabilities and improve the search efficiency, and the parameters of the PID controller are optimized by the improved PSO algorithm. The simulation results show that the proposed algorithm improves the secondary frequency modulation effect under the background of a high proportion of renewable energy connected to the power grid. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Particle swarm optimization (PSO)

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Quantitative analysis for coupling between frequency dynamic and power angle oscillation 4

Quantitative analysis for coupling between frequency dynamic...

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4th IEEE International Conference on power, intelligent Computing and Systems, ICPICS 2022

作者： Liu, Fusuo Wang, Chao Ma, Ruicong Li, Wei Cao, Yongji Chang, Haijun Zhang, Hengxu Gao, Zhimin State Key Laboratory of Smart Grid Protection and Control NARI Group Corporation State Grid Electric Power Research Institute Nanjing China NARI Group Corporation State Grid Electric Power Research Institute Nanjing China Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

With the increasing penetration of power electronic devices, the behaviors of the power system become more and more complex. This paper analyzes the coupling characteristics between the frequency dynamics and power angle oscillation. The mechanism of frequency response and power angle oscillation is derived. The evaluation indexes are proposed to quantify the frequency response, power angle oscillation, and coupling characteristics. The coupling degree of the frequency dynamics and power angle oscillation is depicted by the Pearson correlation coefficient. The impacts of power angle oscillation on the frequency response are attained through time-domain simulation and theoretical analysis. The results show that the proposed evaluation indexes are effective to quantify the coupling characteristics. Additionally, there is positive correlation between the frequency dynamics and power angle oscillation. © 2022 IEEE.

关键词： Frequency response

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Research on Coordination Strategy of Emergency and Correction control under High Proportion of New Energy Connected to power grid 6

Research on Coordination Strategy of Emergency and Correctio...

引用

6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Liu, Fusuo Huang, Hui Chang, Haijun Wu, Xuelian Wang, Chao NARI Group Corporation/State Grid Electric Power Research Institute State Key Laboratory of Smart Grid Protection and Control Nanjin China

ISBN: (纸本)9798350347159

With the large-scale access of new energy sources, the operation mode and the uncertainty factors of the power grid increase, meanwhile the short-term power shock has an increasing impact, which exacerbates the complexity of the system frequency response characteristics and the difference in space-time distribution. Based on the analysis of principles and adaptability of emergency control and correction control, this paper comprehensively considers the operation mode and new energy access, and proposes a centralized control decision-making method based on model and trajectory driving from the perspective of global frequency control. The method also considers the continuously adjustable control resources and low voltage ride through of new energy. Finally, the practicality of the proposed method is verified based on the actual power grid simulation. © 2022 IEEE.

关键词： Decision making

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Data-Driven Early Warning for Dynamic Insecurity Risk of Hybrid AC/DC power grids

Data-Driven Early Warning for Dynamic Insecurity Risk of Hyb...

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2023 International Conference on power System Technology, powerCon 2023

作者： Yan, Jiongcheng Li, Changgang Liu, Yutian Zhu, Yuanzhen Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China Electric Power Research Institute of State Grid Shandong Electric Power Company Jinan China

ISBN: (纸本)9798350300222

The dynamic interactions between AC and DC systems and the uncertainty of renewable generation increase the risk of cascading failures and bring challenges for the secure operation of hybrid AC/DC grids. Insecurity early warning identifies the security risk and guides the control decision-making, which is important for the secure power system operation. To achieve fast insecurity early warning, a data-driven early warning method for dynamic insecurity risk is proposed in this paper. First, Latin hypercube sampling and improved K-medoids algorithm are utilized to generate typical operating conditions (OCs) in the future. Then, stacking denoising autoencoders and ensemble extreme learning machines are deployed to construct security risk assessment models to fast assess the dynamic security of typical OCs. And model update is performed to ensure the assessment accuracy when cascading failures occur. Finally, the insecure OCs are ranked into different insecure levels based on the control cost needed to ensure the system security. Simulation results of the Northwest hybrid AC/DC grid in China demonstrate that the proposed method can achieve fast insecurity early warning and effectively track the security risk tendency during the process of cascading failures. © 2023 IEEE.

关键词： Risk assessment

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Review on Risk Assessment of power System under Rainstorm-Flood and Disaster control Improvement Strategies 1

Review on Risk Assessment of Power System under Rainstorm-Fl...

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2024 1st International Conference on Smart grids and power Systems, ICSGPS 2024

作者： Wu, Wenjie Hou, Hui Zhou, Yangjun Wei, Guohui Zhang, Wei Zhong, Shiwen School of Automation Wuhan University of Technology Wuhan China Guangxi Key Laboratory of Intelligent Control and Operation and Maintenance of Power Equipment Electric Power Research Institute of Guangxi Power Grid Co. Ltd. Nanning China Guangxi Power Grid Co. Ltd. Nanning China Guangxi Power Grid Equipment Monitoring and Diagnosis Engineering Technology Research Center Electric Power Research Institute of Guangxi Power Grid Co. Ltd. Nanning China

The global warming and El Nino effects are becoming more and more obvious now. These result in frequent rainstorms, especially in coastal areas. It is necessary to deeply study evolution mechanism of rainstorm-flood disasters, assess disaster risk of power grid, and formulate efficient power grid flood control strategies. Firstly, the research progress of disaster modeling is summarized according to the disaster evolution mechanism. The differences between hydrological models and machine learning models are compared, and the possibility of combining them is discussed. Secondly, current disaster risk assessment methods of power grid and their application in rainstorm-flood disasters to quantify flood prevention capacity are reviewed. Thirdly, the power grid flood control measures are studied from the perspective of pre-disaster grid reinforcement and post-disaster repair to improve resilience. Finally, in view of the above content, the shortcomings of current researches and feasible research directions in the future are proposed. © 2024 Published under licence by IOP Publishing Ltd.

关键词： Disasters

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Assessment of Static Voltage Stability Margin for power Systems with Causal Decomposition and Reverse Feature-Enhanced Temporal Convolutional Networks

Assessment of Static Voltage Stability Margin for Power Syst...

引用

IEEE PES Asia-Pacific power and Energy Engineering Conference (APPEEC)

作者： Haifeng Zhou Xianyu Zha Qi Pan Naishuang Li Jiabin Zhang Jiacheng Liu State Key Laboratory of Smart Grid Protection and Operation Control NARI Group Corporation (China Electric Power Research Institute) Nanjing China

ISBN: (数字)9798350386127

ISBN: (纸本)9798350386134

Rapid and accurate static voltage stability assessment is crucial for the safe operation of large-scale interconnected power grids. Existing methods have failed to effectively filter key input variables in massive measurement data, limiting assessment accuracy. This study proposes an assessment method based on causal decomposition and reverse feature-enhanced temporal convolution networks. Initially, using bottom-layer measurement data as input, key variables are selected through causal decomposition, reducing the original feature set and enhancing computational efficiency. Subsequently, a reverse feature-enhanced temporal convolution model is constructed to fully mine data characteristics and achieve high precision assessment. Validation in an improved four-machine two-area simulation system demonstrates that this method significantly enhances estimation accuracy and algorithm performance while reducing the dimensionality of original variables.

关键词： Adaptation models Accuracy Correlation Convolution power system stability Predictive models Feature extraction Stability analysis Data models Convolutional neural networks

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Robust control of Bidirectional power Converter in an AC/DC Hybrid Microgrid Based on the H∞Tracking Problem 4

Robust Control of Bidirectional Power Converter in an AC/DC ...

引用

4th International Conference on power and Energy Technology, ICPET 2022

作者： Guo, Tianyu Guo, Haiping Luo, Chao Miao, Lu Huang, Libin State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China China Southern Power Grid Csg Key Laboratory for Power System Simulation Electric Power Research Institute Guangzhou China Electric Power Dispatching and Control Center of Guangdong Power Grid Guangzhou China

ISBN: (数字)9781665480796

ISBN: (纸本)9781665480796

The bidirectional power converter (BPC) in the ac/dc hybrid microgrid plays a vital role in maintaining the dynamic balance of power in the microgrid, achieving mutual support of power between the AC and the DC areas, and improving the power quality. In view of this, this paper proposes a robust control method for BPC in the ac/dc hybrid microgrid based on the H∞ tracking problem. First, based on the superposition theorem, the voltage control problem of the ac/dc hybrid microgrid is converted into a H∞ tracking problem for solution, and the robust controller is mathematically proved to exist stably. Then, the designed H∞ robust controller is reduced based on the principle of optimal Hankel norm approximation reduction. Finally, the simulation model is built based on the MATLAB/Simulink to verify the correctness and effectiveness of the proposed method. © 2022 IEEE.

关键词： Robust control

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Transient Performance Optimization of grid Forming Converter 6

Transient Performance Optimization of Grid Forming Converter

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6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Wang, Sichao Li, Chunpeng Yang, Yuexi Han, Congda Zhang, Hanbin Huang, Junwei State Grid Smart Grid Research Institute Co. Ltd. State Key Laboratory of Advanced Power Transmission Technology Beijing China State Grid Fujian Electric Power Research Institute Fujian Key Laboratory of Protection and Operation Contorl for Smart Grid Fuzhou China

ISBN: (纸本)9798350347159

With the increased penetration of renewable energy sources (RES), the power system is emerging a lower inertial characteristic. This can lead to a higher rate-of-change of frequency (RoCoF) and the voltage instability issue during grid disturbance conditions, thus threatening the security of the power grid. Accordingly, researchers have recently proposed a novel grid-forming (GFM) control strategy. Compared to the traditional grid-following (GFL) control method, the GFM control can emulate the dynamic behaviors of the synchronous generator (SG), inherently providing inertial support to stabilize the grid frequency and transient AC voltage. However, it may lead to abnormal transient stress, such as over/under DC voltage and AC overcurrent, raising the risk of unexpected tripping. The paper will present the operating principles of multiple types of GFM and GFL control strategies, and evaluate their dynamic performance during the grid voltage variation events. To address the issue of transient stress, the paper will propose a novel control strategy for suppressing the over/under DC voltage and AC overcurrent so that prevented disconnection of the GFM converters. The proposed method is validated with an example of PV generation scenario, and the effectiveness in improving the dynamic performance has been demonstrated by studying the frequency variation cases. © 2022 IEEE.

关键词： Transients

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A Distributionally Robust Optimal Allocation Method of Energy Storage for Resilience Enhancement of Distribution Network

A Distributionally Robust Optimal Allocation Method of Energ...

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2023 IEEE International Conference on Energy Technologies for Future grids, ETFG 2023

作者： Cao, Kuan Liu, Yutian Wang, Chunyi Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid Shandong Electric Power Company Development Planning Department Jinan China

ISBN: (纸本)9781665471640

To solve the problem of active power imbalance in distribution network with high penetrations of photovoltaic (PV) under extreme weather, the paper proposes a distributionally robust optimal allocation method of energy storage considering extreme scenarios. Firstly, considering that the effect of energy storage on enhancing the resilience of distribution network is strongly related to its location, resilience indexes based on node evaluation are established to select the installation sites of energy storage. Secondly, in view of the correlation and randomness of PV output and load, the typical scenarios with the empirical probability distribution are generated based on Frank Copula joint probability distribution function. Then, Kullback-Leibler divergence is utilized to characterize the probability distribution ambiguity set of the typical scenarios. Based on the ambiguity set, a two-stage distributionally robust optimization model for energy storage capacity is established to minimize the cost of energy storage investment and distribution network operation. For further improving the resilience, an operational resilience index as a chance constraint considering extreme scenarios is embedded into the model. Finally, the case study shows that the proposed method can effectively improve PV accommodation capacity of distribution network and reduce load loss in extreme scenarios. © 2023 IEEE.

关键词： copula function distributionally robust optimization energy storage allocation Kullback-Leibler divergence resilience

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