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Emergency control methods for power systems based on improved deep reinforcement learning 6

Emergency control methods for power systems based on improve...

引用

2024 6th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2024

作者： Zhang, Jie Zhu, Yihua Liang, Zhuohang Ma, Qinfeng Zhang, Qingqing Liu, Mingshun An, Su Pu, Qingxin Dai, Jiang State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangdong Guangzhou510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangdong Guangzhou510663 China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangdong Guangzhou510663 China Power Dispatching and Control Center of Guizhou Power Grid Co. Ltd. Guizhou Guiyang550000 China

In order to achieve fast and accurate transient stability analysis and emergency control, this paper proposes a transient stability emergency control method based on improved deep reinforcement learning. In order to fully explore the temporal and spatial variation trend of transient response, a multi-dimensional feature containing information such as transient situation energy is constructed, and the deep reinforcement learning model is transformed based on the time-space graph neural network. On this basis, an emergency control model is constructed, and the power grid knowledge is integrated into the emergency control decision-making scheme to reduce the exploration of invalid decision-making and improve the performance of the model. The effectiveness of the proposed method is verified in the IEEE-39 system. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Deep reinforcement learning

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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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A Networked Method Applied to Sensitivity Analysis of a VSG controlled BESS system 5

A Networked Method Applied to Sensitivity Analysis of a VSG ...

引用

5th International Conference on power Engineering, ICPE 2024

作者： Sun, Zhiyuan Luo, Chao Zheng, Kun Zhu, Yihua Yu, Jiawei Guangxi Power Grid Electric Power Research Institute China S. Power Grid Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Nanning China Electric Power Research Institute China Southern Power Grid State Key Laboratory of Hvdc Guang zhou China National Energy Power Grid Technology R&d Centre Guang zhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guang zhou China

ISBN: (纸本)9798331531140

The grid-forming battery energy storage system (BESS) plays important role in constructing new energy system. This paper presents a frequency domain modal-based stability analysis of virtual synchronous generator (VSG) controlled BESS. Both ac and dc side interactive dynamics of the grid-tied inverter system are considered, by establishing a hybrid ac/dc impedance network. Then, the frequency domain modal analysis (FMA) method for networked converter systems is applied to the BESS system, covering the eigen-sensitivity from the node level to parameter level. Using this method, key parameters that influence the BESS system's weakly/negative damping modes most can be better analyzed and identified. The analysis results are validated via the time-domain simulations. © 2024 IEEE.

关键词： Frequency domain analysis

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The HEFT Algorithm Based on Node Merging 8

The HEFT Algorithm Based on Node Merging

引用

8th International Workshop on control Engineering and Advanced Algorithms, IWCEAA 2024

作者： Huang, Ying Lu, Yuanhong Zhang, Jie Zhang, Jingyue Guo, Haiping National Energy Power Grid Technology R&D Centre Guangzhou510663 China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou Guangzhou510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou Guangzhou510663 China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou Guangzhou510663 China

ISBN: (纸本)9798331528881

The task scheduling problem in power systems is complex, especially when communication costs exceed computation costs. This paper proposes an improved HEFT algorithm with a node merging mechanism, merging nodes through hierarchical traversal to assign high-communication-cost tasks to the same processor, reducing communication overhead. Experiments with 499-dimensional and 1614-dimensional matrices from the power system show that the improved algorithm reduces completion time by 5ms and 2ms, respectively, compared to standard HEFT. © 2024 IEEE.

关键词： Scheduling algorithms

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Multi-Type Electric Vehicle Schedulability Modeling Method based on User Charging Behavior Characteristics 11

Multi-Type Electric Vehicle Schedulability Modeling Method b...

引用

11th China International Conference on Electricity Distribution, CICED 2024

作者： Xue, Yinjuan Chen, Qifang Cai, Haiqing Xia, Mingchao Gu, Haohan School of Electrical Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&d Centre Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9798350368345

With the rapid proliferation of Electric Vehicles (EV s), effectively leveraging the regulation potential of EV charging loads has become a prominent issue. This paper proposes a multi-type EV schedulability modeling method based on the analysis of charging behavior characteristics of different user types. The model comprehensively considers the charging characteristics of various types of EV s, including private cars, ride-hailing vehicles, and taxis, utilizing a charging start-stop probability distribution model. Case studies demonstrate that this model can not only accurately reflect the charging demands of EV s but also provide valuable references for strategies involving EV fleet participation in grid regulation. © 2024 IEEE.

关键词： Charging stations

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Large-scale non-real-time Simulation Platform for power systems Based on Cloud Computing 4

Large-scale non-real-time Simulation Platform for Power Syst...

引用

4th International Conference on Energy, power and Electrical Engineering, EPEE 2024

作者： Zhang, Jingyue Lu, Yuanhong Hu, Yufeng Zhang, Jie Guo, Haiping Huang, Libin Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China National Energy Power Grid Technology R&d Centre Guangzhou China China Southern Power Grid Co. Ltd Guangzhou China State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9798331518066

The rapid evolution of smart grids has increased the complexity of power system structures and operational characteristics, presenting new challenges in system management and reliability. Traditional power system simulation tools struggle with non-real-time data processing and scalability due to limitations in their architectural designs. Moreover, existing cloud simulation platforms are constrained by closed hardware architectures and lack sufficient non-real-time capabilities. As a solution, we propose a novel large-scale non-real-time simulation platform for power systems based on cloud computing, designed with a modular architecture. By leveraging advanced technologies in cloud computing, parallel computing, and non-real-time simulation, our platform addresses critical needs for scalability, efficiency, and cost-effectiveness. We discuss how integrating these technologies enhances computational performance and supports complex simulation tasks, ultimately improving decision-making and operational efficiency in power system management. © 2024 IEEE.

关键词： Cloud platforms

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Simulation Testing of Large-Scale Grid-Connected Wind power with Energy Storage system Based on Active Support Performance Evaluation Indices 10

Simulation Testing of Large-Scale Grid-Connected Wind Power ...

引用

10th International Forum on Electrical Engineering and Automation, IFEEA 2023

作者： Zhu, Yihua Hu, Yun Tu, Liang Su, Mingzhang Luo, Chao Csg State Key Laboratory of Hvdc Electric Power Research Institute Guangzhou China National Energy Power Grid Technology R&d Centre Guangzhou 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

ISBN: (纸本)9798350309379

This paper establishes simulation modeling for large-scale grid connected wind power with energy storage system (ESS). The conventional grid-following (GFL) based ESS is used as a reference object to test the active support performance of large-scale grid-connected wind power with grid-forming (GFM) based ESS with active support performance evaluation indices in different scenarios. (1) Small disturbance evaluation indices: The point of common coupling (PCC) frequency/voltage drop depth and recovery time. (2) Large disturbance evaluation indices: The PCC frequency/voltage drop depth and rise height after fault removal. The output active/reactive power drop depth and rise height/recovery time after fault removal. (3) Island capability evaluation indices: The PCC frequency/voltage fluctuation amplitude at the moment of switching and system stability after switching. © 2023 IEEE.

关键词： active support performance evaluation indices different scenarios grid-following (GFL) grid-forming (GFM)

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Adaptive Identification of power system operational States Based on Spatio-Temporal Dynamic Graph Neural Networks 4

Adaptive Identification of Power System Operational States B...

引用

4th IEEE International Conference on Electronic Technology, Communication and Information, ICETCI 2024

作者： Zhang, Qingqing Ma, Qinfeng Liu, Mingshun Zhang, Jie Zhu, Yihua Liang, Zhuohang An, Su Pu, Qingxin Dai, Jiang Power Dispatching and Control Center of Guizhou Power Grid Co. Ltd. Guizhou China China Southern Power Grid State Key Laboratory of HVDC Electric Power Research Institute Guangzhou510663 China National Energy Power Grid Technology R&D Centre Guangzhou510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou510663 China

ISBN: (纸本)9798350361643

The state identification of the operational status of power systems plays a crucial role in ensuring the safety, efficiency, and reliable operation of power systems, forming the foundation for the management and control of power system operations. In the practical operation of power systems, the duration of fault states is short, while the system remains in a safe and stable state for a significantly longer period, leading to an imbalance in the training samples available. This imbalance can cause traditional machine learning classification algorithms to favor the majority categories of power system operational states, resulting in inaccurate evaluation metrics and reduced model generalization capability. To address this issue, this paper introduces a spatiotemporal dynamic graph neural network model for the identification of power system operational states. By incorporating class cost coefficients, focal loss, and cross-entropy in a joint loss function, the model adaptively focuses on the less represented operational state categories during training, improving classification accuracy on imbalanced and challenging samples. Moreover, the integration of temporal information and spatial topology information within the graph neural network enhances the model's robustness and generalization ability in state identification. Experimental results on the standard IEEE 68-bus system demonstrate that, compared to traditional machine learning methods, the proposed joint loss with the spatiotemporal dynamic graph neural network model achieves higher accuracy in the identification of power system operational states, significantly improving classification performance on imbalanced samples with a 4.8% increase in F1-score, reaching a peak F1-score of 98.6%. © 2024 IEEE.

关键词： Graph neural networks

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Multi-Objective Coordination and Stability control of High Proportion Wind power system Based on K-Domain Tuning Damping 19th

Multi-Objective Coordination and Stability Control of High P...

引用

19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Zhang, Qingtao Gao, Diju Zhang, Dan Cai, Haiqing Gu, Haohan Chen, Wei Wu, Wencong Chen, Zhihao Institute of Logistics Engineering Shanghai Maritime University Shanghai China Institute of Logistic Science and Engineering Shanghai Maritime University Shanghai China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9789819608966

With the further development of "double high" characteristics of power system, the traditional stability problem dominated by synchronous generator has gradually evolved into a new stability problem dominated by power electronic equipment control. In addition, different types of failure problems can occur in wind power systems. In order to achieve multi-objective coordinated and stable operation of high proportion wind power system, a damping control method with parameters tuning is proposed, which includes the design of filtering link and proportional amplification link. Among them, the key parameters of the proportional link are adjusted. Finally, the feasibility of the proposed control method is verified by simulation tests. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Electric power system stability

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Research on Active Support control Strategy and its Performance of Renewable Energy power Station with Multiple Energy Sources 7

Research on Active Support Control Strategy and its Performa...

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7th IEEE Conference on Energy Internet and Energy system Integration, EI2 2023

作者： Zeng, Guanming Tu, Liang Zhu, Yihua Hu, Yun Luo, Chao Li, Shengnan State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid National Energy Power Grid Technology R&d Centre Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control For New Energy Power System Csg Key Laboratory For Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid Csg Key Laboratory For Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&d Centre Guangdong Provincial Key Laboratory of Intelligent Operation and Control For New Energy Power System Guangzhou China Yunnan Power Grid Co. Ltd. Electric Power Research Institute Yunnan Kunming China

ISBN: (纸本)9798350345094

The increasing integration of renewable energy reduces the inertia and frequency support capacity of the power system. The issue of frequency stability has become one of the core issues in the security and stability of power system and the efficient consumption of renewable energy nowadays. To improve the performance of renewable energy power station (REPS), based on the analysis of typical active support control logic and relative performance requirements of REPS with single energy source (SES), an active support control strategy and coordinated control logic of active power of REPS with multiple energy sources (MES) are proposed in this paper. The performance of proposed strategy is theoretically analyzed from the aspect of dominant energy source and the effect of the capacity of energy storage. The effectiveness of the proposed strategy and the accuracy of the theoretical analysis of performance are verified by realtime simulation. © 2023 IEEE.

关键词： Renewable energy

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