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Transient Stability Evaluation of Independent Microgrid based on Message Passing Graph Neural Network 6

Transient Stability Evaluation of Independent Microgrid base...

引用

6th International Conference on Electronics Technology, ICET 2023

作者： Zhen, Jiubao Huang, Shufan Jia, Xuwen Du, Haocheng China Agricultural University College of Information and Electrical Engineering Beijing100083 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan250061 China

ISBN: (纸本)9798350337693

Virtual synchronous generator is used to control independent microgrid to provide inertia and damping support, but it often brings transient stability problems. Due to the large number of nonlinear and non-smooth characteristics of highly electronic independent microgrid, it is difficult to analyze it by the traditional transient stability analysis method. In this paper, the independent microgrid controlled by virtual synchronization is taken as the object. Firstly, we compare the impact of detailed modeling of energy storage and simplified modeling on the transient stability, and then discuss the impact of current limiting link of virtual synchronous machine on the transient stability. Secondary, combined with the idea of graph neural network, we propose an independent microgrid transient stability evaluation model based on message passing graph neural network. The information corresponding to bus and transmission lines in microgrid is aggregated and updated by message passing mechanism, so as to depict the topological connection relationship of microgrid, and then consider the influence of topology structure on transient stability evaluation. Last, a WSCC-9 system with virtual synchronous machine is taken as an example. The results show that considering the energy storage detailed model and current limiting link can effectively improve the accuracy of stability analysis. The proposed method has stronger generalization ability and is more applicable to the microgrid system with variable topological structure. © 2023 IEEE.

关键词： Stability

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Application of deep reinforcement learning in power system scheduling strategy simulation 4

Application of deep reinforcement learning in power system s...

引用

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

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

ISBN: (纸本)9798331518066

With the increasing scale and complexity of power system, the current scheduling strategy methods often have the problems of limited adaptability and unsatisfactory results. Therefore, a power system scheduling method using DQN (Deep Q Network) is introduced in this study. This method uses neural network model to learn and optimize scheduling strategy, and has strong adaptability and enhanced global optimization ability. Comparative evaluations with genetic algorithms and particle swarm algorithms on IEEE-118 and SG-126 datasets show that the proposed method has significant advantages in terms of cumulative reward and stable runtime. © 2024 IEEE.

关键词： Deep reinforcement learning

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Energy Storage Configuration Method for Distribution Network Resilience Enhancement Using Two-Stage Game Optimization 8

Energy Storage Configuration Method for Distribution Network...

引用

8th International Conference on Power and Renewable Energy, ICPRE 2023

作者： Liu, Shuai Li, Yuwen Zhou, Heng Cao, Kuan Liu, Yutian State Grid Weihai Power Supply Company Development Planning Department Weihai China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China

ISBN: (纸本)9798350328813

In order to cope with the impact of extreme weather on distribution network, a two-stage multi-objective game optimization-based method of energy storage configuration for distribution network resilience enhancement is proposed in this paper. First, typical scenarios are generated based on N-k contingency as well as distributed photovoltaic (DPV) output characteristics, and evaluation indexes of resilience and economy are established. Then a two-stage multi-objective optimal configuration model is proposed, considering the operating state and resilience demand of distribution network before and after the power supply transfer. Finally, the model is solved by multi-objective particle swarm (MOPSO) and Nash game. Simulation results on the modified IEEE33-node model demonstrate that the proposed method can achieve good equilibrium solution between resilience and economy. © 2023 IEEE.

关键词： MOPSO Nash game power supply transfer resilience two-stage optimal configuration

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Stability Analysis for the Vehicular Platoon system With Time- Varying Delay via A State Decomposition Method

Stability Analysis for the Vehicular Platoon System With Tim...

引用

Automation, control and Robotics Engineering (CACRE), International Conference on

作者： Hang Xu Chuan-Ke Zhang Xing-Chen Shangguan Li Jin Yang Li Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geosciences

ISBN: (数字)9798350350302

ISBN: (纸本)9798350350319

In this paper, the consideration of the stability problem for the vehicular platoon system (VPS) with communication delays under proportional differential (PD) control is studied by the Lyapunov- Krasovskii functional (LKF). Firstly, a VPS considering delay is modeled to analyze the influence of delays for the VPS in operation. Then, an error state-space system of the VPS is constructed and transformed into a singular system. As a result, the stability criterion is proposed based on the state decomposition method via the LKF. Finally, the tolerance for delay is calculated for a case of four vehicles with different controller gains. The result shows that the proportional gain is inversely proportional to the time delay and the differential gain is in direct proportion to the time delay meanwhile. Besides, the high-speed vehicular platoon is more affected by the time delay.

关键词： Automation Delay effects Roads Stability criteria Estimation Delays PD control

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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...

引用

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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Design and Implementation of Power system Simulation Platform Based on Cloud Computing 4

Design and Implementation of Power System Simulation Platfor...

引用

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

作者： Lu, Yuanhong Guo, Haiping Zhao, Yanjun Huang, Libin Hu, Binjiang Luo, Hui Zhang, Jingyue National Energy Power Grid Technology R&d Centre Guangzhou China State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid 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)9798331518066

Power system simulation involves simulating the operating states and dynamic processes of power systems using mathematical models and computer technology to analyze and predict system behavior. Traditional simulation methods struggle to meet the needs of large-scale, complex power grids due to significant demands for computational resources. Cloud computing, with its high scalability, resource pooling, and on-demand services, is ideally suited for the extensive simulation calculations required by modern power systems. Despite its advantages, the application of cloud computing in power system simulation poses challenges related to data security and privacy, particularly in collaborative simulations involving multiple power entities. This paper presents the design and implementation of a cloud computing-based power system simulation platform. The proposed platform leverages the distributed computing capabilities of cloud computing, integrates federated learning to ensure data privacy, and utilizes advanced power system simulation technologies. This approach significantly enhances simulation efficiency and accuracy while providing data security and privacy protection. The platform offers reliable decision support for power system planning, operation, and control. © 2024 IEEE.

关键词： Cloud platforms

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Distributed Power system Simulation and Monitoring Supported by Cloud Technology : A grid optimization scheduling method based on MADRL 4

Distributed Power System Simulation and Monitoring Supported...

引用

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

作者： Luo, Hui Zhang, Jie Hu, Yufeng Zhang, Jingyue Guo, Haiping Huang, Libin 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 Guangzhou China 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

ISBN: (纸本)9798331518066

This study explores the optimization of Distributed Generation systems (DGS) within a Multi-Agent Deep Reinforcement Learning (MADRL) framework. The focus is on transforming the overall optimization goal of the system into a global reward function and designing local rewards adapted to heterogeneous agents. Using the IEEE 33 node system as a case study, the impact of power aggregation and load management from photovoltaic systems, energy storage systems, electric vehicle charging facilities, and HVAC systems is analyzed. The results demonstrate that the proposed edge-cloud collaborative framework optimizes resource allocation and scheduling. The cloud platform is capable of integrating data from diverse sources and managing it in a unified manner, thereby coordinating the operations of multiple heterogeneous agents. The scalability and flexibility of cloud technology allow for the dynamic adjustment of computational resources according to demand, ensuring global optimization and the judicious allocation of resources. © 2024 IEEE.

关键词： Cloud platforms

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Spatial-temporal distribution characteristics and traceability analysis of NOx emission from vehicles based on real-time automatic vehicle identification data in Guangzhou, China

Spatial-temporal distribution characteristics and traceabili...

引用

2023 International Conference on Smart Transportation and City Engineering, STCE 2023

作者： Yang, Xinru Pian, Yuzhuang Xu, Rui Liu, Yonghong School of Intelligent Systems Engineering Sun Yat-Sen University Guangdong Guangzhou510275 China Guangdong Provincial Key Laboratory of Intelligent Transportation System Guangdong Guangzhou510275 China Guangdong Provincial Engineering Research Centre for Traffic Environmental Monitoring and Control Guangdong Guangzhou510275 China

ISBN: (纸本)9781510673540

With the rapid growing of vehicle population, NOx has gradually become a key factor restricting the prevention and control of O3 pollution in China. High-resolution vehicle emission inventories are essential for the development of scientific and efficient pollution prevention and control policies. In this study, a bottom-up approach is adopted to develop a high temporal and spatial resolution vehicle NOx emission inventory for Guangzhou in 2021 based on real-time road network hourly-scale traffic data detected by 5,198 AVI devices. The study further examines the prominent emission vehicle types, emission periods, and emission hotspots in different regions (11 administrative districts, central urban areas, and non-central urban areas) to facilitate a detailed analysis and traceability of high-pollution events. The results of the study showed that the average daily NOx emission from vehicles was 196.15 t/day and the average daily emission intensity was 15.82 kg/(dayžkm). Diesel trucks, medium & heavy diesel trucks, and diesel trucks with China III or lower emission standards are the prominent vehicles with low occupancy and high emissions. In terms of spatial distribution, HDTs are the main contributors in the non-central urban areas, while heavy passenger vehicles and light duty trucks are the main contributors in the central urban areas, and buses also contribute a slightly higher percentage compared to the non-central urban areas. To meet the demand of freight transportation, the distribution of NOx emission hotspots shows a pattern of dispersion outward along the beltway network centred on Baiyun District. A more detailed traceability analysis of the high NOx emission contribution is used to assist in the development of pollution prevention policies. © 2024 SPIE.

关键词： Trucks

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Short-Term Wind Power Forecasting Based on VMD-QPSO-LSTM

Short-Term Wind Power Forecasting Based on VMD-QPSO-LSTM

引用

Power Electronics, Computer Applications (ICPECA), IEEE International Conference on

作者： Peiqi Xin Hongtao Wang Haobo Wang Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China

The unpredictable and highly variable nature of wind power generation demands advanced predictive models to enhance the operational stability of power systems under non-stationary wind conditions. This study presents an innovative approach for short-term wind power prediction, ingeniously integrating Variational Mode Decomposition (VMD), Quantum Particle Swarm Optimization (QPSO), and Long Short-Term Memory (LSTM) network into a cohesive forecasting methodology. Initially, VMD is applied to deconstruct wind power data into distinct sub-modes, thus reducing data complexity and facilitating more accurate analysis. The LSTM model is then fine-tuned using QPSO to refine its hyperparameters, thereby optimizing forecast performance. Each sub-mode is forecasted through a specialized LSTM model, and the collective forecasts are compounded to form the final prediction. Comparative analyses with conventional LSTM, PSO-enhanced LSTM, and QPSO-LSTM models reveal that our proposed VMD-QPSO-LSTM approach yields significantly higher accuracy in forecasting, highlighting its potential to efficiently navigate the uncertainties associated with wind power generation.

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Gait Planning and Motion control Based on Vrep Simulation for Quadruped Robot 5

Gait Planning and Motion Control Based on Vrep Simulation fo...

引用

5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhou, Linqi Chen, Zhihua Liu, Jun Liu, Zhi Chen, Yumeng Zhang, Liting Nanchang Hangkong University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Moe Key Lab of Nondestructive Testing Technology Nanchang330063 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing100081 China

ISBN: (纸本)9798350307320

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot's foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper. © 2023 IEEE.

关键词： Robot programming

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