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Numerical investigation of dynamic characteristics of dual throat nozzle and bypass dual throat nozzle in thrust vectoring starting process

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Chinese Journal of Aeronautics 2024年第10期37卷 184-206页

作者： Yuqi ZHANG Jinglei XU Minglei CAO Ruifeng PAN Shuai HUANG Key Laboratory of Inlet and Exhaust System Technology of Ministry of Education Nanjing University of Aeronautics and AstronauticsNanjing 210016China College of Energy and Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China State Key Laboratory of Mechanics and Control of Aeronautics and Astronautics Structures Nanjing 210016China

The Bypass Dual Throat Nozzle(BDTN)is a novel fluidic Thrust Vectoring(TV)nozzle,it switches to TV state by opening the valve in the *** greatly manipulate the BDTN,the dynamic characteristics in the TV starting process should be *** paper conducts numerical simulations to grasp the variation processes of performances and the flow field evolution of BDTN and Dual Throat Nozzle(DTN).The dynamic responses of TV starting in typical DTN models are investigated at ***,the TV starting processes of BDTN in different Nozzle Pressure Ratio(NPR)conditions are simulated,and the valve opening durations(T)are also *** the expected TV direction is achieved in the DTN,the jet is deflected to the opposite direction at the beginning of the dynamic process,which is called the reverse TV ***,this phenomenon disappears in the *** larger injection width of DTN intensifies unsteady oscillations,and the reverse TV phenomenon is *** the BDTN,T determines the delay degree of performance variations compared to the static results,which is called hysteresis *** NPR=10,the hysteresis affects the final stable performance of *** study analyses the dynamic characteristics in DTN and BDTN,laying a foundation for further design of nozzles and control strategies.

关键词： Dual Throat Nozzle(DTN) Bypass Dual Throat Nozzle(BDTN) Dynamic characteristic Thrust vectoring starting process Cavity vortex Hysteresis effect

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New Energy Consumption Capacity Evaluation Method for Isolated Industrial Park Considering Flexible Load Regulation Ability

New Energy Consumption Capacity Evaluation Method for Isolat...

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2024 IEEE IAS Industrial and Commercial power system Asia, I and CPS Asia 2024

作者： Li, Nan Xu, Hui Tan, Zhenlong Dai, Haonan Zheng, Zhibao Hao, Ling Xu, Fei Chen, Lei Tong, Zihao Tsinghua University State Key Laboratory of Power System Operation and Control Beijing China Co. Ltd. Beijing China Tsinghua University School of Economics and Management Beijing China

ISBN: (纸本)9798350352290

In the context of the global energy transition, China is promoting the synergistic integration of energy sources, grids, loads and storage through national strategic policies. This paper examines the challenges of integrating volatile new energy sources, such as wind and solar, into the grids of isolated industrial parks (IIPs). It proposes a model to assess and optimize the consumption capacity of these resources to balance energy production with grid demand effectively. Initially, a 'resource-power' conversion model is developed to simulate the potential output of wind and solar installations, given the absence of direct connectivity to the grid in newly established IIPs. Then, with the optimization objective of minimizing the overall cost of isolated grid operation, the new energy consumption capacity of IIPs is evaluated, taking into account the actual operating constraints of thermal power units, the maximum new energy consumption that can be technically achieved, and the regulation potential of flexible load participation response to mitigate the impacts caused by fluctuations in new energy sources. Finally, based on the analysis of the actual operation data of the IIPs, the simulation results show that the IIP can be guided by adjusting the installed capacity parameters for planning the installed size of wind and solar in the IIP before connecting to wind and PV. Moreover, fully exploiting flexible load regulation ability can effectively improve the IIP's wind power consumption capacity, which can provide theoretical guidance for optimizing the IIP's scheduling and promoting new energy consumption. © 2024 IEEE.

关键词： Clean energy

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Application research of time-slot task synchronization method based on timestamp counter polling in electromagnetic transient real-time simulation 6

Application research of time-slot task synchronization metho...

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6th International Conference on Information Science, Electrical, and Automation Engineering, ISEAE 2024

作者： Guo, Qi Lu, Yuanhong Guo, Tianyu Zhang, Jie Huang, Libin Tu, Liang Guo, Zhilong Xu, Dehuai Guo, Chuang 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 Dawning Network Technology Corp. Ltd. Wuhan China

ISBN: (纸本)9781510682924

In the practical application of electromagnetic transient real-time simulation computing platform, due to the large amount of calculation and long calculation time of electromagnetic transient simulation calculation, in order to improve the calculation speed and accuracy, it is usually necessary to use multiple CPU cores for parallel calculation at the same time, and ensure that each task synchronization and coordination among the computing cores. So, it is of great significance to select an appropriate task synchronization method for the realization of the electromagnetic transient real-time simulation computing platform. The paper puts forward a kind of based on TSC (Time Stamp Counter) Time Stamp Counter polling Time slot task synchronization method, this method supports high precision Time synchronization and coordination between different tasks, and can adapt to the transmission and efficient processing of large amounts of data. The test results prove that this method can avoid the overhead and delay of a large number of interrupts and thread switching, improve the efficiency, stability and predictability of task execution, and meet the performance requirements of the task synchronization method based on the centralized tightly coupled electromagnetic transient real-time simulation prototype. © 2024 SPIE.

关键词： Electromagnetic transients

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Zero-phase CARIMA Filtering and Application in Wind-storage system Sizing and power Dispatch Optimization

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CSEE Journal of power and Energy systems 2024年第6期10卷 2283-2295页

作者： Wei Wang Peng Chen Guorui Ren Jizhen Liu Fang Fang Zhe Chen State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China Department of Energy Technology Aalborg University9220 AalborgDenmark

Hybrid energy storage system(HESS)is an effective way to mitigate wind power fluctuations on multi-time scale,and can improve influence of large-scale grid-connected wind power on stability and reliability of power system.A novel methodology named zero-phase controlled auto-regressive integrated moving-average(CARIMA)filter is proposed to integrate HESS to smooth wind power ***,a design method for zero-phase CARIMA filter is provided,and then used to determine grid-connected power for a wind storage system and size *** reasons,direct current(DC)component caused by energy storage efficiency and grid-connected power delay caused by phase shift,for causing superfluous energy storage configuration are *** addition,a nonlinear programming scheduling strategy considering battery degradation is *** imbalance caused by efficiency difference during dynamic adjustment of energy storage output power is ***,thermostatically controlled loads(TCLs)are integrated in sizing and scheduling HESS to reduce energy storage demand and improve operating conditions of energy ***,effectiveness of the proposed strategy is verified by a case study.

关键词： CARIMA demand response energy storage optimization wind power zero-phase

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Technical Research on Simulation and Predictive Analysis of Wind Farms in power systems 4

Technical Research on Simulation and Predictive Analysis of ...

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

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

ISBN: (纸本)9798331518066

To address the issue of insufficient accuracy in wind power output forecasting, this paper proposes a Support Vector Machine (VSM) model based on similar day matching and kernel entropy component analysis for wind power prediction. The model effectively extracts similar day features through the similar day approach and optimizes feature representation by combining it with kernel entropy component analysis (KECA), ultimately employing the SVM model for wind farm power forecasting. Simulation results demonstrate that using this model for optimizing wind power generation predictions enhances the accuracy of wind power forecasts, surpassing the precision of single-method predictions. The Similar Day-KECA-SVM method leverages historical data from similar days and features extracted through KECA, with SVM performing the final prediction. This approach adeptly handles complex patterns and nonlinear relationships in wind power forecasting, thereby achieving superior predictive performance. © 2024 IEEE.

关键词： Wind forecasting

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The Development of Simulation Mirror system and its Application in HVDC 6

The Development of Simulation Mirror System and its Applicat...

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6th International Conference on HVDC, HVDC 2024

作者： Ou, Kaijian Wu, Wencong Cai, Haiqing State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid National Energy Power Grid Technology R&d Centre. Guangzhou China Guangdong Prov. 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)9798350387759

The testing of HVDC new control function and training of HVDC operation personnel require the integration of power system simulation and dispatching automation. This paper presents and builds AC&DC power system simulation mirror system, which is the closed-loop of real-time digital simulation and dispatching automation. Moreover, the applications of simulation mirror system on HVDC new control function testing and HVDC simulation training cabinet are also introduced in this paper. © 2024 IEEE.

关键词： automatic generation control (A GC) automatic HVDC control (ADC) dispatching automation high voltage direct curren t(HVD C) real-time digital simulator(RTDS)

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Combined Wind-Storage Frequency Modulation control Strategy Based on Fuzzy Prediction and Dynamic control

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Energy Engineering 2024年第12期121卷 3801-3823页

作者： Weiru Wang Yulong Cao Yanxu Wang Jiale You Guangnan Zhang Yu Xiao Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology of the Ministry EducationJilin132012China State Grid Songyuan Electric Power Supply Company Songyuan138000China

To ensure frequency stability in power systems with high wind penetration,the doubly-fed induction generator(DFIG)is often used with the frequency fast response control(FFRC)to participate in frequency ***,a certain output power suppression amount(OPSA)is generated during frequency support,resulting in the frequency modulation(FM)capability of DFIG not being fully utilised,and the system’s unbalanced power will be increased during speed recovery,resulting in a second frequency drop(SFD)in the ***,the frequency response characteristics of the power system with DFIG containing FFRC are ***,based on the analysis of the generation mechanism of OPSA and SFD,a combined wind-storage FM control strategy is proposed to improve the system’s frequency response *** strategy reduces the effect of OPSA and improves the FM capability of DFIG by designing the fuzzy logic of the coefficients of FFRC according to the system frequency index in the frequency support *** the speed recovery stage,the energy storage(ES)active power reference value is calculated according to the change of DFIG rotor speed,and the ES output power is dynamically adjusted to reduce the ***,taking the IEEE 39-bus test system as an example,real-time digital simulation verification was conducted based on the RTLAB OP5707 simulation *** simulation results showthat theproposedmethodcan improve theFMcapabilityofDFIG,reduce the SFDunder thepremise of guaranteeing the rapid rotor speed recovery,and avoid the overshooting phenomenon so that the systemfrequency can be quickly restored to a stable state.

关键词： Doubly-fed induction generator frequency fast response control output power suppression amount frequency response characteristics second frequency drop combined wind-storage

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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...

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

Design and Implementation of Power System Simulation Platfor...

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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...

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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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