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检索条件"机构=Ministry of Education of Key Laboratory of Complex System Intelligent Control and Decision"

共 2255 条记录，以下是11-20 订阅

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Voltage and Frequency control Coordination Strategy of Wind-PV-ESS system for Black-Start 7

Voltage and Frequency Control Coordination Strategy of Wind-...

引用

7th International Conference on Power and Energy Applications, ICPEA 2024

作者： Lei, Haoda Cao, Kuan Sun, Runjia Liu, Yutian Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan China

ISBN: (纸本)9798350356113

In blackout scenarios of new power systems, wind farms (WF) and photovoltaic power stations (PVS) configured with scaled energy storage system (ESS) can be used as sources to support the black-start of thermal power units. Aiming at the disturbance of system voltage and frequency during black-start, a voltage and frequency control coordination strategy of Wind-PV-ESS system for black-start is proposed. The voltage control strategy includes normal control mode and correction control mode. When the bus voltage keeps within the limit, the former coordinately distributes the reactive power of each WT and PVA to maximize the dynamic reactive power reserve. After the bus voltage is disturbed beyond the limit, the latter makes full use of the fast dynamic reactive power response characteristics of SVG and ESS to provide voltage support. In the frequency control strategy. the reference power generated by the PI controller is allocated according to the proportion of the reserve power of each wind turbine (WT) or photovoltaic array (PVA) to the total reserve to eliminate the frequency deviation. Simulation results show the effectiveness of the proposed strategy. © 2024 IEEE.

关键词： Wind turbines

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Frequency Domain Stability Analysis and Simulation of New Energy Power Generation systems 9

Frequency Domain Stability Analysis and Simulation of New En...

引用

9th Asia Conference on Power and Electrical Engineering, ACPEE 2024

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

ISBN: (纸本)9798350309638

Stability analysis of grid-connected inverters is advanced through impedance analysis in this study, which leads to the development of a comprehensive mathematical model and simulation. control parameters, notably the voltage inner-loop control parameter Kv, the proportional gain Kp of the phase-locked loop (PLL), and the integral gain K1, were meticulously adjusted to assess their effects on subsynchronous oscillations. It was determined that while the proportional gain p and integral gain K1 have a marginal impact on sub-synchronous oscillations, the voltage inner-loop control parameter K1 significantly influences these oscillations. The insights gained from this analysis contribute to a deeper understanding of, and potential solutions for, synchronous oscillation issues. The ability to mitigate such oscillations facilitates the integration of a higher proportion of renewable energy sources, thereby enhancing the stability and reliability of the electrical power system. This enhancement is of critical importance in the pursuit of sustainable energy transitions and the advancement of clean energy sources. © 2024 IEEE.

关键词： Phase locked loops

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Short-Term Wind Power Forecasting Based on VMD-QPSO-LSTM 4

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

引用

4th IEEE International Conference on Power, Electronics and Computer Applications, ICPECA 2024

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

ISBN: (纸本)9798350359589

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. © 2024 IEEE.

关键词： deep learning long short-term memory network variational mode decomposition wind power forecasting

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Combined Rotor-Side and Grid-Side Suppression of Sub-Synchronous Oscillation in Doubly-Fed Wind Turbines 7

Combined Rotor-Side and Grid-Side Suppression of Sub-Synchro...

引用

2024 7th International Conference on Mechanical, Electrical and Material Application, MEMA 2024

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

In the field of wind power generation, the significant geographical separation between wind farms and load centers often necessitated the long-distance and large-scale transmission of wind energy, which was typically achieved through transmission lines equipped with series compensation capacitors. However, this setup led to interactions between the series compensation capacitors and the control systems of doubly-fed induction generators (DFIGs), potentially causing sub-synchronous oscillations in grid-connected systems. To address this issue, our study focused on a DFIG-based wind farm interconnected via a series-compensated line. We proposed an innovative suppression strategy that incorporated additional virtual damping on the grid side. This strategy was effectively combined with an ancillary approach of adding virtual inductance on the rotor side, offering a robust solution to mitigate sub-synchronous oscillations. The simulation results showed that the joint application of these two strategies was more effective than implementing them individually. Notably, the strategy involving additional virtual damping on the grid side outperformed the approach of adding virtual inductance on the rotor side. © Published under licence by IOP Publishing Ltd.

关键词： Inductance

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Transient Stability Analysis and Enhancement of Virtual Synchronous Generator with Current Limiter 7

Transient Stability Analysis and Enhancement of Virtual Sync...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Wang, Yantuan Ye, Hua Yang, Jialun Chu, Xiaodong Mou, Qianying Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China

ISBN: (纸本)9798350359558

The modern power system exhibits a double high characteristic, where the physical structure and control strategies of power electronic devices have altered the stability characteristics of the modern power system. This paper investigates the transient instability issue faced by virtual synchronous generators (VSG) equipped with a current limiter during grid faults. Firstly, the transient stability model of the VSG is established. Then, the equal-area criterion (EAC) is employed to reveal the mechanism of transient instability in VSG and elucidate the influence of the current limiter on the transient stability of VSG. Based on this analysis, current angle configuration methods are further proposed to enhance the transient stability of VSG. Finally, the correctness of the mechanism analysis and proposed methods is validated through simulation. © 2024 IEEE.

关键词： Synchronous generators

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Microgrid energy management strategy based on LSTM-DDQN 3

Microgrid energy management strategy based on LSTM-DDQN

引用

2024 3rd International Conference on Electrical, control and Information Technology, ECITech 2024

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

This paper introduces a novel algorithm, LSTM-DDQN, designed to address the stochastic economic dispatch problem in microgrids. The inherent variability and randomness of photovoltaic (PV) energy pose challenges for accurate output prediction. Traditional approaches, including physical and statistical methods, often fall short in terms of accuracy. For microgrids with a high proportion of PV generation, we propose a new algorithm that combines Long Short-Term Memory (LSTM) neural networks with the Double Deep Q-Network (DDQN) algorithm. The algorithm leverages the LSTM model to capture the uncertainty of the learning environment and optimizes the Q-value iteration rules in the DDQN algorithm, thereby enhancing the training speed of the neural network. Experimental results demonstrate the algorithm's remarkable dispatch capabilities in managing the interplay between PV generation, battery capacity, and overall load demand. This algorithm provides robust support for the stable operation of microgrids. © 2024 Published under licence by IOP Publishing Ltd.

关键词： Long short-term memory

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Research on Microgrid Energy Storage Scheduling Strategy Incorporating Electric Vehicles Based on the DQN Algorithm 9

Research on Microgrid Energy Storage Scheduling Strategy Inc...

引用

9th Asia Conference on Power and Electrical Engineering, ACPEE 2024

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

ISBN: (纸本)9798350309638

This study focuses on the scheduling of a microgrid integrated with electric vehicles, employing a reinforcement learning algorithm to devise an optimal economic operation strategy. The approach addresses the challenges of renewable energy generation's randomness and the economic and safety concerns arising from the extensive integration of electric vehicles into the microgrid. The paper explores the reinforcement learning-based energy management of storage devices within the microgrid. A Deep Q-Network (DQN) method is utilized to formulate the microgrid storage scheduling problem as a Markov decision Process (MDP). The study involves a detailed simulation of a residential user microgrid, considering various parameters such as battery storage capacity, charging and discharging rates, and electric vehicle load models. The reinforcement learning algorithm demonstrates the capability of real-time response to power changes in the microgrid, ensuring operational cost minimization even under multiple input uncertainties. © 2024 IEEE.

关键词： Markov processes

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Transient Overvoltage Quantitative Analysis Based on Short-Circui Ratio of New Energy Generation Stations 3

Transient Overvoltage Quantitative Analysis Based on Short-C...

引用

3rd Asia Power and Electrical Technology Conference, APET 2024

作者： Wu, Yuhan Li, Yajie Shandong University Key Laboratory of Power System Intelligent Dispatch and Control The Ministry of Education Jinan China

ISBN: (纸本)9798350367690

With the increasing proportion of grid-connected renewable energy sources such as photovoltaic and wind power, the stability issues caused by large-scale development of new energy sources have become prominent. Among these issues, transient overvoltage is the primary constraint limiting the large-scale development of new energy sources. Studies have shown that the occurrence of transient overvoltage is closely related to the system strength of grid-connected points for new energy sources. The weaker the system strength, the greater the risk of stability problems such as transient overvoltage. The short-circuit ratio is an important indicator for assessing the grid strength of new energy integration points. Monitoring the short-circuit ratio can effectively evaluate the strength of the new energy station's integration into the system. Therefore, based on the short-circuit ratio of new energy generation stations, this paper quantitatively analyzes the relationship between the short-circuit ratio and transient overvoltage. In future research, the short-circuit ratio can be used as a constraint condition, with transient overvoltage as an indicator, to facilitate the determination of reactive power compensation solutions for high-proportion new energy integration systems. Finally, MATLAB/simulink simulations validate the accuracy of the analysis. © 2024 IEEE.

关键词： Wind power integration

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Acceleration of Power system Dynamic Simulation with High-Penetration Renewable Generation via Time-Step Adjustment Based on ETFBs 7

Acceleration of Power System Dynamic Simulation with High-Pe...

引用

7th IEEE Student Conference on Electric Machines and systems, SCEMS 2024

作者： Cao, Jiawen Lv, Dongbao Liu, Xindi Li, Changgang Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan China

ISBN: (纸本)9798350366945

With the widespread integration of renewable energy sources (REs), the number of power system scenarios to be analyzed has increased significantly, and the system structure has become increasingly complex, which increases the computational burden of power system dynamic simulations and leads to substantial computation time. Therefore, there is an urgent need to improve the efficiency of dynamic simulation to meet the requirements of advanced applications. The uEITSA method adopts a fixed system time-step in the overall simulation, which makes it challenging to balance simulation accuracy and efficiency. Therefore, a system time-step adjustment strategy is proposed in this paper to optimize the uEITSA method, implemented in the open-source Simulation Toolkit for Electrical Power systems (STEPS). Firstly, the system time-step adjustment strategy based on elementary transfer function blocks (ETFBs) is introduced. Secondly, the implementation of the proposed strategy in STEPS software is described in detail. Finally, the simplified Shandong Power Grid model is tested to demonstrate that the proposed system time-step adjustment strategy can improve simulation efficiency without jeopardizing simulation accuracy. © 2024 IEEE.

关键词： Power systems computer aided design

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Optimal Dispatch for Large-Scale Renewable Energy Bases Without Conventional Power Support

Optimal Dispatch for Large-Scale Renewable Energy Bases With...

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Zhang, Kunpeng Liu, Tianhao Liu, Yutian Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan China

ISBN: (纸本)9798350350821

In large-scale renewable energy base and HVDC systems, the absence of conventional power support makes commutation failures a significant threat to system security and stability. An optimal dispatch method based on Kolmogorov-Arnold Networks (KAN) is proposed, which considers voltage and frequency dynamic security constraints. First, a time-domain simulation model of the system is developed to generate training data for KAN. The KAN is then designed to estimate the transient overvoltage at the point of common coupling in the renewable energy base after the occurrence of commutation failure. Frequency fluctuation is calculated by frequency nadir prediction model. Thirdly, an optimal dispatch model is formulated to maximize the delivered power of HVDC, which considers both operational and dynamic security constraints. Simulation results demonstrate that the proposed optimal dispatch model enhances system security with an acceptable reduction in delivered power. © 2024 IEEE.

关键词： commutation failure Kolmogorov-Arnold Networks LCC-HVDC power generation dispatch renewable energy base transient overvoltage estimation

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