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5th International Conference on Advances in Electrical, Electronics and Computing Technology, EECT 2025

作者： Wang, Zihan Wang, Mingqiang Xu, Chang Wang, Jialiang Zhang, Yizhe Liang, Caishuai Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

ISBN: (纸本)9798331541545

Under the current general trend of the power industry's transformation towards clean energy, wind power generation, as an important form of renewable energy utilization, is steadily increasing its proportion in the power system. However, the inherent volatility and uncertainty of wind power bring numerous challenges to the stable operation of the power system. Firstly, based on the traditional unit commitment model, this paper comprehensively considers the capacity reserve and ramping reserve of the power system, and constructs a unit commitment model that considers the supply and demand constraints of both types of reserves simultaneously. Then, on the basis of this model, an in-depth and comprehensive discussion is carried out, focusing on the key operation strategy of the active power curtailment operation of wind power. This not only helps to improve the power system's ability to accommodate wind power, but also enables a better response to the challenges of volatility and uncertainty brought by wind power to the power system, thus ensuring the safe, stable and economic operation of the power system. Finally, the model is transformed into a mixed-integer linear programming model that can be directly called by the commercial solver CPLEX, and the effectiveness of the model is verified by a modified IEEE 26-node distribution network. © 2025 IEEE.

关键词： Integer programming

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Time-Varying Formation Tracking control of Heterogeneous Multi-Agent systems With Intermittent Communications and Directed Switching Networks

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 294-296页

作者： Yuhan Wang Zhuping Wang Hao Zhang Huaicheng Yan the Shanghai Research Institute for Intelligent Autonomous Systems Tongji University the National Key Laboratory of Autonomous Intelligent Unmanned Systems the Frontiers Science Center for Intelligent Autonomous System of Ministry of Education the College of Electronic and Information Engineering the Department of Control Science and Engineering Tongji University the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education the School of Information Science and Engineering East China University of Science and Technology

Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so... 详细信息

关键词： Switches Topology Observers Formation control Event detection Switched systems Multi-agent systems control theory Autonomous systems Stability

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Development of High-Speed On-Of Valves and Their Applications

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Chinese Journal of Mechanical Engineering 2022年第4期35卷 21-41页

作者： He Wang Zhen Chen Jiahai Huang Long Quan Bin Zhao Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China

With the widespread application of the computer and microelectronic technology in the industry,digitization becomes the inevitable developing trend of the hydraulic *** of the hydraulic components is critical in the digital hydraulic ***-speed on-of valves(HSVs)which convert a train of input pulses into the fast and accurate switching between the on and of states belong to widely used basic digital hydraulic *** some ways,the characteristics of the HSVs determine the performance of the digital hydraulic *** paper discusses the development of HSVs and their ***,the HSVs with innovative structures which is classifed into direct drive valves and pilot operated valves are discussed,with the emphasis on their ***,an overview of HSVs with intelligent materials is presented with considering of the switching frequency and fow ***,the applications of the HSVs are reviewed,including digital hydraulic components with the integration of the HSVs and digital hydraulic systems controlled by the HSVs.

关键词： High-speed on-of valve Digital hydraulic component Switching frequency Flow rate Innovative structure intelligent material

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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-...

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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...

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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

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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...

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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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Microgrid energy management strategy based on LSTM-DDQN 3

Microgrid energy management strategy based on LSTM-DDQN

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

Research on Microgrid Energy Storage Scheduling Strategy Inc...

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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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