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Energy-based Directional Pilot Protection for Distribution Networks with IBDGs Considering Unmeasured Load Switching

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CSEE Journal of power and Energy systems 2024年第1期10卷 139-150页

作者： Chenghan Zhou Guibin Zou Shuo Zhang Xuhui Wen Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan 250061China

Inverter-based distributed generations(IBDGs)are the main approach to utilizing clean energy in distribution networks(DNs).Compared with synchronous source,fault response of IBDG is very *** a result,in DNs with high penetration of IBDGs,legacy protection schemes will no longer be *** this paper,an energy-based directional pilot protection scheme suitabie for DNs with IBDGs is *** scheme considers the large range of phase angle caused by IBDG integration and uses improved energy polarity criterion to determine fault *** addition,magnitude of energy is used to distinguish between faults and load switching to overcome maloperation of directional pilot protection caused by internal unmeasured load *** proposed scheme first uses local measured information to determine fault direction sign and then exchanges the direction sign with the remote *** scheme does not require high-bandwidth communication and strict data synchronization,so it can be implemented at a low ***,simulation studies verify effectiveness of the proposed scheme.

关键词： Distribution network energy polarity inverterbased distributed generation pilot protection unmeasured load

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Secondary Frequency control Considering Optimized power Support From Virtual power Plant Containing Aluminum Smelter Loads Through VSC-HVDC Link

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Journal of Modern power systems and Clean Energy 2023年第1期11卷 355-367页

作者： Peng Bao Wen Zhang Yuxi Zhang Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong UniversityJinan 250061China

The growing number of renewable energy replacing conventional generators results in a loss of the reserve for frequency control in power systems,while many industrial power grids often have excess energy supply due to abundant wind and solar energy *** paper proposes a secondary frequency control(SFC)strategy that allows industrial power grids to provide emergency high-voltage direct current(HVDC)power support(EDCPS)for emergency to a system requiring power support through a voltage source converter(VSC)HVDC *** architecture including multiple model predictive control(MPC)controllers with periodic communication is designed to simultaneously obtain optimized EDCPS capacity and minimize adverse effects on the providing power support(PPS)***,a model of a virtual power plant(VPP)containing aluminum smelter loads(ASLs)and a high penetration of wind power is established for the PPS *** flexibility and controllability of the VPP are improved by the demand response of the *** uncertainty associated with wind power is considered by chance *** effectiveness of the proposed strategy is verified by simulation results using the data of an actual industrial power grid in Inner Mongolia,*** DC voltage of the VSCs and the DC in the potlines of the ASLs are also investigated in the simulation.

关键词： Secondary frequency control power support voltage source converter(VSC) high-voltage direct current(HVDC) model predictive control(MPC) virtual power plant(VPP) demand response

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system Strength Assessment Based on Multi-task Learning

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CSEE Journal of power and Energy systems 2024年第1期10卷 41-50页

作者： Baoluo Li Shiyun Xu Huadong Sun Zonghan Li Lin Yu Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan 250014China China Electric Power Research Institute Beijing 100192China

Increase in permeability of renewable energy sources(RESs)leads to the prominent problem of voltage stability in power system,so it is urgent to have a system strength evaluation method with both accuracy and practicability to control its access scale within a reasonable ***,a hybrid intelligence enhancement method is proposed by combining the advantages of mechanism method and data driven ***,calculation of critical short circuit ratio(CSCR)is set as the direction of intelligent enhancement by taking the multiple renewable energy station short circuit ratio as the quantitative ***,the construction process of CSCR dataset is proposed,and a batch simulation program of samples is developed accordingly,which provides a data basis for subsequent ***,a multi-task learning model based on progressive layered extraction is used to simultaneously predict CSCR of each RESs connection point,which significantly reduces evaluation error caused by weak *** performance and anti-noise performance of the proposed method are verified on the CEPRI-FS-102 bus system,which provides strong technical support for real-time monitoring of system strength.

关键词： Critical short circuit ratio hybrid intelligence enhancement multi-task learning system strength

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Multi-stage Provincial power Expansion Planning and Multi-market Trading Equilibrium

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Journal of Modern power systems and Clean Energy 2024年第5期12卷 1652-1665页

作者： Guangsheng Pan Zhongfan Gu Yuanyuan Sun Kaiqi Sun Wei Gu the School of Electrical Engineering Southeast UniversityNanjingChina Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education School of Electrical EngineeringShandong UniversityJinanChina

Decarbonization in the power sector is one of the critical factors in achieving carbon neutrality,and the top-level design needs to be carried out from the perspective of power planning.A multi-stage provincial power expansion planning(PPEP)model is proposed to simulate the power expansion planning at different stages of the power systems rich in renewable energy *** model covers 16 types of power supply,considering macro-policy demands and micro-operation *** stand-alone capacity aggregation model for coal-based units within the PPEP model allows for accurate construction and retirement with different stand-alone ***,the soft dynamic time warping(soft-DTW)based K-medoids technique is adopted to generate typical scenarios for balancing the model accuracy and solution ***,a multi-market trading equilibrium(MMTE)mechanism is proposed to address the differences in the levelized cost of energy between the coal-based and renewable-based units by participating in energy and ancillary service *** the coalbased units take on the task of providing ancillary services from renewable-based units in the ancillary service market,the MMTE mechanism can effectively equalize the profits of both by having renewable-based units purchase ancillary services from coal-based units and pay for them,thus improving the motivation of coal-based units.A case study in Xinjiang province,China,verifies the effectiveness of the planning results of the PPEP model and the profit equilibrium realization of the MMTE mechanism.

关键词： power expansion planning market design ancillary service market renewable energy generation energy market

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Optimizing battery deployment: Aging trajectory prediction enabling homogenous performance grouping

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Journal of Energy Chemistry 2025年第1期100卷 565-577页

作者： Shuquan Wang Feng Gao Zhan Ma Hao Tian Yusen Zhang School of Control Science and Engineering Shandong UniversityJinan 250061ShandongChina Key Lab of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan 250061ShandongChina

As battery deployments in electric vehicles and energy storage systems grow, ensuring homogeneous performance across units is crucial. We propose a multi-derivative imaging fusion(MDIF) model, employing advanced imaging and machine learning to predict battery aging trajectories from minimal initial data, thus facilitating effective performance grouping before deployment. Utilizing a derivative strategy and Gramian Angular Difference Field for dimensional enhancement, the MDIF model uncovers subtle predictive features from discharge curve data after only ten cycles. The architecture includes a parallel convolutional neural network with lateral connections to enhance feature integration and *** on a self-developed dataset, the model achieves an average root-mean-square error of 0.047 Ah and an average mean absolute percentage error of 1.60%, demonstrating high precision and *** robustness is further validated through transfer learning on two publicly available datasets, adapting with minimal retraining. This approach significantly reduces the testing cycles required, lowering both time and costs associated with battery testing. By enabling precise battery behavior predictions with limited data, the MDIF model optimizes battery utilization and deployment strategies, enhancing system efficiency and sustainability.

关键词： Lithium-ion battery Battery prognostics Fusion model Convolutional neural network Transfer learning

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Partial Solution Operator Discretization-Based Methods for Efficiently Computing Least-Damped Eigenvalues of Large Time Delayed power systems

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CSEE Journal of power and Energy systems 2025年第2期11卷 671-682页

作者： Hua Ye Xiaofan Jia Muyang Liu Yutian Liu Sicong Zhang Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of EducationShandong UniversityJinan 250061China School of Electrical Engineering Xinjiang UniversityUrumqi 830046China State Grid Jiangsu Electric Power Research Institute Nanjing 211103China

To investigate impact of time delays on the small signal stability of power systems, the least-damped eigenvalues with the smallest damping ratios have been calculated by eigen-analysis methods based on Solution Operator Discretization (SOD) with Pseudo-Spectral collocation (PS) and Implicit Runge-Kutta (IRK) methods. This paper evolves SOD-PSIIRK into their partial counterparts, i.e., PSOD-PSIIRK, with greatly enhanced efficiency and reliability in analyzing large-scale time delayed power systems. Compared with SOD-PSIIRK, PSOD-PSIIRK are characterized in constructing low order discretization matrices of solution operator as well as efficiently and directly solving the embedded Matrix-Inverse-Vector Products (MIVPs). The dimensions of the discretization matrices of solution operator are largely reduced as only the retarded state variables are discretized, rather than all state variables as in SOD-PSIIRK. Meanwhile, the proposed PSOD-PSIIRK optimize the most computationally expensive operations in SOD-PSIIRK by avoiding the iterative solutions to the two embedded MIVPs. PSOD-PS/IRK directly and efficiently compute the MIVPs via factorizing the Kronecker product-like discretization matrices of the solution operator into Schur complements. The Central China-North China ultra-high-voltage power grid with 80577 state variables serves to validate the proposed PSOD-PSIIRK and shows that compared with SOD-PSIIRK, the computational time consumed by PSOD-PSIIRK is cut down by 49.96 times without loss of any accuracy.

关键词： Eigenvalue analysis low frequency oscillation Schur complement decomposition small signal stability solution operator discretization spectral discretization time delay wide-area measurement system

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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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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...

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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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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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Sub-Synchronous Oscillation Suppression in Series-Compensated Grid-Connected Doubly-Fed Wind Turbines Utilizing Virtual Inductance on the Rotor Side 7

Sub-Synchronous Oscillation Suppression in Series-Compensate...

引用

7th IEEE International Electrical and Energy Conference, CIEEC 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)9798350359558

To tackle the issue of Sub-Synchronous control Interaction (SSCI) in doubly fed wind turbines featuring series capacitor compensation, a novel approach is undertaken by creating an impedance model for the Doubly Fed Induction Generator (DFIG). This model utilizes a power outer-loop control method for decoupling, in alignment with IEEE standards. The study extensively examines the genesis and underlying causes of sub-synchronous oscillations. A novel rotor-side suppression strategy, featuring the integration of virtual inductance into the DFIG's rotor control loop, is proposed to mitigate oscillations induced by series-compensated transmission line parameters. Comparative analysis indicates that the inclusion of virtual inductance effectively quells sub-synchronous oscillations. Additionally, a Simulink-based grid-connected DFIG model is constructed, and time-domain simulations are conducted to validate the model's accuracy in predicting grid-connected sub-synchronous oscillations and confirm the efficacy of the proposed suppression technique. © 2024 IEEE.

关键词： Inductance

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