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Feature selection of power system data for frequency prediction with BO-LightGBM-Boruta 认领 引用
1
作者 Jie Zhou Xiangqian Tong +2 位作者 Jing Zhou Ran Liu Shixian Bai 《Energy and AI》 EI CSCD 2025年第3期763-775,共13页
Accurate grid frequency prediction is essential for the stable operation and optimized dispatch of modern power systems.However,efficiently identifying critical features that influence grid frequency prediction from h... Accurate grid frequency prediction is essential for the stable operation and optimized dispatch of modern power systems.However,efficiently identifying critical features that influence grid frequency prediction from highdimensional,complex power system data remains a significant challenge.To enhance the accuracy of grid frequency predictions,a feature selection method that integrates Bayesian Optimization(BO),LightGBM,and the Boruta algorithm(BO-LightGBM-Boruta)was proposed.The data collected under various fault scenarios from the New England 10-machine 39-bus test system were used as experimental samples to train the grid frequency prediction models and evaluate their predictive performance,thereby verifying the effectiveness and practical value of the proposed feature selection approach.The performance of the BO-LightGBM-Boruta method is compared with Lasso regression and Recursive Feature Elimination(RFE)under three prediction models:E3DLSTM,LSTM,and ConvLSTM.The results show that the BO-LightGBM-Boruta method provides significantly more accurate predictions than the other two feature selection approaches in grid frequency prediction tasks.Notably,the combination of the proposed method and E3D-LSTM,which achieves the highest accuracy across different fault conditions,demonstrates outstanding predictive performance. 展开更多
关键词 Feature selection Grid frequency prediction Bayesian optimization LightGBM-Boruta
Frequency-Hopping Frequency Reconnaissance and Prediction for Non-cooperative Communication Network 认领 引用 被引量：9
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作者 Gao Li Wei Wang +2 位作者 Guoru Ding Qihui Wu Zitong Liu 《China Communications》 SCIE EI CSCD 2021年第12期51-64,共14页
The continuous change of communica-tion frequency brings difficulties to the reconnaissance and prediction of non-cooperative communication net-works.Since the frequency-hopping(FH)sequence is usually generated by a c... The continuous change of communica-tion frequency brings difficulties to the reconnaissance and prediction of non-cooperative communication net-works.Since the frequency-hopping(FH)sequence is usually generated by a certain model with certain regularity,the FH frequency is thus predictable.In this paper,we investigate the FH frequency reconnais-sance and prediction of a non-cooperative communi-cation network by effective FH signal detection,time-frequency(TF)analysis,wavelet detection and fre-quency estimation.With the intercepted massive FH signal data,long short-term memory(LSTM)neural network model is constructed for FH frequency pre-diction.Simulation results show that our parameter es-timation methods could estimate frequency accurately in the presence of certain noise.Moreover,the LSTM-based scheme can effectively predict FH frequency and frequency interval. 展开更多
关键词 non-cooperative communication network frequency-hopping frequency prediction LSTM
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Optimal generation scheduling in power system using frequency prediction through ANN under ABT environment 认领 引用 被引量：1
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作者 Simarjit KAUR Yajvender Pal VERMA Sunil AGRAWAL 《Frontiers in Energy》 EI CSCD 2013年第4期468-478,共11页
In a competitive and deregulated power scenario,the utilities try to maintain their real electric power generation in balance with the load demand,which creates a need for the precise real time generation scheduling(G... In a competitive and deregulated power scenario,the utilities try to maintain their real electric power generation in balance with the load demand,which creates a need for the precise real time generation scheduling(GS).In this paper,the GS problem is solved to perform the unit commitment(UC)based on frequency prediction by using artificial neural network(ANN)with the objective to minimize the overall system cost of the state utility.The introduction of availability-based tariff(ABT)signifies the importance of frequency in GS.Under-prediction or over-prediction will result in an unnecessary commitment of generating units or buying power from central generating units at a higher cost.Therefore,an accurate frequency prediction is the first step toward optimal GS.The dependency of frequency on various parameters such as actual generation,load demand,wind power and power deficit has been considered in this paper.The proposed technique provides a reliable solution for the input parameter different from the one presented in the training data.The performance of the frequency predictor model has been evaluated based on the absolute percentage error(APE)and the mean absolute percentage error(MAPE).The proposed predicted frequency sensitive GS model is applied to the system of Indian state of Tamilnadu,which reduces the overall system cost of the state utility by keeping off the dearer units selected based on the predicted frequency. 展开更多
关键词 artificial neural network(ANN) frequency prediction availability-based tariff(ABT) generation scheduling(GS)
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Novel mode-coupling vibrations of AlN thin film bulk acoustic resonator operating with thickness-extensional mode 认领 引用 被引量：3
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作者 Zinan ZHAO Nian LI +1 位作者 Yilin QU Weiqiu CHEN 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2023年第12期2187-2206,共20页
The dispersion curves of bulk waves propagating in both AlN and ZnO film bulk acoustic resonators(FBARs)are presented to illustrate the mode flip of the thickness-extensional(TE)and 2nd thickness-shear(TSh2)modes.The ... The dispersion curves of bulk waves propagating in both AlN and ZnO film bulk acoustic resonators(FBARs)are presented to illustrate the mode flip of the thickness-extensional(TE)and 2nd thickness-shear(TSh2)modes.The frequency spectrum quantitative prediction(FSQP)method is used to solve the frequency spectra for predicting the coupling strength among the eigen-modes in AlN and ZnO FBARs.The results elaborate that the flip of the TE and TSh2 branches results in novel self-coupling vibration between the small-wavenumber TE and large-wavenumber TE modes,which has never been observed in the ZnO FBAR.Besides,the mode flip leads to the change in the relative positions of the frequency spectral curves about the TE cut-off frequency.The obtained frequency spectra can be used to predict the mode-coupling behaviors of the vibration modes in the AlN FBAR.The conclusions drawn from the results can help to distinguish the desirable operation modes of the AlN FBAR with very weak coupling strength from all vibration modes. 展开更多
关键词 AlN film mode flip frequency spectrum quantitative prediction(FSQP) dispersion curve mode-coupling vibration
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Dual Alternative Iteration Algorithm-based Hierarchical MPC Strategy for Frequency Regulation Control and Active Power Allocation of Wind-storage Coupling System 认领 引用 被引量：1
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作者 Zhenhua Cai Xubin Liu +4 位作者 Canbing Li Nengling Tai Wentao Huang Sheng Huang Juan Wei 《Protection and Control of Modern Power Systems》 SCIE EI CSCD 2025年第6期160-175,共16页
This paper proposes a dual alternative iter-ation algorithm-based hierarchical MPC(DAMPC)strategy to realize frequency regulation control and active power allocation of wind-storage coupling system.The proposed DAMPC ... This paper proposes a dual alternative iter-ation algorithm-based hierarchical MPC(DAMPC)strategy to realize frequency regulation control and active power allocation of wind-storage coupling system.The proposed DAMPC strategy involves a top-level grid fre-quency model predictive control(FMPC)strategy and a bottom-level multi-objective model predictive control(MMPC)strategy.In the FMPC strategy,to improve the frequency regulation performance,the active power ref-erence of the wind-storage coupling system is generated by minimizing the frequency deviation,where the fre-quency reference is calculated by considering the active power deviation and its integral.In the MMPC strategy,the active power reference is optimally allocated to the wind turbine generators(WTGs)and battery energy storage system(BESS)by raising the minimum rotor speed,minimizing the pitch angle deviation and state of charge(SOC)deviation.To solve the multi-objective al-location optimization problem with high efficiency,a dual alternative iteration algorithm(DAIA)is proposed to update the global and local control vectors with the dual vector.Extensive simulations validate the effectiveness of the proposed DAMPC strategy in frequency regulation and active power allocation. 展开更多
关键词 Wind-storage coupling system dual al-ternative iteration algorithm-based hierarchical MPC(DAMPC) grid frequency model predictive control(FMPC) multi-objective model predictive control(MMPC) dual alternative iteration algorithm(DAIA)
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