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A Generalized Wind Turbine Anomaly Detection Method Based on Combined Probability Estimation Model

Journal of Modern Power systems and Clean Energy 2023年第4期11卷 1136-1148页

作者： Xiangjun Zeng Ming Yang Chen Feng Yaohua Tang Key Laboratory of Power System Intelligent Dispatch and Control Shandong UniversityJinan 250061Chinaand X.Zeng is also with the College of Electrical Engineering&New EnergyChina Three Gorges UniversityYichang 443002China Rundian Energy Science and Technology Co. Ltd.Zhengzhou 450046China

Anomaly detection based on the data collected from the supervisory control and data acquisition(SCADA)system is crucial to reduce the failure rate of wind turbines(WTs).The difficulty of this kind of methods is to dynamically identify the threshold for anomaly detection under changing operating *** this paper,a generalized WT anomaly detection method based on the combined probability estimation model(CPEM)is *** CPEM can estimate the conditional probability density function(PDF)of the target variable given changing *** generalization and accuracy are better than those of the independent probability estimation model because it combines the advantages of various kinds of probability estimation models through linear *** using the CPEM,the normal operating bounds under different operating conditions can be obtained,which dynamically form the thresholds for anomaly ***,with respect to the thresholds,hypothesis testing(HT)is adopted to identify the anomaly by inspecting whether the observations exceed the thresholds at a given significance level,providing sound mathematical support for anomaly detection and making the detection results more *** effectiveness of the proposed method is tested by using the actual data of WTs with known *** results illustrate that the proposed method can detect the abnormal operating state of the gearbox and generator much more early than the system fault alarm.

关键词： Anomaly detection combined probability estimation generalization hypothesis testing(HT)

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Current Transformer Polarity Judgment Based on Line Parameter Fitting with Closing Transient Current 17th

Current Transformer Polarity Judgment Based on Line Paramete...

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17th Annual Conference of China Electrotechnical Society, CES 2022

作者： Gu, Qianshuo Cong, Wei Wang, Feng Li, Yiquan Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan250000 China Power Dispatching Control Center of Guangdong Power Grid Co. Ltd. Guangzhou China

ISBN: (纸本)9789819903566

In order to solve the problem of current transformer (CT) reverse connection in power system, this paper proposes a method to judge CT polarity by fitting line parameters with closing transient current. Firstly, the relationship between line parameters and current is studied by deducing the mathematical form of closing current. By using the least square method to fit the sampling values of closing current, the line parameters are obtained. Compare the fitted line parameters with the actual line parameters. If the fitting result is consistent with the actual result, the CT polarity is correct;If the fitting result is contrary to the actual result, the CT polarity is reverse. In order to improve the accuracy of least square fitting, this paper uses matrix pencil algorithm to extract waveform features and realize decoupling among line parameters. Then, the differential equation of closing current is modified, and the remaining parameters are fitted and solved by the least square method. Finally, considering different operating environment and closing angle, the above algorithm is simulated by PSCAD and MATLAB. The simulation results show that when some sampling points are offset, the line parameters fitted by the matrix pencil algorithm are still consistent with the actual parameters. Therefore, the matrix pencil algorithm effectively improves the stability of the method and meets the needs of practical engineering. © 2023, Beijing Paike Culture Commu. Co., Ltd.

关键词： Differential equations

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Wind and PV Power Ramp Events Prediction Based on Long Short-Term Memory Network

Wind and PV Power Ramp Events Prediction Based on Long Short...

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2023 IEEE Sustainable Power and Energy Conference, iSPEC 2023

作者： Wang, Zengwei Li, Zhendong Liu, Yutian Ma, Huan The Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China The State Grid Shandong Electric Power Research Institute Jinan China

ISBN: (纸本)9798350322699

With the increasing penetration rate of renewable generation, the challenges arising from its randomness and intermittent nature are becoming more pronounced. In particular, wind and photovoltaic power ramp events pose a serious threat to the secure and stable operation of power systems, and even lead to frequency instability and load shedding. Based on the long short-term memory neural networks (LSTM), this paper proposes a novel renewable power ramp events (RPREs) forecasting approach. First, filter the key tie-lines. Second, the LSTM network was driven by the known time series of wind, PV, load, and tie-line power to forecast the tie-line power for the next hour, thereby determining the adjustable capacity of the tie-line. Finally, the regulatory capability of the grid is considered to judge the occurrence of a power ramping event. Case study demonstrates that the proposed method can effectively predict power ramping events and meets the requirements of online assessment. © 2023 IEEE.

关键词： LSTM photovoltaic power ramping events forecasting wind power

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Digital twin-oriented multi-physics field simulation analysis of high-voltage SF6circuit breakers

Digital twin-oriented multi-physics field simulation analysi...

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2022 International Conference on Energy Internet and Power systems, ICEIPS 2022

作者： Chen, Jing Zhang, Keqi Liang, Zhenguang Du, Zongzhan Zhang, Hengxu Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Shandong Jinan250061 China

Circuit breakers are important components for removing short circuits in power systems and ensuring safe operation. The operation of circuit breakers may not be predicted and thus cause accidents, so there is an urgent need to innovate means to assess the operation status of power equipment and monitor the operation status of power grids in full real time, to improve the monitoring capability of major key equipment, and to study key technologies for the digital twin of circuit breakers to support the safe and stable operation of transmission networks and the digital transformation of energy systems. This paper establishes the multi-physics field coupling calculation model of the circuit breaker opening process, completes the simulation calculation of the circuit breaker opening process, gets the distribution and change trend of parameters such as electric field, pressure, temperature, density, and airflow speed inside the interrupting chamber, and analyzes the flow characteristics inside the interrupting chamber in different opening processes. We select the characteristic parameters and provide data support for the establishment of fault diagnosis based on the digital twin of the circuit breaker. © Published under licence by IOP Publishing Ltd.

关键词： Electric power transmission networks

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Defect Analysis of Power Equipment Based on Information Extraction Model 6

Defect Analysis of Power Equipment Based on Information Extr...

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2021 6th International Conference on Information Science, Computer Technology and Transportation, ISCTT 2021

作者： Mu, Jinshuang Gao, Zhanjun Zhou, Fengyuan Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Shandong Jinan250061 China

ISBN: (纸本)9783800757282

In operation and maintenance, State Grid has accumulated a large amount of historical equipment defect text data. For problems such as difficulty in text data mining. This paper established a text information extraction model at first. Extract important information such as equipment defect phenomena and defect locations from historical defect data. Based on it, establishing convolutional neural network (CNN) to achieve defect level classification. By comparing classification effect before and after information extraction, results indicate that text information extraction model can improve accuracy of defect level classification model. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Data mining

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A Forecast Error Correction Method Based on Seq2Seq and Auto Encoder for Short-term Wind Power Forecast Enhancement

A Forecast Error Correction Method Based on Seq2Seq and Auto...

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

作者： Ma, Haoyu Yang, Ming Han, Zifen Wang, Bo Che, Jianfeng Li, Menglin Control Shandong University Key Laboratory of Power System Intelligent Dispatch Jinan China State Grid Gansu Power Grid Corporation Lanzhou China China Electric Power Research Institute National Key Laboratory of Renewable Energy Grid-Integration Beijing China

ISBN: (纸本)9798350352290

Accurate wind power forecast (WPF) is highly significant for the safe and economic operation of power systems, and implementing error correction is a common and effective manner to further enhance the forecasting performance. Nonetheless, existing error correction methods fail to consider temporal relationship and may inadvertently increase the error under certain circumstances, thereby compromising the local precision of forecast. In order to address these issues, this paper proposes an error correction model based on Seq2Seq and auto encoder (AE) to improve forecasting accuracy. Firstly, the seq2seq with attention mechanism is introduced to infer the probable error sequence through learning the temporal relationship between the numerical weather prediction sequence and the actual error sequence. Secondly, the samples that the seq2seq providing a positive error inference are collected and the AE model is employed to extract the meteorological features at these moments. Finally, on the basis of the above two models, the error correction method is constructed consisting of preliminary error inference and posterior correction determination. Using operational data from Ningxia province, the proposed method is validated for its remarkable superiority based on the evaluation metrics. © 2024 IEEE.

关键词： Wind forecasting

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Integrated dispatching Model for Power system Incorporating Multiple Modules

Integrated Dispatching Model for Power System Incorporating ...

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Advances in Electrical, Electronics and Computing Technology (EECT), International Conference on

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

ISBN: (数字)9798331541545

ISBN: (纸本)9798331541552

The widespread integration of renewable energy presents significant challenges for power system scheduling. Traditional power system scheduling is mainly based on the concept of “coordinating on a multi-time-level and gradually refining at each level,” using a sequential scheduling framework. However, with the growing integration of renewable energy, the uncertainty in power systems has significantly increased, leading to severe issues such as conflicts in the coordination between different modules. This paper first introduces the scheduling framework of the traditional sequential scheduling model. Then, addressing the problems of module coordination and insufficient flexibility, an integrated multi-time-scale scheduling model is proposed. This model combines day-ahead and intraday scheduling models, optimizing decision variables including unit start/shut states, operation points, and reserves simultaneously to maximize the collaborative potential between different scheduling modules. After linearization, the proposed model is converted into a mixed-integer linear programming (MILP) model, which can be solved directly using commercial optimization solvers. Finally, case analyses demonstrate the effectiveness and superiority of the proposed integrated model compared to the traditional sequential scheduling model.

关键词： Renewable energy sources Analytical models Uncertainty Fluctuations Processor scheduling Refining Regulation Power systems Power system reliability Load modeling

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Knowledge and data jointly driven aeroengine gas path performance assessment method

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Chinese Journal of Aeronautics 2024年第5期37卷 533-557页

作者： Zhe WANG Xuyun FU Rui ZHANG Zhengfeng BAI Xiangzhao XIA Wei JIANG Department of Mechanical Engineering Harbin Institute of TechnologyWeihai 264209China Weihai Key Laboratory of Intelligent Operation and Maintenance Harbin Institute of TechnologyWeihai 264209China Control System Design Laboratory AECC ShenYang Engine Research InstituteShenyang 110015China

Aeroengines,as the sole power source for aircraft,play a vital role in ensuring flight *** gas path,which represents the fundamental pathway for airflow within an aeroengine,directly impacts the aeroengine's performance,fuel efficiency,and ***,timely and accurate evaluation of gas path performance is of paramount *** paper proposes a knowledge and data jointly driven aeroengine gas path performance assessment method,combining Fingerprint and gas path parameter deviation ***,Fingerprint is used to correct gas path parameter deviation values,eliminating parameter shifts caused by non-component performance ***,coarse errors are removed using the Romanovsky criterion for short-term data divided by an equal-length overlapping sliding ***,an Ensemble Empirical Mode Decomposition and Non-Local Means(EEMD-NLM)filtering method is designed to“clean”data noise,completing the preprocessing for gas path parameter deviation ***,based on the characteristics of gas path parameter deviation values,a Dynamic Temporary Blended Network(DTBN)model is built to extract its temporal features,cascaded with Multi-Layer Perceptron(MLP),and combined with Fingerprint to construct a Dynamic Temporary Blended AutoEncoder(DTB-AutoEncoder).Eventually,by training this improved autoencoder,the aeroengine gas path multi-component performance assessment model is formed,which can sufficiently decouple the nonlinear mapping relationship between aeroengine gas path multi-component performance degradation and gas path parameter deviation values,thereby achieving the performance assessment of engine gas path *** practical application cases,the effectiveness of this model in assessing the aeroengine gas path multi-component performance is verified.

关键词： Performance assessment Aeroengine Fingerprint Gas path parameter deviation values Jointly drive

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Optimal Scheduling Considering Multiple Reserves Based on Active Power Curtailment Operation of Wind Power

Optimal Scheduling Considering Multiple Reserves Based on Ac...

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Advances in Electrical, Electronics and Computing Technology (EECT), International Conference on

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

ISBN: (数字)9798331541545

ISBN: (纸本)9798331541552

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.

关键词： Uncertainty Fluctuations Costs Supply and demand Power supplies Wind power generation Power system stability Stability analysis Power system reliability Wind turbines

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Modeling method of photovoltaic power generation grid connection based on particle swarm optimization neural network

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Energy Informatics 2024年第1期7卷 88页

作者： Zhang, Jie Lu, Yuanhong Huang, Libin Guo, Haiping Tu, Liang State Key Laboratory of HVDC China Southern Power Grid Guangzhou510000 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System China Southern Power Grid Guangzhou510000 China CSG Key Laboratory for Power System Simulation China Southern Power Grid Guangzhou510000 China

Aiming at the complex structure, numerous equipment, intricate control and protection logic, as well as the existence of numerous unmodeled dynamics and black-box device models in photovoltaic (PV) grid-connected systems, a modeling method based on Particle Swarm Optimization Neural Network (PSO-NN) is proposed to address the inability of pure mechanism models to accurately simulate their operational dynamics. Utilizing the differences in active power response waveforms under Voltage-Frequency (Vf) control, Power-Reactive Power (PQ) control, and Droop control as criteria for control strategy identification, a PSO-NN model is constructed for PV grid-connected systems, with inputs comprising temperature, humidity, light intensity, voltage, and frequency disturbances, and outputs being active and reactive power. To validate the model's effectiveness, a PV grid-connected system model is built in a self-developed simulation software and connected to an IEEE 14-bus distribution network for simulation verification. The results demonstrate that the proposed PV grid-connected model can effectively identify the types of Vf control, PQ control, and Droop control strategies, and accurately reflect the dynamic response characteristics of active and reactive power under various voltage and frequency disturbances. © The Author(s) 2024.

关键词： Particle swarm optimization (PSO)

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