Fast Nonconvex SDP Solvers for Large-Scale Power System State Estimation

Lan, Yu; Zhu, Hao; Guan, Xiaohong

doi:10.1109/tpwrs.2019.2950392

Cited by 7 publications

(2 citation statements)

References 35 publications

(82 reference statements)

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“…Te power system dispatching center makes corresponding decisions according to the system operation conditions provided by the power system state estimation, so the state estimation is directly related to the safe operation of the power grid. How to obtain state estimation software with superior performance has been one of the goals of engineering and academic circles for many years [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Identification of Anomaly Detection in Power System State Estimation Based on Fuzzy C-Means Algorithm

Leng

Qiu

2023

International Transactions on Electrical Energy Systems

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In order to estimate the power system accurately and identify anomaly detection in real time, an identification method of anomaly detection in power system state estimation based on Fuzzy C-means algorithm is proposed. Considering the problems of scale and redundancy of power system measurement data, effective measurement data of the power system is extracted by the principal component analysis method. On this basis, the power system state estimation model established by particle swarm optimization support vector machines is used to judge the operational state of the power system. An anomaly detection identification method based on fuzzy C-means algorithm is proposed to cluster the measured data and identify the anomaly detection of power system. The experimental results show that this method can accurately estimate the state of the power system and has the highest identification accuracy for anomaly detection compared with similar methods. When the equivalent measurement data is affected by noise, the identification delay of this method for anomaly detection in a power system is 1 s, and the real-time performance is high.

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Section: Introductionmentioning

confidence: 99%

Identification of Anomaly Detection in Power System State Estimation Based on Fuzzy C-Means Algorithm

Leng

Qiu

2023

International Transactions on Electrical Energy Systems

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“…ing-based robust gradient-descent state estimation (GD-SE) [24]. Many methods of distribution networks are similar to those of transmission networks.…”

Section: Introductionmentioning

confidence: 99%

Outlier Reconstruction Based Distribution System State Estimation Using Equivalent Model of Long Short-term Memory and Metropolis-Hastings Sampling

Xia

Sun

Chen

2022

Journal of Modern Power Systems and Clean Energy

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The accuracy of distribution system state estimation (DDSE) is reduced when phasor measurement unit (PMU) measurements contain outliers because of cyber attacks or global positioning system spoofing attacks. Therefore, to enhance the robustness of DDSE to measurement outliers, approximate the target distribution of Metropolis-Hastings (MH) sampling, and judge the prediction of the long short-term memory (LSTM) network, this paper proposes an outlier reconstruction based state estimation method using the equivalent model of the LSTM network and MH sampling (E-LM model), motivated by the characteristics of the chronological correlations of PMU measurements. First, the target distribution of outlier reconstruction is derived using a kernel density estimation function. Subsequently, the reasons and advantages of the E-LM model are explained and analyzed from a mathematical point of view. The proposed LSTM-based MH sampling can approximate the target distribution of MH sampling to decrease the number of the futile iterations. Moreover, the proposed MH-based forecasting of the LSTM can judge each LSTM prediction, which is independent of its true value. Finally, simulations are conducted to evaluate the performance of the E-LM model by integrating the LSTM network and the MH sampling into the outlier reconstruction based DDSE.

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Trajectory sensitivity analysis-based systematic Q-matrix of DFIG with LQR auxiliary voltage and power compensation for oscillation damping

Abdelsalam

Ahmed

Diab

2022

International Journal of Electrical Power & Energy Systems

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Fast Nonconvex SDP Solvers for Large-Scale Power System State Estimation

Cited by 7 publications

References 35 publications

Identification of Anomaly Detection in Power System State Estimation Based on Fuzzy C-Means Algorithm

Identification of Anomaly Detection in Power System State Estimation Based on Fuzzy C-Means Algorithm

Outlier Reconstruction Based Distribution System State Estimation Using Equivalent Model of Long Short-term Memory and Metropolis-Hastings Sampling

Trajectory sensitivity analysis-based systematic Q-matrix of DFIG with LQR auxiliary voltage and power compensation for oscillation damping

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