A New Scheme for Guaranteed State Estimation of Power System

Wang, Bin; He, Guangyu; Liu, Kaicheng

doi:10.1109/tpwrs.2013.2264917

Cited by 11 publications

(5 citation statements)

References 7 publications

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“…In 1970s, Schweppe first proposed the idea of state estimation in power systems. Power system state estimation constitutes the core of the on-line system monitoring, analysis and control functions [2][3][4][5]. State estimation acts like a filter between the raw measurements received from the system and all the application functions that require the most reliable data base for the current system operation state, and it typically includes bad data processing, state estimation solutions, parameter and topology error processing, and other analyses.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: A Robust WLS Power System State Estimation Method Integrating a Wide-Area Measurement System and SCADA Technology

et al. 2015

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With the development of modern society, the scale of the power system is rapidly increased accordingly, and the framework and mode of running of power systems are trending towards more complexity. It is nowadays much more important for the dispatchers to know exactly the state parameters of the power network through state estimation. This paper proposes a robust power system WLS state estimation method integrating a wide-area measurement system (WAMS) and SCADA technology, incorporating phasor measurements and the results of the traditional state estimator in a post-processing estimator, which greatly reduces the scale of the non-linear estimation problem as well as the number of iterations and the processing time per iteration. This paper firstly analyzes the wide-area state estimation model in detail, then according to the issue that least squares does not account for bad data and outliers, the paper proposes a robust weighted least squares (WLS) method that combines a robust estimation principle with least squares by equivalent weight. The performance assessment is discussed through setting up mathematical models of the distribution network. The effectiveness of the proposed method was proved to be accurate and reliable by simulations and experiments. OPEN ACCESSEnergies 2015, 8 2770

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Section: Introductionmentioning

confidence: 99%

RETRACTED: A Robust WLS Power System State Estimation Method Integrating a Wide-Area Measurement System and SCADA Technology

et al. 2015

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“…Therefore, it is necessary to estimate state intervals considering uncertain pseudomeasurements. The interval state estimation (ISE) based on interval analysis theory is regarded as a suitable solution [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Robust Interval State Estimation for Distribution Systems Considering Pseudo-measurement Interval Prediction

Zhang,

Yan,

Huo

et al. 2024

Journal of Modern Power Systems and Clean Energy

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Interval state estimation (ISE) can estimate state intervals of power systems according to confidence intervals of predicted pseudo-measurements, thereby analyzing the impact of uncertain pseudo-measurements on states. However, predicted pseudo-measurements have prediction errors, and their confidence intervals do not necessarily contain the truth values, leading to estimation biases of the ISE. To solve this problem, this paper proposes a pseudo-measurement interval prediction framework based on the Gaussian process regression (GPR) model, thereby improving the prediction accuracy of pseudomeasurement confidence intervals. Besides, a weight assignment strategy for improving the robustness of weighted least squares (WLS) ISE is proposed. This strategy quantifies the deviation between the pseudo-measurement intervals and their estimated intervals and assigns smaller weights to the pseudomeasurement intervals with larger deviations, thereby improving the estimation accuracy and robustness of the ISE. This paper adopts the data from the supervisory control and data acquisition (SCADA) system of the New York Independent System Operator (NYISO). It verifies the advantages of the GPR method for pseudo-measurement interval prediction by comparing it with the quantile regression and neural network methods. In addition, this paper demonstrates the effectiveness of the proposed weight assignment strategy through the IEEE 14-bus case. Finally, the differences in the estimation accuracy and the bad data identification between the robust interval state estimation and deterministic state estimation are discussed.

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“…Power system state estimation is an effective means to detect the real-time operation data of the power system which was first proposed by the Schweppe in 1970 [1]. Abundant research has been conducted on power system state estimation to optimize the real-time redundant measurement data of the power system, to realize the real-time and reliable monitoring of the power system, and to ensure the safe and reliable operation of the system [2][3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Robust Power System State Estimation Method Based on Generalized M-Estimation of Optimized Parameters Based on Sampling

Hou

et al. 2023

Sustainability

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Robustness is an important performance index of power system state estimation, which is defined as the estimator’s capability to resist the interference. However, improving the robustness of state estimation often reduces the estimation accuracy. To solve this problem, this paper proposes a power system state estimation method for generalized M-estimation of optimized parameters based on sampling. Compared with the traditional robust state estimator, the generalized M-estimator based on projection statistics improves the robustness of state estimation, and the proposed optimized parameter determination method improves the overall accuracy of state estimation by appropriately adjusting its robustness. Considering different degrees of non-Gaussian distributed measurement noises and bad data, the estimation accuracy the proposed method is demonstrated to be up to 23% higher than the traditional generalized M-estimator through MATLAB simulations in IEEE 14, 118 bus test systems, and Polish 2736 bus system.

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A New Scheme for Guaranteed State Estimation of Power System

Cited by 11 publications

References 7 publications

RETRACTED: A Robust WLS Power System State Estimation Method Integrating a Wide-Area Measurement System and SCADA Technology

RETRACTED: A Robust WLS Power System State Estimation Method Integrating a Wide-Area Measurement System and SCADA Technology

Robust Interval State Estimation for Distribution Systems Considering Pseudo-measurement Interval Prediction

Robust Power System State Estimation Method Based on Generalized M-Estimation of Optimized Parameters Based on Sampling

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