Enhancement of power system stability by real-time prediction of instability and early activation of steam turbine fast valving

Robak, S.; Machowski, J.; Skwarski, Mateusz

doi:10.1016/j.egyr.2022.05.285

Cited by 5 publications

(1 citation statement)

References 15 publications

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“…With the rapid development of information technology, big data technology can be seen everywhere in production and life. In the power industry, the construction of the electric power Internet of things makes the power management and information technology fully integrated [1][2][3][4][5]. Power system prediction can provide the development status and level of the current power system, and the power dispatching department formulates the power supply plan according to the power system prediction.…”

Section: Introductionmentioning

confidence: 99%

Short-term electric power prediction in a certain area based on least squares support vector machine

Xie

Gao

2023

Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023)

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Short-term power prediction is one of the important tasks in the daily operation of the energy system. With the popularity of smart grid, it brings more difficulties to the accuracy of electricity prediction. The purpose of this study is to explore the characteristics of short-term power data to achieve efficient and accurate power prediction and provide a reference for power grid operation management. Firstly, according to various characteristics of power prediction, this paper builds shortterm power prediction models by using SVM and LS-SVM, respectively. Then, this paper compares the prediction results of the two single models with the test values. It is found that the prediction curve of the LS-SVM model is better than that of the SVM model, and the LS-SVM prediction model has better potential for prediction short-term power consumption. This indicates that different machine learning models are suitable for different types of electrical power predictions.

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Section: Introductionmentioning

confidence: 99%

Short-term electric power prediction in a certain area based on least squares support vector machine

Xie

Gao

2023

Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023)

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Rotor angle stability improvement by coordinated control of SVC and SSSC controllers

Dahat

Dhabale

2023

Energy Reports

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Enhancement of power system stability by real-time prediction of instability and early activation of steam turbine fast valving

Cited by 5 publications

References 15 publications

Short-term electric power prediction in a certain area based on least squares support vector machine

Short-term electric power prediction in a certain area based on least squares support vector machine

Rotor angle stability improvement by coordinated control of SVC and SSSC controllers

Analysis of the combined effects of SVC and SSSC controllers to improve power system stability

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