Estimation of accuracy of chosen SVC power for steel-making arc furnace

Nikolaev, A.A.; Anokhin, V. V.; Lozhkin, I. A.

doi:10.1109/icieam.2016.7911442

Cited by 7 publications

(4 citation statements)

References 7 publications

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“…Power quality is currently a critical issue, particularly in plants with high power consumers that are occasionally unbalanced [1], [2]. These consumers can be found in metallurgical plants like Electric Arc furnaces [3], [4], Laddle furnaces [5], and rolling mills [1]. These high power consumers use a lot of electricity and can have an impact on power quality via reactive power, low power factor, and electric current harmonics [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Researches regarding power quality at the hot rolling mills’ power supply

Ivascanu,

Militaru,

Panoiu

et al. 2024

J. Phys.: Conf. Ser.

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The study described in the paper was carried out through measurements taken at a feed station in a hot rolling line. The aforementioned measures are appropriate for the purpose of analyzing power quality. The measurements were taken using a three-phase power quality analyzer. Measurements were taken for voltage and current values, as well as for active, reactive, and apparent powers. The analysis of the measurements taken indicates that the power quality is affected by the nonlinearity of the load. As a consequence, the level of reactive power becomes higher, leading to a reduced power factor.

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Section: Introductionmentioning

confidence: 99%

Researches regarding power quality at the hot rolling mills’ power supply

Ivascanu,

Militaru,

Panoiu

et al. 2024

J. Phys.: Conf. Ser.

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show abstract

“…Power quality is currently a critical issue, particularly in plants with high power consumers that are occasionally unbalanced [2]. These consumers can be found in metallurgical plants like electric arc furnaces (EAF) [3,4], ladle furnaces [5], and rolling mills [1]. These high power consumers use a lot of electricity and can have an impact on power quality via reactive power, low power factor, and electric current harmonics [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Power Factor Modelling and Prediction at the Hot Rolling Mills’ Power Supply Using Machine Learning Algorithms

Panoiu,

Ivascanu

2024

Mathematics

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The power supply is crucial in the present day due to the negative impacts of poor power quality on the electric grid. In this research, we employed deep learning methods to investigate the power factor, which is a significant indicator of power quality. A multi-step forecast was developed for the power factor in the power supply installation of a hot rolling mill, extending beyond the horizontal line. This was conducted using data obtained from the respective electrical supply system. The forecast was developed via hybrid RNN (recurrent neural networks) incorporating LSTM (long short-term memory) and GRU (gated recurrent unit) layers. This research utilized hybrid recurrent neural network designs with deep learning methods to build several power factor models. These layers have advantages for time series forecasting. After conducting time series forecasting, qualitative indicators of the prediction were identified, including the sMAPE (Symmetric Mean Absolute Percentage Error) and regression coefficient. In this paper, the authors examined the quality of applied models and forecasts utilizing these indicators, both in the short term and long term.

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“…Nowadays there are technical solutions for mitigating the flicker perturbations at the desired level. Before deciding to adopt specialized equipments for reducing the perturbations, it is necessary to analyse the disturbing source and adopt technical measures [7], like continuous charging of burden material into the furnace [8]. These ones are less costing as the mitigating specialized equipments based on FACTS.…”

Section: Introductionmentioning

confidence: 99%

“…These ones are less costing as the mitigating specialized equipments based on FACTS. The analysis of minimum level of SVC for an electric arc furnace is conducted in [8]. The installation, start-up and performance of a SVC for an electric arc furnace upgrade to modernize a stell melting facility is conducted in [9].…”

Section: Introductionmentioning

confidence: 99%

Assessment of flicker perturbations in power systems with multiple disturbing consumers

Lazaroiu

Golovanov

Elefterescu

et al. 2018

2018 18th International Conference on Harmonics and Quality of Power (ICHQP)

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The connection in the electric network of perturbing loads must be done such that aggregating the all disturbance contributions of the loads to not exceed the threshold levels. The results of a flicker monitoring campaign for a period of 1 month, with several power supply configurations, are reported in this paper. The flicker contribution of each perturbing load was determined such that to establish the share of each end-user to the required investment for a mitigating equipment.

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Estimation of accuracy of chosen SVC power for steel-making arc furnace

Cited by 7 publications

References 7 publications

Researches regarding power quality at the hot rolling mills’ power supply

Researches regarding power quality at the hot rolling mills’ power supply

Power Factor Modelling and Prediction at the Hot Rolling Mills’ Power Supply Using Machine Learning Algorithms

Assessment of flicker perturbations in power systems with multiple disturbing consumers

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