Temperature calculation of overhead power line conductors based on CIGRE Technical Brochure 601 in Slovakia

Kanálik, Martin; Margitová, Anastázia; Beňa, Ľubomír

doi:10.1007/s00202-019-00831-8

Cited by 17 publications

(10 citation statements)

References 17 publications

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“…Using the direct monitoring methods, the conductor temperature is measured directly, or by measuring the specific temperature-dependent parameter, such as the conductor sag, mechanical tension or distance from ground [32,45]. Using the indirect monitoring methods, the conductor temperature is obtained by applying a specific mathematical model that uses the measured weather parameters and loading current as input data [46,47]. When using a helicopter or UAV, it is possible to determine the exact conductor temperature at the time of scanning by using the thermographic measurement.…”

Section: The Impact Of the Conductor Initial Temperature Determination Error On The Recalculated Conductor Sagmentioning

confidence: 99%

Advanced Power Line Diagnostics Using Point Cloud Data—Possible Applications and Limits

2021

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The advance in remote sensing techniques, especially the development of LiDAR scanning systems, allowed the development of new methods for power line corridor surveys using a digital model of the powerline and its surroundings. The advanced diagnostic techniques based on the acquired conductor geometry recalculation to extreme operating and climatic conditions were proposed using this digital model. Although the recalculation process is relatively easy and straightforward, the uncertainties of input parameters used for the recalculation can significantly compromise such recalculation accuracy. This paper presents a systematic analysis of the accuracy of the recalculation affected by the inaccuracies of the conductor state equation input variables. The sensitivity of the recalculation to the inaccuracy of five basic input parameters was tested (initial temperature and mechanical tension, elasticity modulus, specific gravity load and tower span) by comparing the conductor sag values when input parameters were affected by a specific inaccuracy with an ideal sag-tension table. The presented tests clearly showed that the sag recalculation inaccuracy must be taken into account during the safety assessment process, as the sag deviation can, in some cases, reach values comparable to the minimal clearance distances specified in the technical standards.

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Section: The Impact Of the Conductor Initial Temperature Determination Error On The Recalculated Conductor Sagmentioning

confidence: 99%

Advanced Power Line Diagnostics Using Point Cloud Data—Possible Applications and Limits

2021

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“…-Further improve smoothness. In a type of superheated steam temperature system characterized by a multi-capacity inertial transfer function model, since the control goal is to maintain a constant superheated steam temperature, it is easy to obtain the steady-state output value of the sub-controller offline from each sub-model [5]. When the system is relatively stable under variable conditions, a first-order inertia link module can be added between the two controllers.…”

Section: Handover Strategymentioning

confidence: 99%

Superheated steam temperature system of thermal power control engineering based on neural network local multi-model prediction

Zhan

Du²,

Dong

et al. 2021

THERM SCI

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The superheated steam temperature object of thermal power plant has the characteristics of time lag, inertia and time-varying parameters. The control quality of the conventional proportional integral derivate controller with fixed parameters will decrease after the object characteristics change. The generalized predictive control strategy of superheated steam temperature based on neural network local multi-model switching can achieve the goal of designing sub-controllers for fixed models under several typical operating conditions. When the system operating conditions change, the effective switching strategy is timely and accurate. Switch to the most suitable controller. The paper proposes a new smooth switching method, which can effectively suppress the large disturbance phenomenon of the object when switching. The simulation results verify the effectiveness of the control strategy.

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“…Li Yonghua used the singular spectrum analysis (SSA) method to segment and reconstruct the preprocessed data, used the mean generating function to reconstruct the reconstructed sequence, and then used it as the input feature, the original sample sequence as the output, and then constructed a BP neural network. [13][14] The model predicts precipitation characteristics at multiple time steps in the future, and experiments show that the prediction effect is better; in machine learning, the support vector machine algorithm also has accurate and efficient prediction capabilities in meteorological prediction, which is a method based on statistical knowledge. This method can avoid high-dimensional over-fitting problems, has fast solution speed and high prediction accuracy.…”

Section: Introductionmentioning

confidence: 99%

Research on Meteorological Prediction Method of High-Voltage Overhead Transmission Line Channel Based on Encoder-Decoder LSTM

Tan,

Sun,

Wang

et al. 2024

Advances in Transdisciplinary Engineering

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Meteorological prediction has important application value in the energy industry and related fields. Accurate prediction of meteorological factors, such as sunshine intensity, ambient temperature and wind speed, is crucial to the operation of power transmission lines and the safety of equipment. However, traditional meteorological prediction methods may suffer from missing data and outliers, as well as challenges in model accuracy and generalization capabilities. This study uses the Encoder-Decoder LSTM network to predict the original wind speed, ambient temperature, and sunshine intensity of power transmission lines, by applying the Bi-LSTM neural network as the encoder of the network and the LSTM neural network as the decoder of the network. Through processing and predictive analysis of data collected from six overhead transmission lines of Hunan Power Grid, we verified that the model has strong feature extraction capabilities for long-term series, and the model has good generalization on unknown data. Not only can it accurately predict key meteorological parameters such as temperature, sunshine intensity and wind speed, but the deviation of the prediction data is small and has good validity and accuracy. It provides reliable meteorological information for the power industry and related fields, especially the application of dynamic capacity expansion technology. method of prediction.

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Temperature calculation of overhead power line conductors based on CIGRE Technical Brochure 601 in Slovakia

Cited by 17 publications

References 17 publications

Advanced Power Line Diagnostics Using Point Cloud Data—Possible Applications and Limits

Advanced Power Line Diagnostics Using Point Cloud Data—Possible Applications and Limits

Superheated steam temperature system of thermal power control engineering based on neural network local multi-model prediction

Research on Meteorological Prediction Method of High-Voltage Overhead Transmission Line Channel Based on Encoder-Decoder LSTM

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