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Computation of electromagnetic forces in the windings of amorphous core transformers

Thanh Bao Doan, Tung Doan Duc, Le Tuan-Ho

Archives of Electrical Engineering

2023

Vol. 72, nr 2

521--539

Electromagnetic forces generated by the short circuit current and leakage flux in low- and high-voltage windings of distribution transformers as well as amorphous core transformers will cause the translation, destruction, and explosion of the windings. Thus, the investigation of these forces plays a significant role for researchers and manufacturers. Many authors have recently used the finite element method to analyze electromagnetic forces. In this paper, an analytic model is first developed for magnetic vector potential formulations to compute the electromagnetic forces (i.e., axial and radial forces) acting on the low- and high-voltage windings of an amorphous core transformer. The finite element technique is then presented to validate the results obtained from the analytical model. The developed model is applied to an actual problem.

A combined method for wind power generation forecasting

Le Tuan-Ho

Archives of Electrical Engineering

2021

Vol. 70, nr 4

991--1009

Most of the existing statistical forecasting methods utilize the historical values of wind power to provide wind power generation prediction. However, several factors including wind speed, nacelle position, pitch angle, and ambient temperature can also be used to predict wind power generation. In this study, a wind farm including 6 turbines (capacity of 3.5 MW per turbine) with a height of 114 meters, 132-meter rotor diameter is considered. The time-series data is collected at 10-minute intervals from the SCADA system. One period from January 04th, 2021 to January 08th, 2021 measured from the wind turbine generator 06 is investigated. One period from January 01st, 2021 to January 31st, 2021 collected from the wind turbine generator 02 is investigated. Therefore, the primary objective of this paper is to propose a combined method for wind power generation forecasting. Firstly, response surface methodology is proposed as an alternative wind power forecasting method. This methodology can provide wind power prediction by considering the relationship between wind power and input factors. Secondly, the conventional statistical forecasting methods consisting of autoregressive integrated moving average and exponential smoothing methods are used to predict wind power time series. Thirdly, response surface methodology is combined with autoregressive integrated moving average or exponential smoothing methods in wind power forecasting. Finally, the two above periods are performed in order to demonstrate the efficiency of the combined methods in terms of mean absolute percent error and directional statistics in this study.