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Equivalent load estimation method for determining railway power requirements under extended feeding conditions using a simplex algorithm
•Power estimation method developed for electric railway under extended feeding condition.•No actual measurements required to provide accurate power requirement estimation.•The optimal capacity of power equipment can be determined through the proposed method. Electric railway system substations (S/Ss...
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Published in: | International journal of electrical power & energy systems 2022-05, Vol.137, p.107770, Article 107770 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •Power estimation method developed for electric railway under extended feeding condition.•No actual measurements required to provide accurate power requirement estimation.•The optimal capacity of power equipment can be determined through the proposed method.
Electric railway system substations (S/Ss) extend the power supply distances under extended feeding conditions to maintain continued service in the event of a failure in an adjacent S/S. Accurate load modeling is thus required to design realistically the capacity of a subway S/S in consideration of the extended feeding conditions. However, it is difficult to measure accurately or predict the amounts of active and reactive power consumed by the load and the location of the load owing to the nature of the moving train load. Therefore, in this paper, we propose an algorithm to estimate the net supplied power accurately from the viewpoint of the S/S over a specific time interval. The algorithm first estimates the power consumed by the load and the location of the load based on actual measured data under normal power supply conditions. Then, the electric train load state estimated in the power-supplying section of each S/S can be used to simulate the system with extended feeding conditions—which is challenging to evaluate and verify in the field—through software-in-loop simulations. |
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ISSN: | 0142-0615 1879-3517 |
DOI: | 10.1016/j.ijepes.2021.107770 |