Abstract
In this work, the Coyote Optimization Algorithm (COA) is implemented for estimating the parameters of single and three-phase power transformers. The estimation process is employed on the basis of the manufacturer’s operation reports. The COA is assessed with the aid of the deviation between the actual and the estimated parameters as the main objective function. Further, the COA is compared with well-known optimization algorithms i.e. particle swarm and Jaya optimization algorithms. Moreover, experimental verifications are carried out on 4 kVA, 380/380 V, three-phase transformer and 1 kVA, 230/230 V, single-phase transformer. The obtained results prove the effectiveness and capability of the proposed COA. According to the obtained results, COA has the ability and stability to identify the accurate optimal parameters in case of both single phase and three phase transformers; thus accurate performance of the transformers is achieved. The estimated parameters using COA lead to the highest closeness to the experimental measured parameters that realizes the best agreements between the estimated parameters and the actual parameters compared with other optimization algorithms.
Highlights
The transformer is a vital element in electrical power systems
The accurate estimation of the transformer equivalent circuit parameters helps in efficient monitoring process of power transformers
Real time measurements were used by applying frequency response [4] or time domain analysis to obtain an accurate estimation of the transformer parameters [5]–[8]
Summary
The transformer is a vital element in electrical power systems. The failure of transformer or the wrong operation affects the overall power system reliability and performance. The real time measurement process includes load terminal data, phase measurement unit (PMU), inrush current test, open circuit and short- circuit tests This process, in most cases, requires disconnecting the transformer from operation, which is considered an impractical solution. Imperialist competitive and gravitational search algorithms (GSA) have been proposed to estimate the single-phase transformer parameters from name-plate data [25], In addition, Artificial Bee Colony Algorithm was used in [26] to estimate the transformer parameters All of these algorithms can be applied using name-plate or load data during the operation of transformer without having to disconnect the transformer for testing purposes. Experimental tests (open and short circuit tests) are done on single and three-phase transformer to verify the estimated parameters
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