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Power transformer is a vital device in substations. Load and no load losses create a hot spot point in transformer, so it is obviously necessary to limit the core temperature to values that cause no damage to the core itself, adjacent materials, or the oil. Core temperatures as low as 110 C–120 may degrade oil. This has led experts in the field to suggest that 130 C would be a reasonable limit for the core temperature. For this reason, need to a device for local cooling is necessary. Authors in this paper find a novel method for oil cooling in hot spot point or area. Oil spraying device is simulated and then path of pressured oil after shooting in hot spot point, is evaluated. With using of 230/63/20kv Punel substation in Iran data, and after simulation and calculation, authors find that with using of this device utilities could remove their problem for over loading of transformers in the load peak time.

System identification is about building models from data. A data set is characterized by several pieces of information: The input and output signals, the sampling interval, the variable names and units, etc.Similarly, the estimated models contain information of different kinds, estimated parameters, their covariance matrices, and model structure and so on. In this paper we collected Temperature of oil and winding in 230/63kv transformer of SARI Substation and considered the winding temperature for input in the model and oil temperature for out put. After that calculated their data by MATLAB software and get a new model with the good best fit for the heat transfer from core and winding to oil. For verification of were calculated results, has been simulated the process in COMSOL Software.

Hot spot temperature (HST) is the most important parameter in the operation of power transformers. The HST has to be held under a prescribed limit. HST has a considerable effect on the insulation aging. Therefore detecting, monitoring and removing the HST could be a very important and necessary action for Utilities. A new design of oil spraying and its effect, along with a thermal management in a transformer cooling system has been studied in this paper. The effect of oil fluid flow on the HST problem has been considered in this paper; and the calculations and simulation have been performed by Ants algorithm. The simulation results have been validated based on a 230/63/20 kV, 250MVA transformer at the Sari substation in Iran, and the results indicate that the new design could mitigate the limitations of transformer loading due to the HST problem. The Ants algorithm have been proposed and applied for accomplishing this task and to give an improved level of accuracy.

A power loss, heat generation and heat distribution evaluations in a large-scale oil cooled power transformer are presented here, along with the details of computer implementation and experimental verification. In this paper, we consider that core power losses are approximately constant with temperature various or might decreased with that. Winding temperature and oil will increase with the load increasing and might create a hot spot and that is caused by degradation insulation and the loss of life in the power transformer. Therefore the authors tried to Asses these phenomena with use of electrical and thermal soft wares. On the results (with Iranian network data) of simulation showed that in case of oil spraying on the hotspot point or area, very low temperature with the best conditions would be obtained. Then it is best to provide a cooling system with the best insulation and with the minimum side effect on the magnetic and electrical field distribution. Finally by reduction in transformer losses, could savings potential of 22 TWh / year for EU.

Transformers are important and expensive elements of a power system. Inordinate localized temperature rise, hottest spot temperature (HST), causes rapid thermal degradation of insulation and subsequent thermal breakdown. To prescribe the limits of short-term and long-term loading capability of a transformer, it is necessary to estimate the HST of transformer winding to as high a degree of accuracy as can possibly be made. These papers have now improved the accuracy of estimation of hottest spot temperature. Inordinate temperature rise in a power transformer due to load current is known to be the most important factor in causing rapid degradation of its insulation and decides the optimum load catering ability or the load ability of a transformer. The Top Oil Temperature (TOT) and Hottest Spot Temperature (HST) being natural outcome of this process, an accurate estimation of these parameters is of particular importance. IEEE / IEC among others have proposed procedure to estimate the temperatures, however, the accuracy of the predictions are not always as good as are desired. Unacceptable temperature rise may occur due to several fault conditions other than overloading, and hence warrant an online monitoring of the transformer.