Distribution transformer is the most vital component in the power system. Failure of a transformer leads to loss of revenue besides affecting the reliability of power supply to consumers. It can lead to the non-availability of the transformer for a long duration. Due to this, it is important to maintain the good quality of mineral oil. Thus, if the quality of the mineral oil is reduced then its dielectric strength/quality is degraded. Finally, it can affect the services of the transformer, in terms of continuity of power supply. This paper entails the development of a mathematical MATLAB/Simulink model which able to calculate the life cycle of distribution transformer and exact oil changing frequency. With the help of proposed Matlab/Simulink models, the plot curves between furan content formation versus time, pollution index versus time, and dielectric strength of oil versus time are also prepared. The article methodology uses the newly proposed equations, that are in accordance with IEEE standards: IEEE Guide for Loading Mineral-Oil-Immersed Transformers and Step-Voltage Regulators (IEEE Std. C57.91-2011) and IEEE Guide for the Reclamation of Insulating Oil and Criteria for Its Use (IEEE Std C57.637-2015). Then the case study for a 100 kVA distribution transformer is realized. So, with the input values in the Simulink model of load current of the transformer, dielectric constant of oil and flash point of oil we can estimate the life of the distribution transformer. Harmonic load factor in our research work is not included, in order to reduce influence of harmonic load we need to installed the active filter, which is not covered in this paper.

This paper proposes an adaptive neuro-fuzzy inference system (ANFIS) maximum power point tracking (MPPT) controller for grid-connected doubly fed induction generator (DFIG)-based wind energy conversion systems (WECS). It aims at extracting maximum power from the wind by tracking the maximum power peak regardless of wind speed. The proposed MPPT controller implements an ANFIS approach with a backpropagation algorithm. The rotor speed acts as an input to the controller and torque reference as the controller’s output, which further inputs the rotor side converter’s speed control loop to control the rotor’s actual speed by adjusting the duty ratio for the rotor side converter. The grid partition method generates input membership functions by uniformly partitioning the input variable ranges and creating a single-output Sugeno fuzzy system. The neural network trained the fuzzy input membership according to the inputs and alter the initial membership functions. The simulation results have been validated on a 2 MW wind turbine using the MATLAB/Simulink environment. The controller’s performance is tested under various wind speed circumstances and compared with the performance of a conventional proportional–integral MPPT controller. The simulation study shows that WECS can operate at its optimum power for the proposed controller’s wide range of input wind speed.

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This paper deals with dynamic simulation of a directly driven Permanent Magnet Synchronous Generator (PMSG) with a full scale converter interfaced to the grid. A comparative assessment of two control strategies is the main focus of this paper. The first is the SVM based voltage oriented control strategy and the second is the hysteresis current control strategy. Maximum power point tracking and pitch angle control is also modeled. The controller performance is analyzed through simulation results with various changes in wind velocity.Index Terms-PMSG, pitch control, maximum power point tracking, voltage oriented control, hysteresis current control.