A New Hybrid Artificial Neural Network Based Control of Doubly Fed Induction Generator

In this paper, Hybrid Artificial Neural Network (ANN) with Proportional Integral (PI) control technique has been developed for Doubly Fed Induction Generator (DFIG) based wind energy generation system and the performance of the system is compared with NN and PI control techniques. With the increasing use of wind power generation, it is required to instigate the dynamic performance analysis of Doubly Fed Induction Generator under various operating conditions. In this paper, three control techniques have been proposed, the first one is using PI controller, the second one is ANN control, and the third one is based on combination of ANN and PI. The performance of the proposed control techniques is demonstrated through the results, determined by using MATLab/Simulink. From the results it is observed that the dynamic performance of the DFIG is improved with the Hybrid control technique

Predictive Direct Torque Control Strategy for Doubly Fed Induction Machine for Torque and Flux Ripple Minimization

The main drawback of Direct Torque Control (DTC) or Direct Power Control (DPC) is non-constant switching frequency; this drawback can be eliminated by employing predictive DTC. The predictive DTC technique is employed without much complicated online calculations by simply implementing constant switching times for active rotor voltage vectors to reduce torque and flux ripples and achieve constant switching frequency. The predictive DTC strategy has been implemented for RSC of Doubly Fed Induction Machine (DFIM). The performance of the proposed control methodology is compared with the classical DTC method under various operating conditions such as step change in torque, continuous variation of torque command, and the performance of DFIM near synchronous speed. It is found that the performance of the proposed predictive DTC strategy of DFIM is quite good compared to classical DTC strategy

Investigation of THD Analysis in Residential Distribution Systems with Different Penetration Levels of Electric Vehicles

Electric Vehicles (EVs) are becoming a viable transportation option because they are environmentally friendly and provide solutions to high oil prices. This paper investigates the impacts of electric vehicles on harmonic distortions in urban radial residential distribution systems. The accomplishment of EV innovation relies on the accessibility of EV charging stations. To meet the power demand of growing EVs, utilities are introducing EV charging stations in private and public areas; this led to a change in the residential distribution system infrastructure. In this paper, an urban radial residential distribution system with the integration of an electric vehicle charging facility is considered for investigation. An impact of different EV penetration levels on voltage distortion is analysed. Different penetration levels of EVs into the residential distribution system are considered. Simulation results are presented to validate the work carried out in this paper. An attempt has been made to establish the relationship between the level of penetration of the EVs and voltage distortion in terms of THD (Total Harmonic Distortion)

A Novel Approach Using Adaptive Neuro Fuzzy Based Droop Control Standalone Microgrid In Presences of Multiple Sources

In this paper, a novel Q/P droop control strategy for regulating the voltage and frequency in Standalone micro grid with multiple renewable sources like solar and wind is presented. The frequency and voltage control strategy is applied to a Standalone micro grid with high penetration of intermittent renewable generation system. Adaptive Neuro-Fuzzy logic Interface system (ANFIS) controller is used for frequency and voltage control for Renewable generation system. Battery energy storage system (BESS) is used to generate nominal system frequency instead of using the synchronous generator for frequency control strategy. A synchronous generator is used to maintain the state of charge (SOC) of the BESS, but it has limited capacity. For Voltage control strategy, we proposed reactive power/active power (Q/P) droop control to the conventional reactive power controller which provides voltage damping effect. The induced voltage fluctuations are reduced to get nominal output power. The proposed model is tested on different cases and results show that the proposed method is capable of compensating voltage and frequency variations occurring in the micro grid with minimal rated synchronous generator. ©2020. CBIORE-IJRED. All rights reserve

Dynamic performance improvement of standalone battery integrated PMSG wind energy system using proportional resonant controller

The load voltage and frequency should be controlled under steady state and transient conditions in off grid applications. Power quality and power management is very important task for rural communities under erratic wind and load conditions. This paper presents a coordinated Proportional resonant (PR) and battery energy controller for enhancement of power quality and power management in direct drive standalone wind energy system. The dynamic performance of standalone direct drive Permanent Magnet Synchronous Generator (PMSG) is investigated with the proposed control scheme under various operating conditions such as fluctuating wind with step increase and decrease in wind velocity, balanced and unbalanced load conditions. The proposed PR control strategy with battery energy controller also ensures effective power balance between wind and battery source in order to fulfill the load demand. The superiority of the proposed control strategy is confirmed by comparing with the traditional vector control strategy under fluctuating wind and load conditions through MATLAB/SIMULINK platform