In a technically advanced world where demand is increasing very fast especially large number of non-linear loads and electric vehicles has led to energy crisis and pollution of grid power. Depleting conventional energy sources and environmental concerns has led to integration of large number of distributed energy resources (DERs) at distributional level to resolve problem of energy crisis and reduce emissions. With grid connected to different types of DERs, it is very challenging to manage the power flow, resolve energy crisis and maintain good power quality. Improper energy management may lead to inefficient operation of DERs and may build up stress on energy storage systems (ESS) impacting their life cycle. Thus, it is necessary to use energy management schemes (EMS) for efficient and reliable operation. EMS helps to enhance overall system efficiency and reduce the stress on ESS. This paper presents the analysis of different EMS applied on distribution system for efficient and economic operation of DERs and carryout stress analysis on ESS. Overall system efficiency, Hydrogen utilization in fuel cell, state of charge (SoC) of batteries and supercapacitor are the main parameters considered for performance comparison. To analyze the proposed work a simulation model is designed in MATLAB.
Grid frequency variation causes phase angle deviation in current with respect to voltage. This is sensed at the phase-locked loop in the controller. In past studies the effect of grid frequency variation is neglected while designing the controller for power quality restoration. When modern grids are connected to large numbers of non-linear loads and various types of distributed generation (DG), it results in continuous variation in grid frequency. Thus it is necessary to consider the grid frequency variation for effective power quality restoration. However, tuning of conventional PI controller gains considering frequency variation is very difficult. Thus it is necessary to develop an adaptive intelligent nonlinear controller to tackle the effects of frequency variation, voltage distortion and non-linear load simultaneously. This paper presents the importance of considering the effects of the frequency variation, grid voltage distortion and non-linear load, while designing and deploying a controller for power quality restoration. The proposed controller supplies power to local load as well as transferring surplus power to the grid from DG along with the additional benefit of improving grid power quality. A DG with an ANFIS optimized PI current controller for power quality enhancement is proposed. The method is economical as it requires no additional hardware. Results are compared with PI, PI-RC and fuzzy current controllers to validate the effectiveness of the proposed controller.
Brushless motors has special place though different motors are available because of its special features like absence in commutation, reduced noise and longer lifetime etc., The experimental parameter tracking of BLDC Motor can be achieved by developing a Reference system and their stability is guaranteed by adopting Lyapunov Stability theorems. But the stability is guaranteed only if the adaptive system is incorporated with the powerful and efficient optimization techniques. In this paper the powerful eagle strategy with Particle Swarm optimization and Firefly algorithms are applied to evaluate the performance of brushless motor Where, Eagle Strategy(ES) with the use of Levy's walk distribution function performs diversified global search and the Particle Swarm Optimization (PSO) and Firefly Algorithm(FFA) performs the efficient intensive local search. The combined operation makes the overall optimization technique as much convenient The simulation results are obtained by using MATLAB Simulink software.
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