Pipelined Learning Automation for Energy Distribution in Smart Grid
The process of learning automation is an intelligent learning model which controls the flow control without any wastage. In the proposed work, a pipelined LA (PLA) model of energy distribution in the smart grid tree network is employed to enhance the efficiency of the distribution process. The PLA employs three phases of operation: (i) load request evaluation phase, (ii) learning automation phase, and (iii) energy calibration phase. First phase evaluates the load request at various levels; energy distribution to various levels is evaluated during the second phase. Finally, calibration of energy adjustment is performed during the third phase to improve the efficiency of the grid network.
The simulation results show that, the proposed technique yields high efficiency and fairness of the smart grid network. PLA simplifies the hardware architecture, reduces processing and control delay, makes flow control easy and improves the accuracy of the DSM.
KeywordAutomation Energy distribution Fairness index Tree network Smart grid
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