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Krishan Arora,Deepak Prashar 한국디지털융합학회 2020 IJICTDC Vol.5 No.2
The change in the power demand results in modification of frequency of interrelated power system amongst the dissimilar areas. The load frequency control can be attained by proper regulation of participating producing elements. The Area Control Error (ACE) has to be minimized for the frequency response enhancement and Integral Square Error (ISE) is generally taken as ACE. The aim of Load Frequency Control (LFC) is to diminish the Integral Square Error to Nil with constant variation of claim of dynamic energy so that the entire produced energy of the arrangement and load obligation correctly matches with every element. In this paper, results of multi area interconnected power system under Unilateral Contract are verified with the assistance of conventional controllers.
Power Efficiency Model for Cloud Servers based on a Hybrid Meta-heuristic Optimization Algorithm
Apoorva Tripathi,Deepak Arora 사단법인 인문사회과학기술융합학회 2016 예술인문사회융합멀티미디어논문지 Vol.6 No.8
The burgeoning demand of Cloud infrastructure has engendered an escalation in the energy consumption pattern of the data centers around the globe. The capability to handle multitudinous sizeable applications is a desideratum in today’s data centers. This stirs up the issue of on-demand resourceprovisioning as well as apportioning the workload in accordance with the time- varying demands. Oftentimes, there is a propensity to apportion data center resources statically, to various applications, based on peak load characteristics. This aids in maintenance of isolation, renders good quality of service and performance guarantees. In data center deployments, delivering high performance has been the solitary concern. Its ramification is the negligence of energy consumption in the process. High energy consumption has many repercussions, for instance, it translates to high operational costs, which is entailed by reduction of the marginal profit of Cloud service providers. Its aftermath is high carbon- emissions which are not ecologically friendly. Henceforth, energy-efficient solutions need to be devised so as to curtail the adverse effects of Cloud computing on the environment. Otherwise, Cloud computing with progressively persistent front-end client-devices interrelating with back-end data centers will cause an enormous escalation of energy usage. To address this problem, the concept of Green Cloud computing has been modelled in this work through the usage of ACO and GA optimization technique. This will lead to the decimation in the energy consumption in data centers. The results will be appraised on the basis of total power consumed and number of jobs completed in the MATLAB 2010a environment.