881 Words4 Pages

Optimal integration of renewable energy resources in data centers with behind the meter renewable generator
Abstract
Introduction
Nowadays the consumption of energy has increased rapidly in data centers due to increase in use of internet and cloud computing
The electricity cost of data centers in USA is about $7.4 billion annually.
Design resource management algorithms have been developed to run the data centers more effectively and efficiently this was due to the increasing energy costs in data centers.
Dynamic cluster service configuration is one approach in which load is given only on a subset of machines and turning off the rest of the machines. other machines are switched on only when there is increase in the workload
Another approach*…show more content…*

let L[t] denote the total number of service requests received by the workload distribution at a time slot t and the number of requests to the data center i can be δi[t] so we have , the service requests are handeled in first in first serve order. The rate of service requests being processed from the queue can be denoted by µi[t] We select µi[t] such that, Where both are the parameters specific to data centers The summation of total power consumed at computer server and the total power consumed at the facility gives the total power consumption at the data centers The power usage efficiency PUE for a data center is defined as the ratio of total power consumed at the data center to the power consumed at the computer server. The standard value of PUE for most of the data centers is 2.0 The ratio Ppeak/Pidle denote the power elasticity of the servers. Let Ppeak be the average peak power when server is handling the request and Pidle be the average idle power use of a computer server Higher the value less is the power consumption when server is idle The total power consumption at data center can be obtained by Where, Because of the unpredictable nature of the renewable energy resource the

let L[t] denote the total number of service requests received by the workload distribution at a time slot t and the number of requests to the data center i can be δi[t] so we have , the service requests are handeled in first in first serve order. The rate of service requests being processed from the queue can be denoted by µi[t] We select µi[t] such that, Where both are the parameters specific to data centers The summation of total power consumed at computer server and the total power consumed at the facility gives the total power consumption at the data centers The power usage efficiency PUE for a data center is defined as the ratio of total power consumed at the data center to the power consumed at the computer server. The standard value of PUE for most of the data centers is 2.0 The ratio Ppeak/Pidle denote the power elasticity of the servers. Let Ppeak be the average peak power when server is handling the request and Pidle be the average idle power use of a computer server Higher the value less is the power consumption when server is idle The total power consumption at data center can be obtained by Where, Because of the unpredictable nature of the renewable energy resource the

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