An Evolutionary Approach to Optimize Data Center Profit in Smart Grid Environment

Abstract

Overwhelming energy-related costs mar data center profits. In a smart grid, the price of electricity may change with real-time demand, geographic area, and time-of-use. Data centers with flexible request dispatch and resource allocation capabilities can cooperatively avail these price variations to reduce expenditures and maximize profit. In this paper, we model the data center profit maximization as a constrained multi-objective optimization problem. Our proposed scheme optimizes data center revenue and expense objectives simultaneously and to the best of our knowledge, is the first scheme that provides trade-off solutions for use in varied operational scenarios. The approach utilizes the Strength Pareto Evolutionary Algorithm (SPEA-II) as the base framework and adapts it to devise an algorithm. Our technique finds Pareto optimal solutions for data center profit maximization problem in a smart grid environment. The simulation results prove the efficacy of the proposed technique.