Optimal risk-aware power procurement for data centers in day-ahead and real-time electricity markets

Abstract

With the growing trend in the amount of power consumed by data centers, finding ways to cut their electricity bills has become an important and challenging problem. In this paper, our focus is on the cost reduction that data centers may achieve by exploiting the diversity in the price of electricity in day-ahead and real-time electricity markets. Based on a stochastic optimization framework, we propose to jointly select a data center's service rate and its power demand bids to the day-ahead and real-time electricity markets. In our analysis, we take into account service-level-agreements, risk management constraints, and statistical characteristics of workload and electricity prices. Using empirical electricity price and Internet workload data and through computer simulations, we show that by directly participating in the day-ahead and real-time electricity markets, data centers can significantly reduce their energy expenditure.