Interval Optimization Model Considering Uncertainty of Load Regulation for Colocation Data Center

Data centers with high energy consumption have great regulation potential, which can be regarded as an important carrier for power grid companies to carry out demand response business. However, multiple uncertainties severely restrict the decision-making of the data center operators and affect their regulation potential. Given this context, this paper proposes an interval optimization model that considers the uncertainties of load regulation for the colocation data center. First, the uncertainty factors in the load regulation process are analyzed. Then, the coupling relationship between the uncertain factors is analyzed. When using the Stackelberg game to solve the problem of split incentives between the tenants and the data center operator, the association models between the uncertain factors are derived, and the distribution of uncertain factors are deduced. Finally, the interval optimization model is applied to construct the upper-level optimistic solution model and the lower-level pessimistic solution model for the load regulation of the colocation data center. The simulation results verify that the proposed model can formulate the optimization range of load regulation and the interval of operator's profits under multiple uncertainties.