Online control of datacenter power supply under uncertain demand and renewable energy
Modern Cloud Service Providers (CSPs) equip their Datacenter Power Supply System (DPSS) with multisources to mitigate power cost, carbon emission, and power outage: (1) multi-markets grid with time-varying energy prices, (2) finite capacity of Uninterrupted Power Supply (UPS), and (3) certain volumes of intermittent renewable energy. With the presence of uncertain renewable sources and datacenter power demand, CSPs have a critical challenge: how to design systematical online control policies that best utilize different characteristics of multisources in a complementary manner to deliver reliable energy to datacenters while minimizing DPSS operation cost. Based on a stochastic optimization model that captures characteristics of DPSS, we apply two-stage Lyapunov optimization to design and analyze an online DPSS control algorithm (OnDPSS). OnDPSS makes decisions on fully utilizing renewable energy, two-timescales power purchasing, and UPS charging/discharging without requiring substantial statistics of system dynamics. Our mathematical analyses and one-month trace-driven simulations have demonstrated both the optimality (in terms of tradeoff between minimization of DPSS operational cost and constraint satisfaction on datacenter availability and UPS lifetime) and system stability (in terms of robustness to time-varying power demand and supply) achieved by OnDPSS algorithm.