Optimal energy scheduling under time-of-use tariffs

Abstract The efficient use of energy can offer substantial cost savings to companies. Precise scheduling is an effective way to improve energy efficiency, since it typically requires little capital investment and has a short payback period. However, making optimal scheduling decisions can be complicated by frequent price changes in the marketplace. This creates a large-scale energy cost minimization problem, which can be difficult to solve. We study this problem for a manufacturing or computer resource with discretely variable speeds, where energy usage increases with speed. We provide a scalable optimal algorithm for minimizing energy cost with discrete speeds under frequently changing energy prices. The result is a more precise, faster and more scalable planning tool for scheduling to control energy costs than is currently available.