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Motivated by the application of energy storage management in electricitymarkets, this paper considers the problem of online linear programming withinventory management constraints. Specifically, a decision maker should satisfysome units of an asset as her demand, either form a market with time-varyingprice or from her own inventory. The decision maker is presented a price inslot-by-slot manner, and must immediately decide the purchased amount with thecurrent price to cover the demand or to store in inventory for covering thefuture demand. The inventory has a limited capacity and its critical role is tobuy and store assets at low price and use the stored assets to cover the demandat high price. The ultimate goal of the decision maker is to cover the demandswhile minimizing the cost of buying assets from the market. We propose BatMan,an online algorithm for simple inventory models, and BatManRate, an extendedversion for the case with rate constraints. Both BatMan and BatManRate achieveoptimal competitive ratios, meaning that no other online algorithm can achievea better theoretical guarantee. To illustrate the results, we use the proposedalgorithms to design and evaluate energy procurement and storage managementstrategies for data centers with a portfolio of energy sources including theelectric grid, local renewable generation, and energy storage systems.

Online Inventory Management with Application to Energy Procurement in Data Centers