2026-07-20T05:25:17Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:6635 2024-03-06T10:38:33Z ddc:004 open_access

Online Energy Storage Management: an Algorithmic Approach Kim, Anthony Liaghat, Vahid Qin, Junjie Saberi, Amin Online Algorithms Competitive Analysis Routing Storage Approximation Algorithms Power Control Motivated by the importance of energy storage networks in smart grids, we provide an algorithmic study of the online energy storage management problem in a network setting, the first to the best of our knowledge. Given online power supplies, either entirely renewable supplies or those in combination with traditional supplies, we want to route power from the supplies to demands using storage units subject to a decay factor. Our goal is to maximize the total utility of satisfied demands less the total production cost of routed power. We model renewable supplies with the zero production cost function and traditional supplies with convex production cost functions. For two natural storage unit settings, private and public, we design poly-logarithmic competitive algorithms in the network flow model using the dual fitting and online primal dual methods for convex problems. Furthermore, we show strong hardness results for more general settings of the problem. Our techniques may be of independent interest in other routing and storage management problems. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Anthony Kim and Vahid Liaghat and Junjie Qin and Amin Saberi 2016 Is Part Of LIPIcs, Volume 60, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2016) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.APPROX-RANDOM.2016.12 urn:nbn:de:0030-drops-66355 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX-RANDOM.2016.12 eng https://creativecommons.org/licenses/by/3.0/legalcode