Codazzi, LauraLauraCodazziCsáji, GergelyGergelyCsájiMnich, MatthiasMatthiasMnich2024-08-052024-08-052024International Joint Conference on Artificial Intelligence (IJCAI 2024)978-1-956792-04-1https://hdl.handle.net/11420/48631We introduce and study various models of how prosumers in a microgrid can satisfy their demands of electrical energy while minimizing their costs over fixed time horizon. Prosumers have individual demands, which can vary ay-by-day, and which they can satisfy by either consuming selfgenerating electrical energy locally (e.g., from operating PV panels) or from acquiring energy from other prosumers in the same microgrid. Our models take into account two key aspects motivated by real-life scenarios: first, we consider a daily volatility of prices for buying and selling energy, and second, the possibility to store the selfgenerated energy in a battery of finite capacity to be either self-consumed or sold to other prosumers in the future. We provide a thorough complexity analysis, as well as efficient algorithms, so that prosumers can minimize their overall cost over the entire time horizon. As a byproduct, we also solve a new temporal version of the classical KNAPSACK problem, which may be of independent interest. We complement our theoretical findings by extensive experimental evaluations on realistic data sets.enhttps://creativecommons.org/licenses/by/4.0/Constraint Satisfaction and OptimizationPlanning and SchedulingPlanning and SchedulingPlanning and SchedulingNatural Sciences and Mathematics::510: MathematicsConference Paper10.15480/882.1319510.24963/ijcai.2024/20710.15480/882.13195Conference Paper