Integration of renewable energy in power systems is a potential source of uncertainty, because renewable generation is variable and may depend on changing and highly uncertain weather conditions. In this paper we present and evaluate a new method to schedule power-demanding tasks with release times and deadlines under uncertainty, in order to balance demand and uncertain supply. The problem is considered as a multi-agent sequential decision making problem where agents have to deal with uncertainty. Our main contribution is a scenario state representation and an algorithm that computes a belief over future scenarios, rather than states. The algorithm is used to recompute the belief when new information becomes available. Experiments show that our method
matches demand and uncertain supply to reduce grid power consumption, and outperforms an existing online consensus scheduling algorithm.
Original languageEnglish
Title of host publicationThe 10th Annual Workshop on Multiagent Sequential Decision-Making Under Uncertainty (MDSM 2015)
StatePublished - May 2015
EventThe 10th Annual Workshop on Multiagent Sequential Decision-Making Under Uncertainty - Istanbul, Turkey

Conference

ConferenceThe 10th Annual Workshop on Multiagent Sequential Decision-Making Under Uncertainty
Abbreviated titleMSDM 2015
CountryTurkey
CityIstanbul
Period4/05/158/05/15
Internet address

    Research areas

  • planning under uncertainty, scheduling, smart grids

ID: 10647906