Pinto, AngeloPinto, TiagoPraça, IsabelVale, ZitaFaria, Pedro2022-03-172022-03-172018978-1-5386-7954-8http://hdl.handle.net/10400.22/20275Electricity markets are complex and dynamic environments, mostly due to the large scale integration of renewable energy sources in the system. Negotiation in these markets is a significant challenge, especially when considering negotiations at the local level (e.g., between buildings and distributed energy resources). It is essential for a negotiator to be able to identify the negotiation profile of the players with whom he is negotiating. If a negotiator knows these profiles, it is possible to adapt the negotiation strategy and get better results in a negotiation. In order to identify and define such negotiation profiles, a clustering process is proposed in this paper. The clustering process is performed using the kml-k-means algorithm, in which several negotiation approaches are evaluated in order to identify and define players' negotiation profiles. A case study is presented, using as input data, information from proposals made during a set of negotiations. Results show that the proposed approach is able to identify players' negotiation profiles used in bilateral negotiations in electricity markets.engClusteringLocal energy marketsProfile modellingk-means algorithmClustering algorithmsBuildingsconference object10.1109/SmartGridComm.2018.8587572