Vale, ZitaMorais, H.Ramos, SérgioSoares, JoãoFaria, Pedro2013-04-182013-04-182011978-1-4577-1000-1978-1-4577-1001-81944-9925http://hdl.handle.net/10400.22/1389In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.engClusteringData miningDemand Response (DR)Energy resources managementIntelligent power systemsLocational Marginal Prices (LMP)Mixed Integer No- Linear Programming (MINLP)conference object2013-04-1210.1109/PES.2011.6039081