Faria, PedroVale, ZitaSoares, JoãoKhodr, H. M.2013-04-302013-04-302009978-1-4244-5097-8http://hdl.handle.net/10400.22/1475Electricity market players operating in a liberalized environment require adequate decision support tools, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. This paper deals with short-term predication of day-ahead spinning reserve (SR) requirement that helps the ISO to make effective and timely decisions. Based on these forecasted information, market participants can use strategic bidding for day-ahead SR market. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.engArtificial neural networks (ANN)Ancillary servicesMulti-agent systemsSpinning reserveElectricity marketsPower systemsSimulationconference object2013-04-1510.1109/ISAP.2009.5352930