Gubina, Andrej F.Andrej F.GubinaKeane, AndrewAndrewKeaneMeibom, PeterPeterMeibomO'Sullivan, JonathanJonathanO'SullivanGoulding, OisinOisinGouldingMcCartan, TomTomMcCartanO'Malley, MarkMarkO'Malley2011-11-022011-11-022009 IEEE2009-06978-1-4244-2234-0http://hdl.handle.net/10197/3281Paper presented at the IEEE PowerTech 2009 conference, Bucharest, June 28 2009-July 2 2009The paper describes the methodology that has been developed for Transmission System Operators (TSOs) of Republic of Ireland, Eirgrid, and Northern Ireland, SONI the TSO in Northern Ireland, to study the effects of advanced wind power forecasting on optimal short-term power system scheduling. The resulting schedules take into account the electricity market conditions and feature optimal reserve scheduling. The short-term wind power prediction is provided by the Anemos tool, and the scheduling function, including the reserve optimisation, by the Wilmar tool. The proposed methodology allows for evaluation of the impacts that different types of wind energy forecasts (stochastic vs. deterministic vs. perfect) have on the schedules, and how the new incoming information via in-day scheduling impacts the quality of the schedules. Within the methodology, metrics to assess the quality of the schedules is proposed, including the costs, reliability and cycling. The resulting schedules are compared to the Day-ahead and In-day results of the existing scheduling methodology, Reserve Constrained Unit Commitment (RCUC), with the historical data used as the input for calibration.313593 bytes1072 bytesapplication/pdftext/plainenPersonal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.ForecastingPower generating schedulingReserve optimizationStochastic schedulingWind powerWind powerElectric power production--IrelandElectric power production--Northern IrelandStochastic systemsProduction schedulingConference Publication10.1109/PTC.2009.5281936https://creativecommons.org/licenses/by-nc-sa/1.0/