Robust forecasting for unit commitment with wind

Boris Defourny, Hugo P. Simao, Warren Buckler Powell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Given the importance of handling high levels of uncertainty from renewables in the unit commitment problem, there has been increased attention given to the use of stochastic programming methods. Since these are computationally very demanding, there is a need for new approximations. We propose to use a point forecast of energy from wind and loads, where the point forecast is chosen and adapted by simulation to produce a robust solution. Traditionally, point forecasts represent an expectation. In our work, we suggest that we can use an appropriately chosen quantile of the forecast distribution which is optimized within a stochastic environment. The result is a policy search algorithm built around a point forecast, which is easily implementable using standard industry models and algorithms.

Original languageEnglish (US)
Title of host publicationProceedings of the 46th Annual Hawaii International Conference on System Sciences, HICSS 2013
Pages2337-2344
Number of pages8
DOIs
StatePublished - Apr 3 2013
Event46th Annual Hawaii International Conference on System Sciences, HICSS 2013 - Wailea, Maui, HI, United States
Duration: Jan 7 2013Jan 10 2013

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
ISSN (Print)1530-1605

Other

Other46th Annual Hawaii International Conference on System Sciences, HICSS 2013
CountryUnited States
CityWailea, Maui, HI
Period1/7/131/10/13

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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