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Selected Works of Sarah M. Ryan
Presentation
A new approximation method for generating day-ahead load scenarios
Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters
  • Yonghan Feng, Iowa State University
  • Dinakar Gade, Iowa State University
  • Sarah M. Ryan, Iowa State University
  • Jean-Paul Watson, Sandia National Laboratory
  • Roger J.B. Wets, University of California, Davis
  • David L. Woodruff, University of California, Davis
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Document Type
Conference Proceeding
Disciplines
Publication Version
Accepted Manuscript
Link to Published Version
http://dx.doi.org/10.1109/PESMG.2013.6672564
Publication Date
1-1-2013
DOI
10.1109/PESMG.2013.6672564
Conference Title
2013 IEEE Power and Energy Society General Meeting
Conference Date
July 21-25, 2013
Geolocation
(49.2827291, -123.12073750000002)
Abstract

Unit commitment decisions made in the day-ahead market and resource adequacy assessment processes are based on forecasts of load, which depends strongly on weather. Two major sources of uncertainty in the load forecast are the errors in the day-ahead weather forecast and the variability in temporal patterns of electricity demand that is not explained by weather. We develop a stochastic model for hourly load on a given day, within a segment of similar days, based on a weather forecast available on the previous day. Identification of similar days in the past is based on weather forecasts and temporal load patterns. Trends and error distributions for the load forecasts are approximated by optimizing within a new class of functions specified by a finite number of parameters. Preliminary numerical results are presented based on data corresponding to a U.S. independent system operator.

Comments

This is an accepted manuscript of a proceedings published as Y. Feng, D. Gade, S. M. Ryan, J-P Watson, R. J-B Wets, and D. L. Woodruff, A New Approximation Method for Generating Day-Ahead Load Scenarios, IEEE Power and Energy Society General Meeting, July 2013. Posted with permission.

Rights
© 2013 IEEE. Personal 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.
Copyright Owner
IEEE
Copyright Date
2013
Language
en
File Format
application/pdf
Citation Information
Yonghan Feng, Dinakar Gade, Sarah M. Ryan, Jean-Paul Watson, et al.. "A new approximation method for generating day-ahead load scenarios" Vancouver, BC, Canada(2013)
Available at: http://works.bepress.com/sarah_m_ryan/83/