Stochastic Look-Ahead Commitment: A Case Study in MISO

Bernard Knueven, M. Nazif Faqiry, Manuel Garcia, Yonghong Chen, Roger Treinen, Trevor Werho, Junshan Zhang, Vijay Vittal, Long Zhao, Anupam Thatte, Shengfei Yin

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

Abstract

This paper introduces the Stochastic Look Ahead Commitment (SLAC) software prototyped and tested for the Midcontinent Independent System Operator (MISO) look ahead commitment process. SLAC can incorporate hundreds of wind, load, and net scheduled interchange (NSI) uncertainty scenarios. It uses a progressive hedging method to solve a novel two-stage stochastic unit commitment. The first stage commitment decisions, made only for those generators whose decision to commit or not in each time period cannot be deferred, can cover the uncertainties within the next three hours. The second stage includes both the dispatch for each of the scenarios and the commitment decisions that can be deferred. Study results on 15 MISO production days show that SLAC may bring economic and reliability benefits under uncertainty.

Original languageEnglish (US)
Title of host publication2023 IEEE Power and Energy Society General Meeting, PESGM 2023
PublisherIEEE Computer Society
ISBN (Electronic)9781665464413
DOIs
StatePublished - 2023
Event2023 IEEE Power and Energy Society General Meeting, PESGM 2023 - Orlando, United States
Duration: Jul 16 2023Jul 20 2023

Publication series

NameIEEE Power and Energy Society General Meeting
Volume2023-July
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Conference

Conference2023 IEEE Power and Energy Society General Meeting, PESGM 2023
Country/TerritoryUnited States
CityOrlando
Period7/16/237/20/23

Keywords

  • Stochastic optimization
  • Uncertainty Management
  • Unit Commitment

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering

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