Risk limiting dispatch

Robert Entriken, Pravin Varaiya, Felix Wu, Janusz Bialek, Chris Dent, Aidan Tuohy, Ram Rajagopal

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

Risk Limiting Dispatch (RLD) is a new framework that integrates complex inputs and allows decision makers to balance tradeoffs and quantify benefits from increased flexibility and improved forecasting. This paper describes a process of forward-contracting for production capacity while considering the full range of operational uncertainties in generation, demand, forecasts, prices, and the risks of unmet demand or excess generation in real time. RLD accounts for reducing uncertainty, increasing costs, and the opportunity for corrective action at future decision points as one approaches that moment. The stochastic formulation of RLD integrates multiple uncertainties into a unified framework and accepts all kinds of probability distributions. This dynamic optimization approach is comprehensive and considers the flexibility of recourse actions taken at later decision stages, when updated information and improved forecasts become available. For instance, Smart Grid sensor data can be used to update the conditional probability distributions in the formulation. A reliability constraint is accommodated directly in terms of the power balance between supply and demand in real time. Alternative quantitative measures of the risk of power imbalance can be incorporated. For example, optimization can be conducted under the requirement that the risk of power imbalance in real time should be less than 0.1% (or any number).

Original languageEnglish
Title of host publication2012 IEEE Power and Energy Society General Meeting, PES 2012
PublisherIEEE Computer Society
ISBN (Print)9781467327275
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 IEEE Power and Energy Society General Meeting, PES 2012 - San Diego, CA, United States
Duration: 22 Jul 201226 Jul 2012

Publication series

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

Conference

Conference2012 IEEE Power and Energy Society General Meeting, PES 2012
Country/TerritoryUnited States
CitySan Diego, CA
Period22/07/1226/07/12

Keywords

  • Optimal Control
  • Optimal scheduling
  • Power system economics
  • Risk analysis
  • Stochastic systems
  • Wind Energy

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