A Reserve Response Set Model for Systems with Stochastic Resources

Nikita G. Singhal, Nan Li, Kory Hedman

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

The uncertainty and variability associated with stochastic resources coupled with the constantly changing system operating conditions introduce new challenges to power systems. Smart, well-designed reserve policies are needed to assist the operators in maintaining system reliability. This paper presents a reserve response set model, which improves upon existing deterministic models. The proposed model aims to address the allocation and deliverability issues associated with reserves by using reserve response set policies and by modeling the predicted post-contingency effects of nodal reserve deployment on critical transmission elements. The performance of the proposed reserve model is compared against contemporary deterministic programs and an extensive-form stochastic program. The results show that the proposed reserve model outperforms the contemporary models and improves the deliverability of reserves post-contingency at reduced costs. All numerical results are based on the IEEE 118-bus and the 2383-bus Polish test systems.

Original languageEnglish (US)
JournalIEEE Transactions on Power Systems
DOIs
StateAccepted/In press - Nov 23 2017

Keywords

  • Ancillary services
  • Computational modeling
  • electricity market design
  • Generators
  • power generation scheduling
  • Power system reliability
  • Predictive models
  • Reliability
  • reliability
  • Stochastic processes
  • stochastic resources
  • Uncertainty

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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