Reliability Based Min-Max Regret Stochastic Optimization Model for Capacity Market with Renewable Energy and Practice in China

Research output: Contribution to journalArticlepeer-review

52 Scopus citations

Abstract

Capacity market is a long-term clearing model to coordinate the traditional thermal generation and the renewable energy generation, which minimizes the total capacity cost of traditional generation, while satisfying the operational constraints and reliability requirement. Furthermore, to address the uncertainties in the long-term optimal decision, min-max regret is employed to find the optimal solution under the worst regret, generating several representable scenarios that can help generation companies to understand how these scenarios would impact on the future generation planning. Finally, a decomposition method is proposed to solve this reliability based min-max regret stochastic optimization model by bisection. The test results on one regional grid in China show the effectiveness of the proposed model.

Original languageEnglish
Article number8510831
Pages (from-to)2065-2074
Number of pages10
JournalIEEE Transactions on Sustainable Energy
Volume10
Issue number4
DOIs
StatePublished - Oct 2019

Keywords

  • Capacity market
  • min-max regret
  • reliability evaluation
  • renewable energy
  • stochastic programming

Fingerprint

Dive into the research topics of 'Reliability Based Min-Max Regret Stochastic Optimization Model for Capacity Market with Renewable Energy and Practice in China'. Together they form a unique fingerprint.

Cite this